Across Eras, and through evolutions, from Stone Age to Modern Age, from Barter System to Cashless Era, from Agriculture and Hand-made Era to I 5.0 , Businesses across Sectors Re-invent themselves in a quest to stay Relevant amidst Socio Politico Economic ESG Legal Technological (SPEELT) Advancements and Changes. The adages, One has to keep Moving to stay Relevant and One has to be Faster than the Nearest to Grow. These certainly suit both People & Organizations – for I believe both People & Organizations are two sides of the same Coin and alignment is crucial to sustain positive momentum.

The Beginnings: Skill & Outcomes

Transition from Agriculture to Industrial Era can be considered as the beginning of a Formal Business Environment, colloquially known to be the advent of Trade Mechanism. Businesses were focused on Delivering Products with a little or no machinery. Sculptures and Monuments across the Globe are testimony to Control on Products & Aesthetics though Hand Made.

Wood, due to ease of working, was mostly the base. Dependence was more on skill and fitment was the only requirement. Classy the outcomes where and still commanding huge values in Antiques Market – that’s the first level of Excellence, neither product nor process based, but sheer outcome based. People Skill was the basis of this Excellence and still makes one wonder how such achievements were possible then without proper so called Engineering Knowledge.

World has come a full circle. Even today, recognition accorded to Hand Made, Custom Built Products command the highest prices in their respective segments – across sectors, starting from Watches, Gems & Jewelries to Automobiles.

Stabilization: Product & Production

Thanks to World Wars, Consumption and Demand were so high, Mechanization was a necessity. Focus on making and delivering products faster, as availability became a key to succeed at the War Front. Excellence then was Speed all across – right from procurement to point of usage. Critical Requirements were – Product & Availability, on time every time.

Improvisation – Product & Performance

Post World War Scenario resulted in abundant unutilized Capacities in Mechanized Factories, compounded by Economic circumstances. Usage shifted from that of Need for Country to that of Need for People. Products were beginning to be made and marketed for Personal Use. Naturally, due to underutilized Capacities, Supply was more than that of Demand. Purchasing shifted to Buying to that of Selling. People began to Choose rather than Accept. Hence need for Product Differentiation arose. Quality became a Decision Factor. Second Stage of Excellence – Product Performance.

Consolidation: Quality & Performance

When Performance is used as Leverage for Sales, naturally Consistency becomes important. Reliability will then be a result of Repeatability. Its easier said for Tangible Products, were Performance can be Measured. Therefore Measurements & Standardizations were introduced. Means and Ways to Measure Customer Satisfaction in Services were beginning to be introduced – using attributes. Belief was, if You Cant Measure, You Cant Improve. Measurements were the next level of Excellence – both during Process and Usage. Quality Control (QC) lead Quality Assurance (QA) became the norm that decided an Organizations Market Standing and Success.

This was aided by Consumer Era. Various Laws and Protection acts came in to protect the Users. Therefore became the Drivers of Product Quality induced Performance. Alongside, when World became a Single Market due to Globalization, Products and Services Standards were to be defined. ISO for Systems and Country Specific Product/ Services Requirements were introduced.

Differentiation: Value for Money, USP to UVP

As a result of Globalization, Protection gave way to Easy Access. Consumers needed something more than Quality – Cultural Aspects & Market Characteristics though played a role. Quality & Performance began to be Measured with respect to Price – Criteria can be as per People Priorities and Needs. Demographic Dividend induced Product Positioning (STP – Segment, Target, Position) was needed for Targeting Product based on Performance with respect to Price. Era of Positioning Excellence – whoever could rightly Position their Products or Services (Differentiated Offerings) as per well segmented Consumer Needs succeeded. Customers began to be the King in Business Cycle.

Value Proposition: UVP to EVP

Education induced Awareness further influenced the Demographic Dividend and their respective choices. As Consumers started moving up the Needs Triangle, Differentiation began to be Value Based more than that of Feature Based – shift from Mass to Class. Emotion and Engagement began to influence Decisions – Consumers identified & associated themselves with Brands. Era of Branding Excellence and Branding Premium, lead to further segmentation – Branded & Nonbranded Segment, Organized and Unorganized Segment apart.

Mass Customization: Beyond EVP

Advent of Consumer Needs identification tools, further lead to Super Positioning (Micro Segmentation). Ability to understand and leverage specific customer expectations improved the Market Standing of the Brands, as the markets began to consolidate around Customer Growth. This was also necessitated due to Dealer Point stocks of all Generic and Standard Products. In order to meet specific customer aspirations, which began as Premium Segmentation within a Segment, Automotive Industry introduced FMS (Flexi Manufacturing Systems) to meet low volume variety mix requirements. Later, consumer durables industry adopted such practices and offered customers to make their own designs within a Boundary.

Services Industry and in General Management too, FMS was introduced as Flexi Management Systems, including the choice of working days and hours. Thanks to COVID, work from home became an option and MBO (Management By Objectives) began to be advocated in real sense.

Consumerism: Safety & Security – Protection Laws

Regulatory environment evolved alongside changes in Demographic Preferences for products and services. Consumer Protection Acts ensured products and services meet the promised Quality and Performance. Naturally focus shifted to Process Management from that of Product Management. QA gave way to QC, with an objective to arrest process variations within permissible limits so as to ensure Products & Services are more than desirable levels. 6-Sigma came in handy both in Process Management and as a Management Tool easily recognizable by Stake Holders.

Across Business Processes, 6-Sigma as a Philosophy gained traction and got entrenched. Necessity to ensure Deliverables Consistently by controlling Process Variations, thanks to 6Sigma Philosophy, Business Management has become Metrics Driven.

Beyond 6-Sigma: Eternal Success

There is always a Question – Does Management Tool or Systems ensure Business Success and thus Sustainability? Going by the Success Rates across the Globe, only about 35% of Businesses demonstrate their agility to sustain Growth & Profitability. Majority of such Organizations are usually characterized by their ability to stay relevant by both Product & Process Innovation. Infact, 6-Sigma philosophy helps in Structuring even the Innovation Process.

Therefore, its a foregone conclusion that 6-Sigma helps to stay Optimal but for sure does not ensure Sustainability. Business Sustainability can only be ensured interms of adaptability and competitiveness to outperform the closest competitors and substitutes / alternates. 6-Sigma Philosophy when adopted in SPEELT Driven Organization, may at best help to understand the status, which probably can be used to Re-position & Re-orient for Growth & Profitability. Even if You are Excellent & Efficient, You cannot remain there for long

It is to be remembered, even in the era of IOT and AI, there are many products which command a Premium when Handmade and are targeted to meet very personal consumer aspirations. It is then, Consumers chase such Brands and not the other very common way. Even when the delivery is longer, Consumers prefer to wait until serviced without even considering possibility of an alternate choice. Every Businessman dreams to be there, but a very few, I repeat – only a very few, make it real.

About the Author :

Dr. NITHYANANDAN DEVARAAJ (NITHIN) BE., MBA., Ph.D
Independent Board Member, Business Excellence Expert, Technical Due Diligence & Capability Assessor.
Managing Partner – SAAE Enterprises
President – Coimbatore Management Association
Past National Secretary – The Institute of Indian Foundrymen.
Former MD / CEO of a German & Japanese MNC
Chairman – Shri Avinashiappar Trust
Past Managing Director & CEO – Flow Link Systems (P) Ltd ( a Voith Group Company )

Dr. Nithin has about 35 + Years of Experience in Engineering Manufacturing organizations. He has worked for LMW Group, L&T, Hitachi & CRI Group. He is considered to be a Professional with a rare blend of Intrapreneurial Orientation, having been a Business Head across Engineering Manufacturing Organisations / Industries.

Dr. Nithin is an Intrapreneur with hands on experience establishing medium & large scale end to end Value Chain Manufacturing Organizations (from Castings to Finished Products) for Indian Corporates and MNCs, driving Growth & Profitability by Building, Sustaining and Growing High Performance Teams.

Dr. Nithin is a Member in Governing Council / Board Of Studies of Universities and Management Institutions as a Management Expert.

Dr. Nithin is part of various industrial associations and professional bodies; he is credited with playing a leading role in bringing land mark changes in Export Incentives, Classification of MSMEs, CPCB Norms, Waste & Disposal Management. He also plays a pivotal role in training and development of educated Youth seeking employment opportunities.

Dr. Nithin Leads a team that turned around a division and a Company, and in establishing large scale projects as bench marks in industry (This Business has won several awards at National & Regional Level which includes – Indian Foundry of the Year, Young Foundryman and Foundryman Awards, 4Star Award from CII, Green Award & Safety Award from Tamil Nadu Government & at National Level from IIF, First Indian Foundry in the segment to get OHSAS 18001 & ISO 50001 Certification and Many Kaizen awards.)

Dr. Nithin is a Managing Trustee of a Family Managed Trust involved in activities like rendering Food, Shelter, Education and Medicare. Noted for rendering services during Chennai, Kerala, Tanjore & Nilgiris Floods.

Dr. Nithin’s Academics:

• Ph.D in Management Sciences
• MBA in Finance & Marketing – Gold Medalist and University Topper
• BE Mechanical Engineer with Distinction
• An IRCA certified lead auditor and assessor for ISO 9001.
• A qualified auditor for EMS, OHSAS & EnMS
• L&T Future Leaders Training at IIM – C

Dr. Nithin’s Professional Associations:

• Member & Industry Nominee, Coimbatore Disaster Management Council
• A Guest Faculty to Premier Management Institutes & Was  Visiting Faculty to IIM – Calicut
• An examiner for Management Qualifications & Assessor for Management Teachers
• An acknowledged management trainer and consultant
• Is a regular Business Column Writer.

Dr. Nithin is a Member of:

• Foundry Development Council, Ministry of Commerce & Industries, India.
• Institution of Engineers, All India and Coimbatore Management Association
• Board of Studies in Universities & Premier Management Institutes

Dr. Nithin is Winner of:

• The Outstanding Alumni & Distinguished Alumni Awards from PSG Institutions & Bharathiar University.
• The CMA Golden Jubilee Year Best Manager award for the region.
• The Best Management Student award and many accolades at National Level.
• The Mother Teresa Award of Excellence for Young Business Managers.

Dr. Nithin’s Management Interests:

• Management of Innovation, Corporate Strategic Planning and Manufacturing Management, Green Supply Chain

Dr. Nithin can be contacted at :

Mobile : +91 94879 46900 , +91 99653 11288

LinkedIn | Twitter | Facebook | E-mail | E-mail2 | Youtube | Youtube

Also read Dr. NITHYANANDAN DEVARAAJ’s earlier articles:

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From a distance, a flamingo looks like poetry standing on one leg. Up close, at mealtime, it looks like it’s having some kind of episode.

Watch one feed and you’ll see it plunge its head underwater, twist its neck until the bill points backward toward its own feet, then snap that bill open and shut so fast the water seems to chatter. At the same moment its webbed feet stomp and shuffle through the mud, and its whole body rocks and bobs like it’s dancing to music no one else can hear. Researchers who study these birds have long admitted the whole routine looks less like feeding and more like slapstick comedy.

Steven Whitfield, who oversees terrestrial and wetlands conservation at the Audubon Nature Institute in New Orleans, has watched this behavior for years and still calls it strange. Flamingos are filter feeders, straining shrimp, algae, and tiny seeds out of murky water through the ridged plates lining their curved bills, functioning something like a living colander. But the real puzzle was the orientation. Why would a bird feed with its head turned upside down and its bill pointed away from the food sitting right in front of it?

A research team led by Victor Ortega-Jiménez, working alongside biophysicist Saad Bhamla at Georgia Tech, set out to answer that question. What they found, recently published in the Proceedings of the National Academy of Sciences, reads less like a fluke of nature and more like an engineering blueprint. Every motion the bird makes generates a small, precisely shaped vortex in the water. The upward flick of the head as it breaks the surface spins a tiny funnel that lifts hidden prey within reach. The rapid chattering of the bill draws a current of food up toward the mouth. Even the seemingly clumsy foot-stomping produces a matched pair of swirling currents that push shrimp and algae straight toward the waiting beak.

In other words, the head faces backward because that is precisely where it needs to be. The bird’s whole body, from the webbing between its toes to the sharp L-curve of its bill, is tuned to produce the exact fluid motion required to gather scattered food into a single mouthful. Bhamla, whose work focuses on how living creatures exploit physics to solve problems, described the flamingo as an animal that plays with fluid dynamics using its beak, its legs, its neck, and its head as one coordinated instrument.

It’s worth sitting with how improbable that coordination really is. Randomness is good at producing noise. It is not good at producing orchestration. What the study actually documents is a closed loop of interdependent parts: a bill shaped to catch exactly what the feet stir up, a neck long enough to reach the disturbance the feet create, and timing precise enough to sync the chattering to the rhythm of the vortex. Take away any single piece and the whole mechanism falls apart. That isn’t what blind trial and error piling up over millions of accidental years tends to produce. That is what a plan looks like. Layered, purposeful engineering like this points toward a Designer who equipped the flamingo, on purpose, to thrive in the exact murky, food-scarce world it was placed in.

Whitfield, who wasn’t involved in the research, put it simply: there are still mysteries tucked inside even the most familiar-looking creatures, and a bird as odd as the flamingo probably has more of them waiting than most.

Here’s what should make anyone working in business intelligence sit up straighter. The flamingo’s feeding ritual might appear to be a cute metaphor. Instead, it’s a field-tested, published, peer-reviewed model of what it actually looks like to be an intelligently-designed, tightly integrated system operating inside a noisy, cluttered environment. There are at least three lessons worth stealing from a bird most people only think about at the zoo.

1. Insight lives inside the noise, not outside of it

A flamingo doesn’t wait for the water to clear before it eats. It goes looking in the murkiest, most cluttered part of the marsh, because that’s where the food actually is. Clear water in a flamingo’s world is water that’s already been picked over.

Most organizations treat messy data the same way an amateur birdwatcher treats a muddy pond: as an obstacle to route around. Things like raw transaction logs, half-structured support tickets, sensor feeds, and scattered spreadsheets from six departments that never talk to each other come to mind. The instinct is to wait for someone to clean it all up before doing anything useful with it. But the companies that actually extract value from their data are the ones willing to wade directly into the clutter, build the filtering mechanism first, and trust that the signal is in there. The mud isn’t the problem. Refusing to enter it is.

2. Passive observation catches nothing; you have to stir the water yourself

This is the part of the flamingo story that surprises people most. The bird doesn’t hold still and wait for shrimp to drift past its bill. It actively disturbs the water. It stomps, it bobs, it manufactures the very currents that bring hidden prey within reach. Stillness would starve it.

A shocking number of business intelligence programs are built around stillness. A dashboard gets built, a report gets scheduled to land in an inbox every Monday morning, and everyone assumes the insight will simply surface on its own if they stare at the numbers long enough. From decades of experience, I can tell you without a doubt: it won’t. The organizations that consistently find the trend before a competitor does are the ones that go stir the pond: running exploratory queries nobody asked for, cross-referencing datasets that were never designed to talk to each other, testing hypotheses instead of waiting for a chart to confess something interesting. The vortex has to be created. It doesn’t show up on its own.

3. No single part does the job alone

The flamingo’s trick works only because several systems operate in concert. Pull any one thread and the whole thing unravels. A functioning business intelligence operation looks the same way, and it typically needs more than three moving pieces to actually work:

• A pipeline that reliably pulls raw data in from wherever it lives, without silently dropping records along the way
• A governance layer that keeps definitions consistent, so “active customer” means the same thing in every report
• An analytics engine capable of finding the pattern, rather than merely displaying whatever number was easiest to pull
• A delivery layer that gets the finding in front of the person who can actually act on it, at the moment it still matters

Companies love to invest heavily in one of these, usually the flashy dashboard everyone sees on a big screen in the lobby, while starving the other three. That’s the equivalent of a flamingo with a perfect bill and no functioning feet. The bill alone catches nothing; the feet alone are useless. It’s the coordination between the parts, not the elegance of any single one, that produces the result.

None of this is an accident, whether in the flamingo’s marsh or in a well-run business intelligence operation. A bird doesn’t stumble into a four-part synchronized feeding mechanism by luck, and a company doesn’t stumble into a functioning data strategy by luck either. Both require something built with intention, piece fitted to piece, for a specific purpose.

Which brings the story full circle. Picture that flamingo again, head submerged, bill pointed backward, feet churning up the very mud it needs to eat. From the shoreline, an untrained eye sees a bird that’s confused, feeding upside down, doing everything wrong. Get close enough to understand the physics, and you realize it’s doing the one thing that actually works, engineered down to the shape of its toes, for exactly this task in exactly this water.

That’s the posture worth remembering the next time a data strategy looks backward at first glance. The months spent on unglamorous pipeline work. The data governance meetings nobody wants to sit through. The willingness to go stir up the noisy, uncomfortable parts of the business instead of waiting for a clean report to land in an inbox. None of it looks elegant from the shore. All of it is exactly where the food is.

The flamingo was never fumbling. It was built for this. The only question left is whether the BI systems inside your own organization were built with the same intention, or just left to feed however they happen to land.

“Bringing Data to Life and Life to Data”

About the Author:

Dr. Joe Perez,
Team Lead / Senior Systems Specialist,
NC Department of Health and Human Services

Dr. Joe Perez ( Dr.Joe ) is also the Chief Technology Officer – CogniMind

To book Dr. Joe Perez for your speaking engagement please click here

Dr. Joe Perez was selected as the 2023 Gartner Peer Community Ambassador of the Year.

Dr. Joe Perez is a truly exceptional professional who has left an indelible mark on the IT, health and human services, and higher education sectors. Dr. Joe Perez journey began in the field of education, where he laid the foundation for his career. With advanced degrees in education and a doctorate that included a double minor in computers and theology, Dr. Joe Perez embarked on a path that ultimately led him to the dynamic world of data-driven Information Technology.

In the early 1990s, Dr. Joe Perez transitioned into IT, starting as a Computer Consultant at NC State University. Over the years, Dr. Joe Perez’s dedication and expertise led to a series of well- deserved promotions, culminating in his role as Business Intelligence Specialist that capped his 25 successful years at NC State. Not one to rest on his laurels, Dr. Joe Perez embarked on a new challenge in the fall of 2017, when he was recruited to take on the role of Senior Business Analyst at the NC Department of Health, Human Services (NCDHHS). His impressive journey continued with promotions to Senior Systems Specialist and Team Leader, showcasing his versatility and leadership capabilities.

In addition to his full-time responsibilities at NCDHHS, Dr. Joe Perez assumed the role of
fractional Chief Technology Officer at a North Carolina firm in October 2020. An Amazon best-selling author with over 21,000 followers on LinkedIn and numerous professional certifications, he is a highly sought-after international keynote speaker and recognized expert in data analytics and visualization.

Dr. Joe Perez’s contributions have not gone unnoticed. Dr. Joe Perez is a recipient of the IOT Industry Insights 2021 Thought Leader of the Year award, the 2023 Gartner Peer Community Ambassador of the Year award, and Top Ten Global Thought Leader for several categories at Thinkers360 in four consecutive years (2023-2026). Dr. Joe Perez holds memberships in several prestigious Thought Leader communities, and was recently inducted into the United Nations Global Network of Data Officers and Statisticians. Dr. Joe Perez’s reach extends to more than twenty countries worldwide, where he impacts thousands through his speaking engagements, articles, and status as a Distinguished Fellow in the Public Sector Network’s Future Government Institute.

Beyond his professional achievements, Dr. Joe Perez’s passion for teaching remains
undiminished. Whether as a speaker, workshop facilitator, podcast guest, conference emcee, or team leader, he continually inspires individuals to strive for excellence. He treasures his time with his family and is a gifted musician, singer, pianist, and composer. Joe also dedicates his skills through involvement in his church’s Hispanic ministry. Dr. Joe Perez manages the publication of a widely recognized monthly military newsletter, The Patriot News, and is deeply committed to his community.

To maintain a balanced life, Dr. Joe Perez is a regular at the gym, and he finds relaxation in watching Star Trek reruns. He lives by the philosophy that innovation is the key to progress, and he approaches each day with boundless energy and an unwavering commitment to excellence. Dr. Joe Perez’s journey is a testament to the remarkable achievements of a truly exceptional individual, and more importantly, to the amazing grace of God.

Dr. Joe Perez is Accorded with the following Honors & Awards :

https://www.linkedin.com/in/jwperez/details/honors/

Dr. Joe Perez is Bestowed with the following Licences, Certifications & Badge:

https://www.linkedin.com/in/jwperez/details/certifications/

https://www.thinkers360.com/tl/badge/19985/2764

Dr.Joe Perez is Voluentering in the following International Industry Associations & Institutions :

https://www.linkedin.com/in/jwperez/details/volunteering-experiences/

Dr.Joe Perez can be contacted at :

E-mail | LinkedIn | Web | Sessionize | FaceBook  | Twitter | YouTube

Also read Dr.Joe Perez‘s earlier articles:

The post Great BI Strategy appeared first on Industry4o.com.

EVTOL: Navigating Certifications, Air Mobility Regulations, and Battery Energy Density

As per Vertex Market Research, the eVTOL Aircraft Market is poised for significant growth during the next decade. Global eVTOL Aircraft market is projected to achieve a Compound Annual Growth Rate (CAGR) of approximately 30% during the forecast period from 2026 to 2035.

In 2025, worldwide eVTOL Aircraft Market stood at around US$ 600 Million. The Global eVTOL Aircraft Market size is projected to reach an estimated US$ 18 Billion by 2035. Vertex projects the eVTOL aircraft unit sales estimated to cross 4,000 – 5,000 units by 2035, up from around 250 unit sales deliveries recorded in 2025 (consisting primarily of uncrewed autonomous platforms and military evaluation prototypes).

eVTOL Aircraft Market is driven by several structural drivers such as growing urbanization and increasing traffic congestion, and the rising demand for clean, efficient, and sustainable transportation modes. Technological advancements in electric propulsion systems and battery technologies, coupled with growing consumer demand for fast, efficient, and flexible point-to point urban mobility, are accelerating the adoption of eVTOL platforms.

Additionally, increasing ongoing public-private investments, and strategic collaborations are fueling product development and deployment. The eVTOL aircraft market is also benefiting from a growing range of applications, from air taxis and urban shuttle services to emergency medical transport, private aviation, leisure air tours, and defense and logistics use cases. The integration of vertiports, electric charging infrastructure, and smart city mobility ecosystems is further catalyzing the commercial rollout of eVTOL aircraft globally.

The 2026 Freeze Point

Many players within the eVTOL industry consider 2026 to be the crucial “freeze point” for eVTOL aircraft development. To meet intended 2027-28 launch dates, OEMs will need to firm up aircraft design and crucial technology decisions over the next twelve months. Future alterations to designs and technologies at a late stage of certification could compromise project timelines and costs significantly. Regulators are solidifying the certification standards and operational requirements for these new aircraft, and therefore manufactures have turned attention from aircraft design and development towards regulatory compliance, testing and certification, making 2026 a significant point for the transition.

The eVTOL regulation landscape is rapidly advancing as governments and aviation authorities work to implement clear paths for commercialization. In late 2025, Europe solidified its lead when EASA finalized certain components of its SC-VTOL certification scheme, offering aircraft manufacturers increased regulatory clarity during design and approval stages.

In March 2026, commercialization was pushed forward in the U.S. When the FAA selected six eVTOL companies including Joby and Archer to move forward into a second phase of its eIPP allowing pre-certified aircraft to begin operating in a controlled environment.

Increased global regulatory cooperation occurred in June 2026 when the FAA and EASA met to discuss the alignment of certification standards-a necessary precursor to allowing aircraft certified in one region to operate efficiently in another. China pushed its ambitions to lead advanced air mobility when revised civil aviation regulations will take effect in July 2026 mandating local governments to harmonize management of low-altitude air corridors and vertiports, ultimately promoting increased rollout speeds, reduced regulatory risks and greater opportunity for widespread eVTOL commercialization across the globe.

Battery Chemistry and Energy Density: The Key to eVTOL Scalability

Vertex states that the future growth of the eVTOL sector will be greatly determined by battery technology. Jet fuel provides a very high energy density, but current batteries offer a significantly lower energy density and therefore range, payload capacity and operational efficiency. One difficulty in operating eVTOL craft is that there are two distinct power requirements – one to provide a high power burst for landing, takeoff and hovering and another for sustainable, efficient flight (cruise flight). Conventional battery chemistries are unable to provide both a high power and energy density simultaneously, prompting eVTOL manufacturers to develop a combination of different battery chemistries, with one system used for landing, takeoff and hovering flight, and another used for cruise flight.

As per Vertex Market Research, the eVTOL technology road-map indicates a steady increase in battery energy densities; current aviation-grade lithium ion batteries achieve energy densities in the range 250-300Wh/kg and are capable of short-range operations. The arrival of semi-solid state and silicon-anode batteries with higher energy densities of 300-350Wh/kg are projected to deliver a 30-50% increase in range. Further ahead, solid-state and lithium-metal batteries with predicted energy densities exceeding 400-500Wh/kg may deliver substantial increases in flight range, higher payloads and improved economics. Overall, battery innovation should prove one of the most critical enablers for large-scale eVTOL commercialization and fleet development up to 2035.

EVTOL Market Concentration and Competitive Landscape

As per Vertex, the Global eVTOL Aircraft Market is segmented based on System Component, Lift Design & Configuration, Propulsion Type, Mode of Operation, Range, Maximum Take-Off Weight (MTOW), and Application. By System Component, the market comprises Aerostructures & Interiors, Avionics, Batteries & Cells, Electric Motors & Engines, Software & Platforms, and Other Systems. Based on Lift Design & Configuration, it is categorized into Multirotor, Lift + Cruise, Vector Thrust, and Other Configurations. By Propulsion Type, the market includes Battery Electric, Hybrid Electric, and Hydrogen Electric aircraft.

Based on Mode of Operation, the market is segmented into Piloted, Semi-Autonomous, and Autonomous platforms, while Range is classified into Up to 200 km and Above 200 km. By MTOW, the market is divided into Up to 500 kg, 501–1,500 kg, and Above 1,500 kg aircraft. Based on Application, the market covers Air Taxis, Air Shuttles & Air Metros, Private Transport, Air Ambulance & Medical Emergency Services, Leisure & Recreational Flights, and Other Applications, reflecting the industry’s broadening commercial use cases.

Innovation and strategic alliances are rapidly reshaping the Global eVTOL Aircraft Market as firms strive to reach certification, develop scaled manufacturing, and commence commercial operations. Key participants include Archer Aviation, ARC Aero Systems, AutoFlight, BETA Technologies, EHang, Electra Aero, Eve Air Mobility, Jaunt Air Mobility, Joby Aviation, LIFT Aircraft, Manta Aircraft, Sarla Aviation, SkyDrive, The ePlane Company, Vertical Aerospace, Volant Aerotech, Wisk Aero, and XTI Aerospace, which are heavily investing in obtaining aircraft certifications, developing battery technology, enabling autonomous flight, scaling manufacturing processes and forging commercial ties with airlines, infrastructure companies, and mobility service operators. Investments and technology partnerships continue to define competition in this rapidly evolving sector as it moves from concept development to full commercial application.

In contrast, the market is extremely challenging, with multiple leading developers not able to keep on commercially developing its product for long term. Several eVTOL programs have been abandoned, suspended, or driven to bankruptcy because of lacking funding, delays in certification, technical complexities, or not clear commercial feasibility. There have been a number of setbacks such as Lilium, Volocopter, Overair, Supernal (Hyundai), Urban Air Mobility programs (Airbus), Nexus program (Textron), Urban Aeronautics and Kitty Hawk, which underscore the extensive funding required, regulatory complexities, and execution risks associated with bringing eVTOLs from concept to commercial operation.

About Vertex Market Research

Vertex Market Research is a trusted and reliable market intelligence and consulting firm headquartered in Australia, with research and sales operations across the United States and India. We deliver high-quality market insights, industry analysis, and customized research solutions that help businesses make informed strategic decisions.

Recognized as a reputable source for market research, Vertex Market Research is committed to accuracy, transparency, and data-driven excellence. Our team of experienced analysts and industry experts provides actionable intelligence across diverse sectors, empowering organizations worldwide to identify opportunities, mitigate risks, and achieve sustainable growth.

Vertex Market Research & Consulting (VMRC) is a one-stop destination for your all research requirements. We are a market intelligence and consulting firm with comprehensive experience and rich knowledge of the market research business intelligence, and advisory industry.

Vertex Market Research & Consulting (VMRC) has a vast repository of the latest market research reports, and top company profiles, along with the latest market statistics released by our dedicated industry experts. Our vast repository of research reports across various categories gives you a complete view of the ever-evolving trends and current topics worldwide.

At Vertex Market Research & Consulting (VMRC) the data bank is monitored by teams of subject matter experts which are validated by various statistical data and trending content.

Being a reliable market research company, Vertex Market Research & Consulting (VMRC) guarantee readers of reliable information based on the study of factual data of the past, and present scenarios of the market.

What Vertex Market Research & Consulting (VMRC) Do – Our Services :

Vertex helps clients make informed business decisions. Vertex offers market intelligence research ensuring relevant and fact-based research across a range of industries including chemicals, materials, energy, healthcare, and technology.

Vertex Market Research & Consulting (VMRC) to be Contacted at :

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Mobile : +91-99750 17086 , WhatsApp : +91 – 99750 17086

The post eVTOL Aircraft appeared first on Industry4o.com.

Over the last few months, I have been closely observing the evolution of Artificial Intelligence, Robotics, Cloud Computing, Quantum Computing, and Sustainable Energy. While many people view these as separate industries, I believe they are becoming one interconnected technology ecosystem that will define the next several decades of economic growth.

At the same time, a second reality is emerging.

The AI conversation is shifting away from blind excitement and toward practical business value. We are moving from experimentation to execution, from hype to measurable outcomes, and from isolated innovation to integrated transformation.

The organizations that understand this shift early will become the leaders of the next industrial revolution.

The AI Industry Is Growing Up

For the last few years, AI discussions were dominated by possibilities:

Today, the market is becoming more realistic.

Business leaders are asking new questions:

These questions are healthy because true technological transformation is never about hype. It is about sustainable value creation.

The companies winning today are not necessarily deploying the most advanced AI models. They are deploying AI where it delivers measurable business outcomes.

The Two Realities of AI: Bottlenecks and Breakthroughs

We are witnessing two parallel realities.

Reality 1: The Bottlenecks

Cost Pressures

Organizations are discovering that running advanced AI models at scale is expensive.

Many enterprises are now evaluating whether they should rely on external AI providers or build optimized models internally.

The industry is rapidly moving toward:

The question is no longer “Can AI do this?”

The question is:

“Can AI do this profitably?”

Agentic AI Is Progressing More Slowly Than Expected

Fully autonomous agents remain a huge opportunity, yet real-world deployment continues to face challenges:

Businesses operating in healthcare, financial services, manufacturing, and logistics cannot afford costly mistakes.

As a result, many organizations are adopting a Human + AI model rather than complete automation.

Enterprise Caution

Large companies are becoming more selective about where AI can be trusted.

Critical functions still require:

This does not mean AI is failing.

It means AI is maturing.

Reality 2: The Breakthroughs

While challenges exist, innovation continues at unprecedented speed.

Scientific Discovery

AI is increasingly accelerating scientific research.

Material discovery, drug development, climate modeling, and advanced simulations are now benefiting from AI-powered analysis that can reduce years of research into significantly shorter cycles.

Mass Adoption

For the first time in history, AI capabilities are reaching billions of users through platforms they already use daily.

This creates a powerful feedback loop:

• More users
• More data
• Better models
• Faster innovation

Next-Generation Models

AI models continue to improve in:

The future is not about one giant model.

The future is about ecosystems of specialized intelligence working together.

The Ultimate Technology Value Chain

Many investors and business leaders examine AI, Cloud, Quantum Computing, and Sustainable Energy independently.

I believe this is a mistake.

These technologies form a single value chain.

AI & Robotics: The Brain and Hands

AI provides intelligence.

Robotics provides execution.

Together they create physical automation capable of working in factories, warehouses, hospitals, farms, and homes.

Future robots will not simply follow programmed instructions.

They will:

Just like human workers.

Cloud Computing: The Nervous System

Advanced AI requires massive computational resources.

Most enterprises cannot host these capabilities locally.

Cloud infrastructure provides:

Without the cloud, modern AI cannot operate at enterprise scale.

Cloud is the digital nervous system connecting everything.

Quantum Computing: The Accelerator

As AI models become larger and more sophisticated, classical computing eventually faces limitations.

Quantum computing represents the next major leap in processing capability.

Potential applications include:

Quantum computing may not replace classical computing soon, but it will significantly accelerate solving the world’s most complex problems.

Sustainable Energy: The Foundation

This is perhaps the most overlooked part of the technology revolution.

Every AI model, cloud data center, and future quantum computer consumes enormous amounts of energy.

Without sustainable energy, technological growth becomes unsustainable.

That is why global technology companies are investing heavily in:

Sustainable Energy is not a separate industry anymore.

It is becoming the foundation of the digital economy.

The Missing Piece: Cultural Intelligence

One area that receives far less attention is cultural adaptation.

Technology often assumes a standardized global user.

Human behavior does not work that way.

Consider something as simple as eating a meal.

Different regions use:

A robot trained on generic global data may perform impressively in a laboratory but fail immediately in a local household environment.

The future of AI will not belong only to the companies with the most data.

It will belong to the companies with the most relevant data.

Why Local Intelligence Matters

For AI and robotics to truly become universal, three major developments are required:

1⃣ Integrated AI Ecosystems

Today’s technology landscape is fragmented.

Imagine combining:

The productivity gains could be extraordinary.

2⃣ Real-Time Validation Systems

Future AI systems must continuously evaluate their own decisions.

This means:

Trustworthy AI will outperform merely powerful AI.

3⃣ Hyperlocal Data Infrastructure

The world needs more:

True intelligence is contextual.

Global intelligence without local understanding remains incomplete.

India’s AI Opportunity

India stands at a remarkable crossroads.

With over 1.4 billion people, millions of businesses, and one of the world’s most vibrant digital ecosystems, the opportunity is enormous.

Yet AI adoption remains relatively early compared to its full potential.

Many organizations are still limiting AI usage to:

The next stage will be enterprise-wide transformation.

Where India Can Leapfrog

Manufacturing

Healthcare

Retail

Logistics

Enterprise Functions

The opportunity is not simply AI adoption.

It is AI-driven business transformation.

The Leadership Challenge

The future does not belong solely to data scientists.

It belongs to leaders who can connect:

Technology alone does not create value.

Business outcomes create value.

The leaders who understand both technology and business transformation will become the architects of the next growth cycle.

Final Thoughts

We are entering a new era where AI, Robotics, Cloud Computing, Quantum Computing, and Sustainable Energy are converging into one interconnected ecosystem.

At the same time, success will require more than technology.

It will require:

The biggest winners of the next decade will not be those chasing every new technology trend.

They will be those who understand how all these technologies work together to solve real-world problems at scale.

The future is not AI alone.

The future is the intelligent integration of technology, energy, infrastructure, and human understanding.

About the Author :

Mr. Chandrakumar T 
Enterprise Sales Leader
Honeywell Technologies

Mr. Chandrakumar is an Enterprise Sales Leader with 20+ years of experience helping organizations accelerate growth through telecom, IT infrastructure, AIDC, and automation solutions.

Mr. Chandrakumar has partnered with 60+ strategic enterprise accounts across India, consistently achieving 100–120% of quota targets while building long-term, trust-based relationships.

Mr. Chandrakumar approach blends proven sales methodologies such as Challenger Sale and Miller Heiman with deep expertise in SaaS, cloud, and cybersecurity platforms.

Mr. Chandrakumaris passionate about translating complex technologies into business outcomes that improve efficiency, reduce costs, and create measurable value for customers.

Mr. Chandrakumar believes in being a trusted advisor to customers – guiding them through digital transformation journeys and enabling sustainable success.

Mr. Chandrakumar actively share insights on automation, SaaS, and enterprise sales strategies, engaging with peers, customers, and industry leaders to exchange ideas and best practices.

Mr. Chandrakumar is Bestowed with the following Licenses & Certifications:

https://www.linkedin.com/in/chandrakumar-t-b495bb22/details/certifications/

Mr. Chandrakumar can be contacted at :

LinkedIn | E-mail | Website 

#ArtificialIntelligence #AI #MachineLearning #GenerativeAI #Robotics #CloudComputing #QuantumComputing #SustainableEnergy #DigitalTransformation #ERP #SaaS #Automation #Industry40 #Industry50 #Innovation #FutureOfTech #TechStrategy #DeepTech #CleanTech #Infrastructure #Leadership #BusinessTransformation #IndiaGrowthStory #Technology #TechTrends

The post India’s AI Moment appeared first on Industry4o.com.

Artificial intelligence is becoming one of the most important forces in healthcare. Every day, we see new models, new tools, and new promises about how AI can support diagnosis, reduce workload, improve patient care, and transform clinical operations.

But as healthcare leaders, engineers, researchers, and clinicians look toward the future, one question matters more than ever:

Are we building AI systems that simply produce answers, or are we building systems that truly understand the patient journey?

This distinction is important.

Healthcare is not just a data problem. It is a context problem.

A patient is not defined by one lab result, one diagnosis code, one medication, or one clinical note. A patient’s health story is built over time through many connected signals: lab trends, symptoms, medications, procedures, diagnoses, vitals, imaging reports, provider notes, and changes that may happen slowly across months or years.

In many healthcare systems, this information exists, but it is often fragmented. One part may sit inside an electronic health record. Another may be hidden in clinical notes. Another may appear in lab reports, claims, medication history, or previous encounters.

The challenge is not only collecting this data.

The challenge is connecting it in a meaningful way.

That is where the next generation of healthcare AI needs to evolve.

Prediction Alone Is Not Enough

Many AI systems today are designed to predict risk. They may predict the likelihood of disease, hospital readmission, adverse events, or clinical deterioration.

Prediction is valuable, but in healthcare, prediction alone is not enough.

If an AI system says, “This patient is at high risk,” the clinician still needs to know:

Why is this patient at risk?
Which clinical signals contributed to that risk?
How did the patient’s condition change over time?
Are the lab trends, medications, and diagnoses connected?
Is this a temporary abnormality or part of a larger pattern?
Can the explanation be trusted?

Without clear reasoning, AI becomes difficult to use in real clinical workflows.

Healthcare decisions require trust. Trust requires transparency. And transparency requires more than a final answer.

It requires explanation.

This is why the future of healthcare AI should focus not only on prediction, but also on clinical understanding.

The Patient Story Matters

In real healthcare, timing matters.

A lab value from today may look normal when viewed alone, but when compared with results from the past five years, it may reveal a slow decline. A medication may seem unrelated until it is connected with symptoms, abnormal lab results, and prior diagnoses. A clinical note may contain an early warning sign that does not appear clearly in structured data.

This is especially important in conditions such as chronic kidney disease, sepsis, oncology, adverse drug events, and long-term disease progression.

These conditions are rarely understood from one data point. They require a broader view.

They require systems that can look across time.

This is where longitudinal patient intelligence becomes powerful.

A strong healthcare AI system should be able to analyze how a patient’s health has changed over time, identify patterns, connect related events, and present those insights in a way that clinicians can understand quickly.

The goal is not to replace clinical judgment.

The goal is to support it.

 Why Knowledge Graphs Matter in Healthcare AI

One of the biggest opportunities in healthcare AI is the use of knowledge graphs.

A knowledge graph can help connect different parts of a patient’s clinical history. Instead of treating each data point separately, it can represent relationships between patients, conditions, lab results, medications, procedures, symptoms, and clinical events.

For example, a patient may have a history of diabetes, hypertension, changing kidney function, medication adjustments, and abnormal lab values. Individually, these details may appear across different systems. But together, they can form a meaningful clinical pattern.

A knowledge graph helps AI understand these relationships more clearly.

It gives structure to complex healthcare data.

It allows the system to answer not just “what happened,” but also “how things are connected.”

This is important because healthcare is relationship-driven. Conditions influence medications. Medications influence lab results. Lab trends influence risk. Past diagnoses influence future outcomes.

When AI systems can understand these connections, they become more useful, more explainable, and more aligned with how clinicians think.

The Role of Small Language Models

Large language models have shown impressive capabilities, but healthcare does not always need the largest model for every task.

In many clinical workflows, focused and efficient models can be more practical.

Small language models can be designed for specific healthcare use cases, such as extracting clinical entities, summarizing patient risk, identifying medication-related concerns, or generating clinician-readable explanations.

They can also be more cost-effective, easier to control, and better suited for regulated environments when designed properly.

The future may not be one large model doing everything.

It may be a system of specialized models working together, supported by clinical rules, knowledge graphs, retrieval systems, validation layers, and human oversight.

This approach can make healthcare AI more reliable.

It can also reduce hallucination, improve traceability, and make the system easier to evaluate.

AI Should Explain in Human Language

One of the most important parts of healthcare AI is communication.

Clinicians do not need a system that simply returns a score.

They need a system that explains the reason behind the score.

A useful AI system should be able to say:

The patient’s risk appears elevated because kidney function has declined over multiple lab cycles, blood pressure has remained high, and there is a history of diabetes that may contribute to disease progression.

That type of explanation is far more useful than a number alone.

Healthcare AI should translate complex data into clear clinical narratives.

It should help clinicians see the key signals faster.

It should reduce the time spent searching across disconnected records.

It should bring important patterns to the surface.

Most importantly, it should communicate in a way that supports action.

Building Healthcare AI Responsibly

Healthcare AI must be built with discipline.

This means strong engineering, strong evaluation, and strong governance.

A healthcare AI system should be tested not only for accuracy, but also for reliability, fairness, explainability, privacy, and safety. It should be validated against real clinical workflows. It should be reviewed by clinicians. It should be monitored over time.

The system should also make its reasoning traceable.

If an AI system provides a clinical recommendation or risk explanation, users should be able to understand which data points contributed to that output.

This is how trust is built.

Not through impressive demos.

Not through marketing language.

But through reliable systems that can be evaluated, audited, improved, and safely used in real environments.

The Real Opportunity

The real opportunity in healthcare AI is not just automation.

It is clarity.

Healthcare teams are already dealing with information overload. The problem is not that clinicians lack data. The problem is that they often have too much data, spread across too many places, with too little time to connect everything manually.

AI can help by reducing noise and surfacing what matters.

It can support earlier detection of risk.

It can help identify patterns across years of patient history.

It can assist with adverse drug event review.

It can summarize complex clinical timelines.

It can support diagnostic reasoning while keeping humans in control.

This is where AI can create real value.

Not by replacing healthcare professionals, but by giving them better tools to make faster, safer, and more informed decisions.

The Future of Healthcare AI

The next chapter of healthcare AI should be built around four principles:

Connection, because patient data must be understood across systems and timelines.

Explanation, because clinicians need to know why an AI system reached a conclusion.

Trust, because healthcare decisions require transparency, validation, and safety.

Impact, because the goal is not technology for technology’s sake, but better care, better workflows, and better outcomes.

Healthcare AI should not stop at prediction.

It should connect the dots.

It should explain the patient story.

It should support clinical judgment.

It should reduce burden.

It should help healthcare teams move from fragmented data to meaningful insight.

That is the future worth building.

A future where AI is not just intelligent, but responsible.

Not just powerful, but understandable.

Not just automated, but clinically meaningful.

And not just focused on answers, but focused on helping people receive better care.

Mr. Rahul Reddy Hanumanthgari is an AI Engineering Leader, researcher, and IEEE Senior Member specializing in building production-grade AI systems for healthcare and enterprise platforms.

Mr. Rahul currently contributes to AI-driven engineering initiatives at Labcorp, where his work focuses on applying large language models, agentic AI workflows, and intelligent automation to improve clinical data processing and diagnostic operations.

With over a decade of experience in software engineering, automation, and distributed systems, Mr. Rahul now focuses on designing scalable AI platforms that integrate large language models, retrieval-augmented generation (RAG), and modern AI orchestration frameworks to transform complex healthcare data into actionable insights.

Mr. Rahul is also an active contributor to applied AI research, with work exploring areas such as fairness evaluation in large language models, AI-assisted clinical decision support, and intelligent patient monitoring systems. His research and engineering work aim to advance responsible, trustworthy, and scalable AI systems in real-world environments.

In addition to his technical work, Mr. Rahul regularly engages with industry leaders and C-level executives, helping organizations understand and adopt AI-driven strategies for innovation and operational transformation. He has also delivered expert-level talks and technical presentations on AI engineering, intelligent automation, and emerging AI architectures.

As a judge, Mr. Rahul brings a practitioner’s perspective on technical depth, scalability, and real-world impact, evaluating innovations not only for novelty but also for their ability to translate advanced AI research into reliable, production-ready systems.

Mr. Rahul Reddy Hanumanthgari is Bestowed with the following Certifications :

https://www.linkedin.com/in/rahul-reddy-hanumanthgari/details/certifications

LinkedIn  | ORCID 

The post AI in Healthcare appeared first on Industry4o.com.

AI – Artificial, rather, Alternative Intelligence, matters the most now than ever, especially in the Manufacturing Value Chain. Necessity drives the adoption, as India embarks on its journey to ensure Manufacturing Contributes to atleast 25% of GDP, which shall make India more relevant in the Global Economy. Demographic Dividend, both Domestic and Global, determines the choices and preferences of emerging Society, and therefor Technology Adoption.

In a Populous Country like India, its important benefits of the Value Chain are quintessential to gain Social Equilibrium and Market Buoyancy. India shadowed so far by the exuberant neighbor has to leverage all possible means to move up from being an Alternative to a Preferred choice to Chinese Counterparts.

Evolution of Manufacturing

From post war Industrial Era through Consumer & Information Era, the current era can be termed as Intelligence Era. GDP has grown to present levels, despite getting skewed towards Services, only because of the Growth in Manufacturing Value Chain, ably supported by Domestic Consumption – A stark difference to that of Export Oriented China, which also gives India a cushion from external turbulences.

Automation

Transition though gradual, I sincerely believe adoption of Changes by Indian Organizations have been appropriate – balancing the Societal Readiness and Investment Costs (which is presumably highest amongst Industrialized Nations). Initial Choices of adoption were to improve productivity to match market consumption – focus was on numbers and hence automation was limited to increasing out puts. This is the time Society was in need of a Choice other than that of Agriculture. Education level was moderate, relying on training and skilling. Automating production was the beginning of Artificial Alternative.

Computerization

Near saturation levels in Market and availability of Choices, brought in a need for Product Differentiation – by means of Quality and Consistency, reflected by Branding. Consumers sought to be identified with Brands. Need for containing Human Errors, supported by improvement in Societal Education Levels called for next level of Technology adoption. This is when Computerization happened in Manufacturing, aided by development of stepper motors. Second Level of Artificial Alternative – technically known to be Computer Aided Manufacturing (CAM), on line programming and consistent quality with improved productivity. Parallely, Computer Aided Designing (CAD) was automating the most people dependent process – Design.

Integration

By and large, though technology remained same, focus on further improving through-put times, resulted in off-line programing, higher cutting speeds, feed rates and elimination of non-cutting times. Cabling induced integration techniques (Computer Integrated Manufacturing) helped in integrating CAD-CAM, so as to eliminate the Lag Time and interpretation errors by direct on-line transfer of Data from Design to Manufacturing. Next level of Alternative Intelligence, focused on improving Quality and Through Put times, Consistently. Manufacturing evolved into boundary less.

Globalization

Universalization of Products called for Process Management requiring Quality Management Systems. Focus shifted from Output Quality to Process Quality. Beginnings were laborious documentation consuming precious human efforts, and most of the times creating a Parallel Organization. Audits were mostly fault finding rather than value adding, to begin with. Documentation accuracies mattered more than shop floor necessities. Over the years, as the Organizations matured, QMS became a powerful Process Management Tool, benefits compounded by Six Sigma & TQM (Total Quality Management)/ TPM (Total Preventive Maintenance) practices. And got integrated with CAM & MIS, seamlessly.

MIS

CIM facilitated automated Data Capturing. Parallel development of Information Technology helped in Automated Data Management (Management Information Systems) – next level of Alternative Intelligence. Subsequent developments through BPR (Business Process Re-engineering) induced further improvements in Human Productivity by eliminating NVAs (Non Value Adding Activities). In the process, Speed and Accuracies too improved, apart from eliminating the need for Physical Data Storage, saving costly storage space. Next level of Alternative Intelligence.

FMEAs

VA (Value Analysis) – VE (Value Engineering) supported by developments in CAE (Computer Aided Engineering) facilitated Product Design & Performance Optimization through Failure Mode Effect Analysis (FMEAs) – both Products & Processes. Concept of Value For Money became a powerful differentiating tool. Next level of Alternative Intelligence.

IOT & Sensors

Sensors, all kinds, were beginning to be deployed liberally for Real Time Data Management, completely limiting Human involvement, thereby further improving Human Productivity, Quality and Consistency. Next level of Alternative Intelligence. Tangible benefits apart, IOT and Sensors also enhanced Management of Safety and Wastes, which became an integral part of EMS (Environment Management Systems), OHSAS (Health & Safety Management Systems) & EnMS (Energy Management Systems).

Extended Organizations

ICT (Information & Communication Technology) further supported Collaborative Commerce and Concurrent Engineering, making QFD (Quality Function Deployment) in which all stake holders are part of (Customers, Employees, Suppliers & Regulators) much easier. This helped to further cut down on Product Development and Commercialization times (nearly 75% improvement).

Next stage of integration through CRM (Customer Relationship Management) helped eliminate time lapses and improve speed & accuracy in Commercial Processes (Materials and Financial Management, including Banking and Regulatory Processes). Next level of Alternative Intelligence.

Summary

As for me, any discussion on AI has been and will be focused on using and adopting appropriate technologies enabling Human Performance, by all means (Quality, Productivity, Consistency and Safety) cutting down unwanted time and processes through automation. It is therefore AI – Artificial Intelligence as an Alternative Intelligence in Manufacturing was and will always be in parallel development alongside technological improvements. Adaptation and Adoption, then, now and hereafter, will be dependent on Organizational & Market Readiness – driven by ROI (Return on Investment) and Pay Back Periods.

However, moving forward, Demography induced challenges will hasten AI adoption as a
replacement for Human Resources in mundane, repeated, hard labour processes. This is
irrespective of Industrial Segments. Its more a watch to wait than wait and watch!.

AI in Manufacturing is not new – it has been and will always be there, not as a substitute for Humans but as a necessary intervention to Leverage Human Performance.

About the Author :

Dr. NITHYANANDAN DEVARAAJ (NITHIN) BE., MBA., Ph.D
Independent Board Member, Business Excellence Expert, Technical Due Diligence & Capability Assessor.
Managing Partner – SAAE Enterprises
President – Coimbatore Management Association
Past National Secretary – The Institute of Indian Foundrymen.
Former MD / CEO of a German & Japanese MNC
Chairman – Shri Avinashiappar Trust
Past Managing Director & CEO – Flow Link Systems (P) Ltd ( a Voith Group Company )

Dr. Nithin has about 35 + Years of Experience in Engineering Manufacturing organizations. He has worked for LMW Group, L&T, Hitachi & CRI Group. He is considered to be a Professional with a rare blend of Intrapreneurial Orientation, having been a Business Head across Engineering Manufacturing Organisations / Industries.

Dr. Nithin is an Intrapreneur with hands on experience establishing medium & large scale end to end Value Chain Manufacturing Organizations (from Castings to Finished Products) for Indian Corporates and MNCs, driving Growth & Profitability by Building, Sustaining and Growing High Performance Teams.

Dr. Nithin is a Member in Governing Council / Board Of Studies of Universities and Management Institutions as a Management Expert.

Dr. Nithin is part of various industrial associations and professional bodies; he is credited with playing a leading role in bringing land mark changes in Export Incentives, Classification of MSMEs, CPCB Norms, Waste & Disposal Management. He also plays a pivotal role in training and development of educated Youth seeking employment opportunities.

Dr. Nithin Leads a team that turned around a division and a Company, and in establishing large scale projects as bench marks in industry (This Business has won several awards at National & Regional Level which includes – Indian Foundry of the Year, Young Foundryman and Foundryman Awards, 4Star Award from CII, Green Award & Safety Award from Tamil Nadu Government & at National Level from IIF, First Indian Foundry in the segment to get OHSAS 18001 & ISO 50001 Certification and Many Kaizen awards.)

Dr. Nithin is a Managing Trustee of a Family Managed Trust involved in activities like rendering Food, Shelter, Education and Medicare. Noted for rendering services during Chennai, Kerala, Tanjore & Nilgiris Floods.

Dr. Nithin’s Academics:

• Ph.D in Management Sciences
• MBA in Finance & Marketing – Gold Medalist and University Topper
• BE Mechanical Engineer with Distinction
• An IRCA certified lead auditor and assessor for ISO 9001.
• A qualified auditor for EMS, OHSAS & EnMS
• L&T Future Leaders Training at IIM – C

Dr. Nithin’s Professional Associations:

• Member & Industry Nominee, Coimbatore Disaster Management Council
• A Guest Faculty to Premier Management Institutes & Was  Visiting Faculty to IIM – Calicut
• An examiner for Management Qualifications & Assessor for Management Teachers
• An acknowledged management trainer and consultant
• Is a regular Business Column Writer.

Dr. Nithin is a Member of:

• Foundry Development Council, Ministry of Commerce & Industries, India.
• Institution of Engineers, All India and Coimbatore Management Association
• Board of Studies in Universities & Premier Management Institutes

Dr. Nithin is Winner of:

• The Outstanding Alumni & Distinguished Alumni Awards from PSG Institutions & Bharathiar University.
• The CMA Golden Jubilee Year Best Manager award for the region.
• The Best Management Student award and many accolades at National Level.
• The Mother Teresa Award of Excellence for Young Business Managers.

Dr. Nithin’s Management Interests:

• Management of Innovation, Corporate Strategic Planning and Manufacturing Management, Green Supply Chain

Dr. Nithin can be contacted at :

Mobile : +91 94879 46900 , +91 99653 11288

LinkedIn | Twitter | Facebook | E-mail | E-mail2

Also read Dr. NITHYANANDAN DEVARAAJ’s earlier articles:

The post MANUFACTURING & AI – A SYNERGY appeared first on Industry4o.com.

The fastest way to make vision inspection work is to stop treating it like an AI feature—and start treating it like production infrastructure.

I’ve witnessed this scenario too many times: the model looks great—then the station collapses in week one. Not because the AI is “bad,” but because the real culprits are upstream and downstream: lighting drift, sloppy fixturing, rushed changeovers, brittle PLC handshakes, and workflows no one trusts.

Factories don’t care about demo accuracy. They care whether inspection survives production reality — shift after shift, line after line. In manufacturing, visual inspection isn’t a software project. It’s a production system.

And that distinction matters more than ever.

The industry has spent years optimizing defect detection accuracy. But factories don’t run on model accuracy alone — they run on reliability, integration, repeatability, maintainability, and operator trust.

A vision AI model that works in a controlled demo but fails during changeovers is not an AI success story — it’s a production liability.

The Real Challenge Is Not Detection — It Is Production Stability

Most quality teams have lived both extremes:

Deep learning helps—but it doesn’t remove the factory constraints: vibration, partvariation, surface glare, tight takt time, frequent changeovers, and the non-negotiable requirement to integrate with controls.

Here’s how I think about it: visual inspection is a stack, and software is only one layer.

The Visual Inspection Stack (Beyond Software)

A production-grade inspection system typically depends on multiple interconnected layers:

Operations & Governance : Ownership, escalation paths, operator trust, and change management

Integration : PLC/MES/QMS connectivity, traceability, reject/rework loops, alarms

Deployment & Reliability : SAT readiness, uptime, calibration procedures, maintenance playbooks

Model & Decision Logic : Classification logic, thresholds, defect taxonomy

Data : Sampling strategies, labelling quality, edge-case handling, drift monitoring

Compute & Cameras : Edge hardware, triggering systems, timing synchronization, enclosures

Lighting, Optics & Mechanics : Illumination geometry, lensing, fixturing, motion control

A simple rule often applies: if the foundational layers are unstable, software alone cannot compensate for upstream variability.

This is where many AI vision deployments encounter difficulties—not because the model fails, but because production environments are inherently dynamic.

Production Does Not Care About the Demo

On the shop floor, the expectations are straightforward:

• pass SAT
• sustain uptime
• survive changeovers
• avoid becoming a new operational bottleneck

If an inspection station cannot be trusted consistently across shifts, even high-performing models lose practical value. It won’t matter what your ROC curve looked like during evaluation.

Scaling inspection therefore requires more than deploying AI models. It requires deployment discipline: standardized mechanical design, calibration routines, acceptance criteria, maintenance workflows, integration logic, and operational governance.

Without that foundation, every deployment risks becoming a custom engineering exercise.

At scale, inspection systems stop being isolated AI projects and start becoming manufacturing infrastructure.  

Detection Is Cheap. Action Is the Product.

The value of inspection is realized only when manufacturing systems can act on the result reliably.

Inspection-to-Action Flow

Detection alone has limited value if it cannot drive reliable manufacturing action.

The real operational layer is everything that happens after inference: PLC handshakes, reject/rework logic, alarms, traceability, and reporting into MES/QMS, operator visibility, and process accountability.

And it has to be legible—defect categories must align with the control plan, evidence images must be understandable to operators, and metrics must drive action – not endless arguments between production and quality teams.

At scale, inspection systems are not evaluated only by model accuracy. They are evaluated by whether production teams trust them enough to run continuously.

Rethinking AI Inspection as Manufacturing Infrastructure

As AI adoption expands across manufacturing, the conversation is gradually shifting.

The question is no longer only: “Can AI detect defects?”

Increasingly, the more important question is: “Can the inspection system remain stable, maintainable, and operationally useful under real production conditions?”

That changes the way inspection systems need to be designed.

Experience from large-scale manufacturing deployments continues to reinforce the same lesson: successful inspection systems are rarely the result of models alone.

They depend on how imaging, mechanics, AI, deployment reliability, integration, traceability, and production workflows work together as a complete operational system.

At Jidoka Technologies, this perspective has been shaped through deployments across 180+ manufacturing lines and more than 300 million inspections per day across production environments.

Because ultimately, the objective is not only defect detection. It is enabling production environments to respond consistently, reliably, and at scale.

About Author :

Mr. Sekar Udayamurthy
Founder & CEO,
Jidoka Technologies Pvt. Ltd.

Mr. Sekar Udayamurthy is the Founder and CEO of Jidoka Technologies, leading the integration of Artificial Intelligence, Machine Vision, and automation to revolutionize defect detection in manufacturing.

Mr. Sekar Udayamurthy works on deploying AI-powered visual inspection systems across manufacturing environments.

Mr. Sekar Udayamurthy’s work focuses on production-grade AI deployment, operational reliability, manufacturing integration, and scalable inspection infrastructure for Industry 4.0 applications.

Previously Mr. Sekar Udayamurthy contributed to large-scale digital engineering and application modernization initiatives as SBU Head at Cognizant, managing multimillion-dollar portfolios and cloud-native platform development.

Mr. Sekar Udayamurthy is passionate about technology, architecture, and fostering high-performance teams, consistently delivering impactful tech solutions aligned with strategic objectives.

Mr. Sekar Udayamurthy  is Bestowed with the following Licenses & Certifications :

https://www.linkedin.com/in/sekarudayamurthy/details/certifications/

Mr. Sekar Udayamurthy  is Bestowed with the following Patents :

https://www.linkedin.com/in/sekarudayamurthy/details/patents/

Mr. Sekar Udayamurthy can be contacted at :

E-mail | LinkedIn | Website

About JIDOKA Technologies Pvt.Ltd :

Jidoka Technologies is an industrial automation leader specializing in “First-Time-Right” manufacturing through Vision AI solutions. Rooted in the Lean manufacturing principle of Jidoka (automation with a human touch), the company eliminates the traditional trade-off between production speed and quality. By combining deep learning with modular hardware, Jidoka enables factories to achieve near-perfect accuracy at extremely high throughputs.

Core Product Offerings :

Jidoka uniquely delivers product inspection(2D & 3D) and process guidance on a single platform:

KOMPASS (Product Inspection)

Unlike traditional rule-based vision systems, KOMPASS uses deep learning to detect micro-defects, anomalies, and non-conformances in real-time. It handles counting, sorting, classification, and label verification at speeds up to 12,000 parts per minute.

NAGARE (Process Guidance)

NAGARE focuses on process integrity through real-time digital verification of assembly steps. This “poka-yoke” (error-proofing) approach guides operators to prevent errors before they become defects, reducing rework by up to 35% and boosting productivity by 25%.

Industry Impact

Jidoka serves diverse sectors including Automotive, FMCG, Pharma, Electronics, and Logistics

Automotive:

The “HILDA” (Human-In-The-Loop) approach inspects cylinder blocks, processing over 1,000 images in 70 seconds and saving thousands of man-hours

FMCG & Logistics:

High-speed packaging line inspection ensures label accuracy and kit completeness, preventing costly recalls

General Manufacturing :

Hardware-agnostic AI integrates seamlessly with existing systems (Siemens, Omron), providing scalable quality control digitization

To Learn more about Jidoka Technologies Pvt. Ltd.:

Jidoka Technologies | AI Vision Inspection Solutions | Customer Stories 

Jidoka Technologies can be contacted at:

E-Mail (1) | E-mail (2) | LinkdedIn | Website | X

The post Visual Inspection in Manufacturing appeared first on Industry4o.com.

On a warm Friday afternoon in July of 1969, a young bank teller named Theodore John Conrad finished his shift at Society National Bank in Cleveland, picked up a plain paper bag, and walked out as if he were heading home like any other day. Inside that bag sat $215,000 in cash, the kind of money that would make most people hesitate before taking a single step. Conrad didn’t rush. He didn’t look over his shoulder. He simply blended into the ordinary movement of the city and kept going, leaving behind a puzzle that would stretch across more than fifty years.

What keeps his story alive is the quiet way he carried it out. Conrad had no criminal background and no dramatic explanation waiting in a notebook somewhere. People who knew him described a calm young man who never hinted at anything unusual. Investigators tried to follow the few clues they had, but the trail cooled almost immediately. Every lead seemed to dissolve into another dead end, and the case slowly turned into something closer to folklore than an active search.

When the truth finally surfaced, long after Conrad had built a new life under a different name, it arrived through something as ordinary as an obituary. A few small details, the kind that most readers would skim past without a second thought, were enough to unravel the secret he had carried for decades. It is strange how a life can hinge on something so small.

His story offers a surprisingly useful way to think about the idea of actionable data in data storytelling. Conrad’s escape shows how information can hide in plain sight, how scattered clues can sit untouched for years, and how meaning often depends on someone noticing the right detail at the right moment. Actionable data works in a similar way. It is less about the volume of information and more about the insight that actually prompts someone to move. Conrad’s story gives us a vivid backdrop for exploring that idea.

1. The Unseen Insights

When investigators first tried to understand how Conrad slipped away so easily, they kept circling back to the same problem. The clues they needed were sitting in front of them, yet none of those clues pointed anywhere useful. The bank’s security procedures were loose, and the daily routines were predictable. Conrad had studied those routines for months. He knew which details mattered and which ones everyone else ignored. That quiet awareness gave him an advantage that no one recognized until it was too late.

Actionable data works in a similar way. Organizations often collect enormous amounts of information, but the pieces that truly matter are rarely the loudest ones. They tend to be the small patterns that hide inside the noise. A sudden shift in customer behavior, a subtle change in how people navigate a website, or a quiet trend in operational delays can reveal more than a hundred charts filled with surface‑level metrics. The challenge is learning to notice what others overlook. Conrad’s story reminds us that the most valuable insights are often the ones that sit quietly in the background.

There is also something to be said about the patience required to find meaning in those quieter signals. Conrad didn’t rush his plan. He watched, waited, and learned how the system around him behaved. Data storytellers face a similar task. The first glance at a dataset rarely tells the whole story. It takes time to understand what the information is trying to say. When you slow down enough to see the patterns that hide beneath the obvious ones, the insights become far more powerful. They become the kind of insights that change decisions rather than decorate presentations.

2. The Two‑Day Head Start

One of the most striking parts of Conrad’s escape was the timing. He chose a Friday afternoon, knowing the bank would not reconcile its cash until Monday morning. That gave him nearly two full days before anyone realized the money was gone. By the time the alarm was raised, he was already far beyond the reach of the first wave of investigators. Timing didn’t just help him. It shaped the entire outcome.

In data storytelling, timing plays a similar role. An insight that arrives too late loses its value. A trend that goes unnoticed for a week can turn into a missed opportunity. A risk that sits unaddressed for a month can grow into a crisis. The speed at which organizations act on their data often determines whether they stay ahead of a problem or chase it from behind. Conrad’s head start illustrates how quickly the window for meaningful action can close.

There is also a lesson here about the rhythm of decision‑making. Some organizations treat data as something to review only at scheduled intervals. They wait for the end of the quarter or the next leadership meeting. By then, the moment has already passed. Actionable data requires a different mindset. It calls for a willingness to respond when the signal appears, even if the timing is inconvenient. Conrad understood the power of timing instinctively. Data storytellers can learn from that instinct by recognizing that the right insight delivered at the right moment can change the entire trajectory of a decision.

3. The Elusive Trail

When investigators searched for Conrad, they kept running into the same problem. There was almost nothing to work with. He had never been fingerprinted. He left behind no dramatic note or confession. There were no security cameras to review. The absence of information became its own kind of obstacle. Every time they tried to follow the trail, they found another empty space where a clue should have been.

In the world of data, those empty spaces matter. Missing information can reveal just as much as the data that is present. A sudden gap in customer activity might signal frustration. A missing field in a form might point to confusion. A drop in engagement might reflect a change in expectations. Data storytellers often focus on what they can measure, but the things they cannot measure sometimes carry the most meaning. Conrad’s trail teaches us that silence can be a signal of its own.

There is also a deeper challenge here. When information is incomplete, it becomes tempting to fill the gaps with assumptions. Investigators did this repeatedly. They guessed where Conrad might have gone. They imagined what he might have done. Those guesses led them in circles for years. Data storytellers face the same temptation. When the data is thin, it is easy to lean on intuition instead of evidence. The better approach is to acknowledge the gaps openly and explore what those gaps might imply. Sometimes the absence of data is the very thing that points toward the truth.

4. The Obituary Clue

The detail that finally revealed Conrad’s identity came from an unexpected place. His obituary mentioned a few small facts that matched the old case file. Those details were ordinary on their own, but together they formed a pattern that someone finally recognized. After decades of searching, the answer arrived through a source no one had considered important.

This is a familiar experience for anyone who works with data. Insights often come from places that seem unrelated at first glance. A customer support transcript might explain a sudden drop in sales. A maintenance log might reveal the cause of a recurring delay. A forgotten spreadsheet might hold the key to understanding a trend that has puzzled analysts for months. Actionable data rarely comes from a single source. It emerges when different pieces of information are brought together in a way that reveals something new.

There is also a lesson here about curiosity. The investigator who solved the case did so because he noticed something that others had overlooked. He allowed himself to follow a thread that seemed small. Data storytellers thrive when they approach information with that same sense of curiosity. The most meaningful insights often begin with a simple question. Why did this happen? Why does this number look different from last month? Why does this pattern appear only in certain situations? When you follow those questions with patience, the story inside the data begins to reveal itself.

Conclusion

Theodore John Conrad’s escape lasted more than fifty years, yet the heart of his story comes down to a handful of small details. A quiet observation about how the bank operated. A choice about timing. A trail defined as much by what was missing as by what was present. A final clue tucked inside an obituary. None of these pieces seemed dramatic on their own, but together they shaped one of the most unusual manhunts in American history.

Actionable data works the same way. It rarely announces itself with fanfare. It hides inside ordinary patterns, scattered clues, and overlooked signals. The value comes from noticing what others miss and understanding how those pieces fit together. When data storytellers approach information with that mindset, the insights they uncover become far more powerful. They become the kind of insights that guide decisions, reveal opportunities, and change outcomes.

Conrad’s story is a reminder that information has a life of its own. It moves quietly. It waits to be noticed. It rewards the people who pay attention. In a world overflowing with data, the real advantage belongs to those who can find the meaning inside the noise and turn it into something that moves people to act.

“Bringing Data to Life and Life to Data”

About the Author:

Dr. Joe Perez,
Team Lead / Senior Systems Specialist,
NC Department of Health and Human Services

Dr. Joe Perez ( Dr.Joe ) is also the Chief Technology Officer – CogniMind

To book Dr. Joe Perez for your speaking engagement please click here

Dr. Joe Perez was selected as the 2023 Gartner Peer Community Ambassador of the Year.

Dr. Joe Perez is a truly exceptional professional who has left an indelible mark on the IT, health and human services, and higher education sectors. Dr. Joe Perez journey began in the field of education, where he laid the foundation for his career. With advanced degrees in education and a doctorate that included a double minor in computers and theology, Dr. Joe Perez embarked on a path that ultimately led him to the dynamic world of data-driven Information Technology.

In the early 1990s, Dr. Joe Perez transitioned into IT, starting as a Computer Consultant at NC State University. Over the years, Dr. Joe Perez’s dedication and expertise led to a series of well- deserved promotions, culminating in his role as Business Intelligence Specialist that capped his 25 successful years at NC State. Not one to rest on his laurels, Dr. Joe Perez embarked on a new challenge in the fall of 2017, when he was recruited to take on the role of Senior Business Analyst at the NC Department of Health, Human Services (NCDHHS). His impressive journey continued with promotions to Senior Systems Specialist and Team Leader, showcasing his versatility and leadership capabilities.

In addition to his full-time responsibilities at NCDHHS, Dr. Joe Perez assumed the role of
fractional Chief Technology Officer at a North Carolina firm in October 2020. An Amazon best-selling author with over 21,000 followers on LinkedIn and numerous professional certifications, he is a highly sought-after international keynote speaker and recognized expert in data analytics and visualization.

Dr. Joe Perez’s contributions have not gone unnoticed. Dr. Joe Perez is a recipient of the IOT Industry Insights 2021 Thought Leader of the Year award, the 2023 Gartner Peer Community Ambassador of the Year award, and Top Ten Global Thought Leader for several categories at Thinkers360 in four consecutive years (2023-2026). Dr. Joe Perez holds memberships in several prestigious Thought Leader communities, and was recently inducted into the United Nations Global Network of Data Officers and Statisticians. Dr. Joe Perez’s reach extends to more than twenty countries worldwide, where he impacts thousands through his speaking engagements, articles, and status as a Distinguished Fellow in the Public Sector Network’s Future Government Institute.

Beyond his professional achievements, Dr. Joe Perez’s passion for teaching remains
undiminished. Whether as a speaker, workshop facilitator, podcast guest, conference emcee, or team leader, he continually inspires individuals to strive for excellence. He treasures his time with his family and is a gifted musician, singer, pianist, and composer. Joe also dedicates his skills through involvement in his church’s Hispanic ministry. Dr. Joe Perez manages the publication of a widely recognized monthly military newsletter, The Patriot News, and is deeply committed to his community.

To maintain a balanced life, Dr. Joe Perez is a regular at the gym, and he finds relaxation in watching Star Trek reruns. He lives by the philosophy that innovation is the key to progress, and he approaches each day with boundless energy and an unwavering commitment to excellence. Dr. Joe Perez’s journey is a testament to the remarkable achievements of a truly exceptional individual, and more importantly, to the amazing grace of God.

Dr. Joe Perez is Accorded with the following Honors & Awards :

https://www.linkedin.com/in/jwperez/details/honors/

Dr. Joe Perez is Bestowed with the following Licences, Certifications & Badge:

https://www.linkedin.com/in/jwperez/details/certifications/

https://www.thinkers360.com/tl/badge/19985/2764

Dr.Joe Perez is Voluentering in the following International Industry Associations & Institutions :

https://www.linkedin.com/in/jwperez/details/volunteering-experiences/

Dr.Joe Perez can be contacted at :

E-mail | LinkedIn | Web | Sessionize | FaceBook  | Twitter | YouTube

Also read Dr.Joe Perez‘s earlier articles:

The post DATA STORY appeared first on Industry4o.com.

Thanks to the Organizations i was with, was amongst the earliest Adopters of ISO as a Management System. Despite being long associated, i always wonder about the task & tussle in adherence to the Systems, let alone the visible benefits the Organization reaps from having an ISO Certified Management System. Many a times, i have noticed that Management Systems survive in isolation even with the supposedly strong commitment by the Top Management.

At shop level, People to a considerable extent, have found ISO Management Systems more an interruption than a savior. Due to which, in Majority of the Organizations ISO remains a fad than a realistic Management Tool. Having certified for ISO is widely believed to have its advantages – from Market and Customer perspective, as a Tool to Attract and sometimes, a Tool to Retain.

Personally and Professionally, I have always believed, and ofcourse demonstrated as well, that any System adopted with conviction by the Top Management and promulgated all across the Organization brings in highly desirable results, consistently. Key is the holistic absorption as part of DRMs, and certainly not in parallel. Success of any Management Tool in an Organization, I strongly attribute to Top Down Approach.

The Genesis:

India emerging as a Manufacturing Hub and a Bankable Market necessitated a common platform for people to assess capability and capacity of Organizations for collaborative working, Branding apart. Any Good Organization Run Professionally certainly had documented system for their own Monitoring, Control and Management, even prior to introduction of ISO. It was easier for such Organizations to quickly convert to ISO Systems and Procedures. What started as a Privileged

Tool, over the Years ISO became a common platform, facilitated by proliferation of Certifying Bodies. From Manufacturing, ISO as a Standard, moved across Industries including Educational Institutions. More than a Quality Management System, ISO is now considered to be an Effective Organization Management System, beyond that of Process Management.

Transitions:

Certain industries looked at ISO quite critically, identified certain insufficiencies as a common tool. Starting with Automotive Sector, every Sector aspired to bring in more stringent requirements specific to their sectors in the name of User Protection and Safety. Those remain specific due to both Cost and Convenience of universalization across Industries.

Over the years, evolution of consumer aspirations and consumer protection movement called for further strengthening of ISO. As an Organization, ISO picked up the good and practicable necessities from those of Industry Specific standards. Periodical Changes were made in Standards and imposed through various clauses. From mundane paper work, ISO became an Operational Tool and in the process, evolved from being a Reactive to a Proactive Tool.

Evolutions:

As an Intrapreneur, I have always enforced an Integrated Working, focused on Effectiveness beyond Efficiencies. Silos are certainly needed to bring focus and efficiency, without which may result in Organizational disarray – meaning fixing of Responsibility & Accountability.

In more than a decade that passed, impact of Businesses on the Stake Holders necessitated a System beyond that of Organization. ISO recognized this need and included as part of the standards calling for ESG Focus and Risk Mitigation, both for the benefit of the Organization and the Stake Holders. As we move into the future, the changes envisaged alongside AI evolution leaves no choice but for the ISO and its Constituent Organizations to be prepared for.

As a result, expect ISO to move ahead of Monitor and Control to that of Leadership and Performance. Built on the fundamental framework Resilience, Sustainability, Digitalization and Value Creation, Culture Building and Business Process Transformation will be the salient aspects. ISO may thus becomes a Strategic Tool, whether it provides a Long Run Sustainable Unique Advantage or not.

Remarks:

ESG induced 3P (People – Planet – Profits) approach has forced upon Businesses to demonstrate Sustainability by way of Consistent Performance. While it is a choice now until the new ISO standard becomes effective, it will be more a compulsion to retain the Certification.

People, Processes & Systems should synergize for Organizational Effectiveness. Success of any Tool will continue to remain People Determined. In my experience, though the Auditors and Assessors play a key role in successful implementation at a Client, Tools have always been beneficial to the Organization, even if there are No Sayers.

It is a debate for another time – whether ISO assures success and helps to improve Profitability. Such a question arises with very many ISO Certified Organizations unable to sustain Businesses, resulting in Closures. But one thing is for sure – if ISO is adopted whole heartedly, it will atleast help us to be prepared at appropriate time and take course corrections. Its worth the investment – interms of Time, Money and Efforts.

About the Author :

Dr. NITHYANANDAN DEVARAAJ (NITHIN) BE., MBA., Ph.D
Independent Board Member, Business Excellence Expert, Technical Due Diligence & Capability Assessor.
Managing Partner – SAAE Enterprises
President – Coimbatore Management Association
Past National Secretary – The Institute of Indian Foundrymen.
Former MD / CEO of a German & Japanese MNC
Chairman – Shri Avinashiappar Trust
Past Managing Director & CEO – Flow Link Systems (P) Ltd ( a Voith Group Company )

Dr. Nithin has about 35 + Years of Experience in Engineering Manufacturing organizations. He has worked for LMW Group, L&T, Hitachi & CRI Group. He is considered to be a Professional with a rare blend of Intrapreneurial Orientation, having been a Business Head across Engineering Manufacturing Organisations / Industries.

Dr. Nithin is an Intrapreneur with hands on experience establishing medium & large scale end to end Value Chain Manufacturing Organizations (from Castings to Finished Products) for Indian Corporates and MNCs, driving Growth & Profitability by Building, Sustaining and Growing High Performance Teams.

Dr. Nithin is a Member in Governing Council / Board Of Studies of Universities and Management Institutions as a Management Expert.

Dr. Nithin is part of various industrial associations and professional bodies; he is credited with playing a leading role in bringing land mark changes in Export Incentives, Classification of MSMEs, CPCB Norms, Waste & Disposal Management. He also plays a pivotal role in training and development of educated Youth seeking employment opportunities.

Dr. Nithin Leads a team that turned around a division and a Company, and in establishing large scale projects as bench marks in industry (This Business has won several awards at National & Regional Level which includes – Indian Foundry of the Year, Young Foundryman and Foundryman Awards, 4Star Award from CII, Green Award & Safety Award from Tamil Nadu Government & at National Level from IIF, First Indian Foundry in the segment to get OHSAS 18001 & ISO 50001 Certification and Many Kaizen awards.)

Dr. Nithin is a Managing Trustee of a Family Managed Trust involved in activities like rendering Food, Shelter, Education and Medicare. Noted for rendering services during Chennai, Kerala, Tanjore & Nilgiris Floods.

Dr. Nithin’s Academics:

• Ph.D in Management Sciences
• MBA in Finance & Marketing – Gold Medalist and University Topper
• BE Mechanical Engineer with Distinction
• An IRCA certified lead auditor and assessor for ISO 9001.
• A qualified auditor for EMS, OHSAS & EnMS
• L&T Future Leaders Training at IIM – C

Dr. Nithin’s Professional Associations:

• Member & Industry Nominee, Coimbatore Disaster Management Council
• A Guest Faculty to Premier Management Institutes & Was  Visiting Faculty to IIM – Calicut
• An examiner for Management Qualifications & Assessor for Management Teachers
• An acknowledged management trainer and consultant
• Is a regular Business Column Writer.

Dr. Nithin is a Member of:

• Foundry Development Council, Ministry of Commerce & Industries, India.
• Institution of Engineers, All India and Coimbatore Management Association
• Board of Studies in Universities & Premier Management Institutes

Dr. Nithin is Winner of:

• The Outstanding Alumni & Distinguished Alumni Awards from PSG Institutions & Bharathiar University.
• The CMA Golden Jubilee Year Best Manager award for the region.
• The Best Management Student award and many accolades at National Level.
• The Mother Teresa Award of Excellence for Young Business Managers.

Dr. Nithin’s Management Interests:

• Management of Innovation, Corporate Strategic Planning and Manufacturing Management, Green Supply Chain

Dr. Nithin can be contacted at :

Mobile : +91 94879 46900 , +91 99653 11288

LinkedIn | Twitter | Facebook | E-mail | E-mail2

Also read Dr. NITHYANANDAN DEVARAAJ’s earlier articles:

The post Future Forward with ISO 9001: 2026 appeared first on Industry4o.com.

Risky Decisions? So What if You Could Test Them First?

So what?

Because the most expensive failures in manufacturing today are not machine
breakdowns, they are decisions executed without understanding their full-system impact.

Every layout change, capacity ramp, or bottleneck “fix” carries hidden risk. The cost of
getting it wrong is measured not just in CapEx, but in lost throughput, missed deliveries,
and credibility erosion.

Digital twins change the equation by giving leaders something manufacturing has rarely
had:

A risk-free environment to test decisions before committing capital.

The mandate: eliminate guesswork, maximize confidence
Traditional manufacturing decisions are often made using:

• Historical data
• Experience and intuition
• Limited pilots on live production

This approach is inherently risky. Once a change is made on the shop floor, reversing it
is slow, costly, and disruptive.
Digital twin enabled decision-making flips this model:

• Decisions are tested virtually, not physically
• Scenarios are explored before execution
• Confidence replaces optimism

In simple terms:

• Traditional approach → “Let’s try and see.”
• Digital twin approach → “Let’s simulate and choose.”

That difference alone is worth millions.

What changed: digital twins are no longer offline simulations

Simulation is not new.

What’s new is real-time, bidirectional intelligence.

Earlier generations of models were static and engineering-owned. Today’s digital twins
are:

• Continuously synchronized with live shop-floor dat
• Integrated with MES, planning, and equipment health
• Enhanced by AI and predictive logic
• Actively used by operations and leadership

They don’t just represent the factory.

They behave like it.

This evolution transforms digital twins from analytical tools into decision engines,
capable of answering:

“If we do this tomorrow, what happens next week?”

They don’t just represent the factory.
They behave like it.
This evolution transforms digital twins from analytical tools into decision engines,
capable of answering:
“If we do this tomorrow, what happens next week?”

Why decision testing matters more than optimization

Optimization improves existing performance.
Decision testing prevents avoidable mistakes.
In complex factories, changes rarely behave in isolation:

• A layout change improves flow, but shifts congestion downstream
• A bottleneck fix increases speed, but exposes upstream variability
• A capacity ramp meets demand, but destabilizes quality

Digital twins reveal second- and third-order effects before they become operational
problems.

This is where most traditional decision-making fails, not in intent, but in visibility.

Decisions that should always be tested in a digital twin

From real-world manufacturing transformations, some decisions are simply too risky to
execute blindly.

1. Factory layout changes

Physical layout changes are capital-intensive and hard to reverse.

A digital twin allows teams to:

• Simulate throughput before moving equipment
• Identify hidden bottlenecks
• Test material flow under peak demand

Many “failed” layouts weren’t bad ideas, they ignored system interactions.

2. Bottleneck fixes

Bottlenecks are rarely where teams think they are

Digital twins help test:

• Multiple solution options (add equipment vs re-sequence vs buffer)
• True impact on OEE and flow
• Whether investment or process change delivers better ROI

This prevents over-investing in the wrong constraint.

3. Capacity ramp-ups

Spreadsheets assume perfect behavior. Factories never deliver it.

Before spending, leaders can test:

• Labor and skill constraints
• Maintenance load and downtime risk
• Yield and quality stability during ramp

Capacity decisions move from hope-based to evidence-based.

4. New product introduction (NPI)

NPI failures are expensive and reputation-damaging.

Digital twins allow:

• Virtual process validation
• Parameter optimization before physical trials
• Faster stabilization of yield and throughput

Time-to-market improves without gambling on live production.

The ROI is no longer theoretical

Organizations deploying digital twins at decision-critical points consistently report:

• Significant reduction in decision-related risk
• Faster introduction of new processes and products
• Better CapEx utilization
• Improved OEE through proactive bottleneck management
• Greater agility during demand or supply disruptions

The biggest benefit is not a single KPI,

it’s decision confidence at scale.

Why many digital twin initiatives still disappoint

The technology is rarely the issue.

Most failures happen when:

• Twins are built without a clear decision owner
• Models are too complex to trust operationally
• Data exists, but context is missing
• Operations teams are observers, not users

Successful implementations start with one question:

“Which decision do we want to make better?”

Everything else is built backward from that.

The real shift: leadership behavior

The hardest change is not building the twin.

It’s trusting it.

Leaders who succeed:

• Encourage teams to test assumptions
• Compare scenarios instead of opinions
• Use the twin continuously, not only during crises
• Treat it as a learning system, not a one-time project

Over time, the digital twin becomes part of how the factory thinks.

Bottom line

Every manufacturing decision carries cost, some visible, many hidden.

Digital twins offer one decisive advantage:

Make mistakes virtually, not physically.

Testing decisions in a virtual factory before spending a rupee is no longer a technology
choice.

It is a leadership discipline

About the Author :

Mr. Gulshan Kumar Saini
Senior Director
Samsung Electronics

Mr. Gulshan Kumar Saini is a manufacturing transformation leader, experienced in scaling plants across India, Korea, USA/Mexico, Russia & Vietnam.

Mr. Gulshan Kumar Saini is a global manufacturing, operations excellence, and smart factory transformation leader with over 30 years of leadership experience at Samsung Electronics, spanning senior roles across India, Vietnam, Korea, Russia, and the United States.

Mr. Gulshan Kumar Saini currently serves as Senior Director – Smart Factory at Samsung Electronics India, where Mr. Gulshan Kumar Saini spearheads enterprise-wide digital transformation initiatives across advanced manufacturing lines for consumer electronics and durables.

Mr. Gulshan Kumar Saini leads the deployment of AI-driven manufacturing systems, industrial robotics, IIoT platforms, machine vision, advanced analytics, and Digital Twin technologies to drive next-generation factory performance.

Mr. Gulshan Kumar Saini is widely recognized for delivering large-scale automation, step- change productivity improvements, and sustainable cost, quality, and efficiency gains in high-volume, high-complexity manufacturing environments. Across his career, Mr. Gulshan Kumar Saini has successfully led global NPI programs, greenfield and brownfield plant setups, capacity expansions, lean transformations, and multi-country manufacturing excellence programs.

Mr. Gulshan Kumar Saini is a PMP-certified professional and Six Sigma Black Belt, Mr. Gulshan Kumar Saini also holds an MBA in FinTech from BITS Pilani, combining strong digital, financial, and operational acumen to translate technology into measurable business outcomes.

Mr. Gulshan Kumar Saini is Bestowed with the following Licenses & Certifications:

https://www.linkedin.com/in/gulshan-kumar-saini/details/certifications/

Mr. Gulshan Kumar Saini is Accorded with the following Honors & Awards:

https://www.linkedin.com/in/gulshan-kumar-saini/details/honors/

Mr. Gulshan Kumar Saini can be contacted at:

Linked In | E-mail (1) | E-mail (2)

Also read Mr. Gulshan Kumar Saini‘s earlier article:

The post Digital Twins for Test Decisions appeared first on Industry4o.com.

The post ELIYA – MASTERING SIMPLICITY appeared first on Industry4o.com.

What AI reveals about supply-chain risks, before they disrupt your factory

One Supplier Fails, Your Factory Stalls. 

So what?

You don’t have an “issue”, you have an existential risk that must be seen early, not fixed after the alarm.

AI Sees the Signals Humans Miss.

● What AI detects: Pattern-level anomalies across financial health, delivery cadence, quality trends, logistics delay signals, and 3rd-party events, days or weeks before an outage.
● How accurate: Proven models (ensemble ML, LSTM/time-series, graph analytics) provide high early-warning accuracy across heterogeneous supplier signals.
● Where it matters: Multi-signal sensing is especially powerful for single-source components (semiconductors, specialty chemicals, sub-assemblies) where substitutes are scarce.

So what?

AI gives you the Golden Window to act, to reroute, re-order, or execute contingency plans before the factory feels the pain.

Five-Step Early-Warning Pipeline (Data → Decision → Action)

So what?

It’s not an IT project, it’s a decision pipeline that turns signal into a timed business action.

Real evidence: AI catches disruptions before they cascade.

So what?

The ROI is practical ; fewer emergency buys, lower expedite fees, less downtime, and stronger customer delivery performance.

What leaders must do next (rapid checklist).

So what?

The firms that institutionalize AI-driven early warnings will shrink the window between supplier stress and factory impact , turning single-supplier risk from a panic into a managed event.

Closing Takeaway

This isn’t about adding another dashboard. It’s about turning supply-chain risk into a managed decision window.

The next disruption won’t announce itself.

The winners will be the factories that see it coming, and act before production feels it.

If one of your critical suppliers went silent today, would you know early enough to protect your factory?

About the Author :    

Mr. Gulshan Kumar Saini
Senior Director
Samsung Electronics

Mr. Gulshan Kumar Saini is a global manufacturing, operations excellence, and smart factory transformation leader with over 30 years of leadership experience at Samsung Electronics, spanning senior roles across India, Vietnam, Korea, Russia, and the United States.

Mr. Gulshan Kumar Saini currently serves as Senior Director – Smart Factory at Samsung Electronics India, where Mr. Gulshan Kumar Saini spearheads enterprise-wide digital transformation initiatives across advanced manufacturing lines for consumer electronics and durables.

Mr. Gulshan Kumar Saini leads the deployment of AI-driven manufacturing systems, industrial robotics, IIoT platforms, machine vision, advanced analytics, and Digital Twin technologies to drive next-generation factory performance.

Mr. Gulshan Kumar Saini is widely recognized for delivering large-scale automation, step- change productivity improvements, and sustainable cost, quality, and efficiency gains in high-volume, high-complexity manufacturing environments. Across his career, Mr. Gulshan Kumar Saini has successfully led global NPI programs, greenfield and brownfield plant setups, capacity expansions, lean transformations, and multi-country manufacturing excellence programs.

Mr. Gulshan Kumar Saini is a PMP-certified professional and Six Sigma Black Belt, Mr. Gulshan Kumar Saini also holds an MBA in FinTech from BITS Pilani, combining strong digital, financial, and operational acumen to translate technology into measurable business outcomes.

Mr. Gulshan Kumar Saini is Bestowed with the following Licenses & Certifications

https://www.linkedin.com/in/gulshan-kumar-saini/details/certifications/

Mr. Gulshan Kumar Saini is Accorded with the following Honors & Awards

https://www.linkedin.com/in/gulshan-kumar-saini/details/honors/

Mr. Gulshan Kumar Saini can be contacted at:

Linked In | E-mail (1) | E-mail (2)

#supplychainrisk #aiinsupplychain #smartmanufacturing #supplychainresilience #industrialai #supplierrisk #multitiersupplychain #manufacturingleadership #operationalrxcellence #futureofmanufacturing

Also read Mr. Gulshan Kumar Saini‘s earlier article:

The post AI in Supply Chain appeared first on Industry4o.com.

When Hackers Employ AI: Is It Time to Rethink our Security Defences?

The rapid expansion of artificial intelligence (AI) across industries has changed countless capabilities, delivering benefits in efficiency, automation, and innovation. However, the same technology has also become a powerful weapon in the hands of predators, essentially altering the landscape of digital threats and malicious activities. As cybercriminals leverage AI to craft more clever and obscure attacks, the level of data protection is questioned. Organisations must relook into their current security strategies to verify, redefine, enhance and remain fit for purpose.

Current Impact on Businesses: Key Metrics

As AI-powered cyber threats rise, businesses are experiencing tangible impacts. Here are some key metrics to illustrate the current landscape:

The Rise of AI-Powered Cyber Threats

Cybercriminals are increasingly leveraging artificial intelligence to enhance both the deception and efficiency of their data exploitation tactics. By implementing machine learning algorithms, these malicious actors can automate activities like credential theft, password cracking, vishing, smishing, and phishing on an unprecedented scale. AI not only accelerates the identification of vulnerabilities within an organization’s systems but also makes breaches and intrusions more challenging to detect and address promptly

Moreover, the emergence of generative AI has introduced new forms of deception, including highly personalised phishing emails and realistic fake content. These advancements empower cybercriminals to orchestrate multi-layered campaigns that adapt dynamically to security measures, leaving traditional defence mechanisms struggling to keep up. As the tools available to hackers become ever more advanced, the threat landscape continues to evolve at a rapid pace, demanding a fundamental rethinking of how we approach cyber security.

For instance, AI-driven deepfake technology has been utilized to produce highly realistic voice and video impersonations, which are exploited in social engineering attacks. Additionally, automated tools can swiftly scan extensive networks for vulnerabilities, outpacing human capabilities. Furthermore, AI-powered bots can execute coordinated attacks that dynamically adjust to the defences they encounter in real-time.

Risks on using Traditional Security models to manage AI Threats:

• Inability to detect unusual Threats: Traditional security models often rely on static signatures and predefined rules, making them ineffective against new and previously unseen AI-generated malware or attack techniques.

• Slow Response Times: Manual analysis and intervention are no match for the speed at which AI-powered attacks operate.

• Overwhelmed Resources: The sheer volume and complexity of AI-driven threats can quickly overwhelm traditional security teams and tools, resulting in missed alerts and insufficient coverage across networks and endpoints.

• Weakness in handling Social Engineering: Conventional defences are ill-equipped to recognise sophisticated social engineering tricks, such as deepfake-based phishing or voice impersonation, which can deceive even security-aware personnel.

• Limited Threat Intelligence Integration: Legacy tools often do not integrate with global threat intelligence platforms, missing out on real-time updates about emerging, AI-driven attack vectors.

• Reactive Rather Than Proactive Approaches: Traditional security models tend to respond to attacks after they occur, rather than predicting or preventing threats by analysing behavioural anomalies and unusual patterns.

• Lack of Automation: Without automation, traditional security operations centre (SOC) teams may become bogged down by repetitive tasks, unable to focus on strategizing against the most sophisticated threats.

Limitations of Traditional Security Tools

Traditional security solutions, such as signature-based antivirus software and static firewalls, were designed to detect known threats using predefined rules. While these tools are still essential for baseline protection, they struggle to keep pace with novel, AI-driven attacks that constantly evolve and mutate.

• Signature-based detection: Relies on known malware signatures, but AI attacks create new variants that evade detection.

• Rule-based firewalls: Static rules are easily bypassed by adaptive AI attack strategies.

• Manual monitoring: Human analysts struggle with the speed and scale of AI-driven threats.

In short, the dynamic and unpredictable nature of AI-powered threats exposes the limitations of conventional defences.

The Case for Next-Generation Cyber Security

To keep pace with AI-enabled hackers, organisations must augment their traditional defences with advanced, intelligent security solutions. These include:

• AI-driven threat detection: Security platforms that use machine learning and behavioural analytics to identify anomalies and suspicious activities, even those not seen before.

• Automated response systems: Tools that can respond to threats in real time, containing breaches and neutralising attacks without human intervention.

• Adaptive security frameworks: Solutions that continuously learn and update their defence mechanisms, staying one step ahead of evolving threats.

• Comprehensive threat intelligence: Integrating global threat data and predictive analytics to anticipate and block emerging attack patterns.

By embracing these next-generation tools, organisations can level the playing field against AI-enabled adversaries.While AI is crucial for modern cyber defence, it is not a silver bullet. Skilled security professionals are needed to interpret AI-generated insights, make strategic decisions, and respond to complex incidents.The integration of AI by hackers has significantly transformed the cybersecurity landscape and it’s time for the Organisations to reshape their existing cybersecurity posture to handle AI threats. By continuously evolving our defences, we can strive to stay ahead in this dynamic digital arms race.

About the Author :

Ms. Kavitha Srinivasulu
CCISO | DPO| DTO| CISA | CRISC | CISM | CGEIT | PCSM | IAPP AIGP | ISO42001: LA
Program Director: Cybersecurity & Data Privacy
Tata Consultancy Services

Ms. Kavitha Srinivasulu is an Award winning Technology Leader.

Ms. Kavitha Srinivasulu is a Senior Cyber Risk and Resilience executive with over 22 years of global leadership experience advising Boards and Executive Committees across Financial Services, Healthcare, Retail, Technology, and regulated industries.

Ms. Kavitha Srinivasulu has delivered and led large-scale, regulator-driven cybersecurity, AI driven, PCI, and SOC transformations for Tier-1 banks, global healthcare organisations, and highly regulated enterprises operating across the UK, EU, USA, APAC, and ANZ.

Ms. Kavitha Srinivasulu is a trusted advisor to Boards, C-suite, regulators, and global enterprises, consistently delivering resilient, compliant, and scalable cyber operating models.

Ms. Kavitha Srinivasulu is an Advisory Member in National Cyber Defence Research Centre (NCDRC)

Ms. Kavitha Srinivasulu is a Board Member of Women in CyberSecurity (WiCyS) India

Ms. Kavitha Srinivasulu is an Executive Committee Member at CyberEdBoard Community

Ms. Kavitha Srinivasulu is an ambassador at ISAC

Ms. Kavitha Srinivasulu is Bestowed with the following Licenses & Certifications :

https://www.linkedin.com/in/kavitha-srinivasulu-5619ab7/details/certifications/

https://www.linkedin.com/in/kavitha-srinivasulu-5619ab7/details/publications/

Ms. Kavitha Srinivasulu can be contacted at :

LinkedIn

Disclaimer :

“The views and opinions expressed by Ms. Kavitha Srinivasulu in this article are solely her own and do not represent the views of her company or her customers.”

Also read Ms. Kavitha’s earlier article:

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How do digital Live Permits transform “work orders” into a process that keeps pace with reality?

In many industrial plants, work permits still act as a “handbrake” for organizations: paper, signature circulation, scattered information, lack of up-to-date information, and limited visibility of what is actually happening on site. The problem is not just about convenience – it’s about safety, accountability, and the ability to respond quickly to changing working conditions.

Meanwhile, dangerous and critical work (e.g., hot work, work at height, work in hazardous areas, servicing during plant operation) does not happen according to an “ideal plan” — it happens in a dynamic, changing environment. This is why classic work orders often lose out to reality: they are not updated, they are not consistent with who is actually where, and they do not create a single version of the truth for health and safety, maintenance, and external companies.

Live Permits is an approach in which a work permit is not a document “for the archives,” but a living operational process — updated in real time, linked to the location and status of activities on site. This is how we build the system at InnerWeb®.

The challenge: safety vs. speed vs. complexity of operations

Before we move on to technology, it is worth identifying the sources of friction that almost always arise in work permit processes:

As a result, the organization chooses between two bad options: either the process is “tight” but slow and cumbersome, or fast but risky. Live Permits are designed to resolve this conflict — through automation, consistency, and timeliness, not by “letting go” of safety.

Where do Live Permits provide an operational advantage?

Below are the key areas where the “live” approach really changes the quality of the
process.

1. Digital permits as a common “point of truth”

The work permit becomes the central object of the process, rather than a form.

2) Real-time updates – a process that keeps pace with change

The biggest difference between an “e-permit” and Live Permit is that the permit is not static.

Example: if a new risk arises in the zone (e.g., parallel work, leak, parameter exceedance), the permit can be automatically switched to “suspended” mode until corrective actions are confirmed.

3) Location as a safety context (geofencing, zones, plan compliance)

At the heart of the InnerWeb® approach is the linking of work permits to the
actual workplace.

Implementation example: in one of the EU-funded pilot projects at the MAN Trucks
plant in Niepołomice, the process included monitoring work permits, training
requirements for external companies and visitors, along with familiarization with the
current risks when entering the plant, alongside the location of trucks and drivers
moving around the facility – using the dense infrastructure of InnerWeb® Industrial
Radio Beacons (over 200 BLE transmitters on the plant’s internal roads). This shows
that work permits can operate in the same “data language” as logistics and traffic
safety at the plant.

4) Competencies and authorizations – “who can” is verified automatically

Live Permits is not just a form – it is compliance logic.

Example : if current training and specific qualifications are required for hot work, the
system can block the start of work without meeting the conditions.

5) Particularly hazardous work : standards, LOTO, and condition control

For high-risk areas, repeatability and clarity of standards are important.

Example : Activating a permit to work in a confined space may require confirmation
of atmospheric measurements and a rescue plan – without this, the “in progress”
status is not possible.

6) Cooperation with security and gate –admission and verification at the entrance

In practice, many problems begin at the entrance to the facility: incomplete
documents, lack of confirmations, unclear scope.

Example : security can see whether a person has active access to a specific job and
zone, instead of relying on paper or declarations.

Additional features that complete the picture of the plant’s “operating system”

Live Permits work most effectively when they are part of a broader ecosystem: safety, maintenance, and logistics.

Key success factors for Live Permits implementation

Risks and issues to consider

What’s next: from “LIVE” permits to predictive prevention

The next step is to use data from the process (statuses, holds, conflicts, events,
locations, schedules) to predict risks and eliminate them in advance:

Live Permits is the foundation: if an organization has a single version of the truth about field work, it can realistically move from reaction to prevention.

Conclusions

Live Permits is a practical response to a problem that is commonplace in many plants today: safety requires tightness, and operations require speed. Digital work orders with real-time updates — linked to location and compliance requirements – allow these goals to be reconciled without compromising safety.

At InnerWeb®, we build solutions for industrial environments where it is not only “compliance on paper” that counts, but also real control of working conditions, transparency for stakeholders, and the ability to respond quickly. Our implementations and pilot projects show that this model works when it covers the entire ecosystem: health and safety, maintenance, contractors, security, and logistics on site.

About the Author :

Mr. Marcin Worecki,
CEO & Founder
InnerWeb Sp. z o.o. 

Mr. Marcin Worecki, CEO of InnerWeb®, is a visionary engineer with over 20 years of technical and industrial experience.

Together with his team, Mr. Marcin Worecki creates unique legal technology for modern industrial plants based on his own experience, customer requirements, and a deep understanding of the global problem of work permits in industrial plants.

As a result, the InnerWeb® System covers the entire process of managing external technical personnel, from training upon entering the plant, through written instructions for work and particularly dangerous work, as well as audits, acceptance, and permit renewals. InnerWeb® combine electronics, physics, algorithms, artificial intelligence, augmented reality, blockchain, web and mobile applications.

InnerWeb® has based their legal technology on a real-time location system, which also allows InnerWeb® to supervise the work being carried out, improve safety and alert in case of danger, which InnerWeb® protect with a patent in 23 countries (EU and US).

New technological solutions are InnerWeb®‘s passion, allowing InnerWeb® to fully realize their potential. InnerWeb® is open to cooperation and focused on completing the tasks assigned to them. InnerWeb® deliver extremely difficult projects and objectives, making the impossible possible. InnerWeb® operate quickly, dynamically, effectively, and proactively.

Mr. Marcin Worecki can be contacted at:

LinkedIn | E-mail 

About InnerWeb® :

InnerWeb® provides technologies for industrial environments, focusing on safety, maintenance, and organizational efficiency.

InnerWeb® combine software and infrastructure (including BLE) to build location and process solutions, such as Live Permits (mobile work permits) and systems that support real-time risk control.

InnerWeb® carry out projects in the form of implementations and pilot programs, including co-financed projects, where, in addition to process digitization, verification of operational value in real plant conditions is key.

InnerWeb® can be contacted at :

InnerWeb®
ul. Michała Grażyńskiego 14
43-300 Bielsko-Biała, Polska

InnerWeb®’s Social Media Handles :

LinkedIn | Website | Youtube | Facebook

For InnerWeb® Technical Support : Email 

Tel: +48 668 669 621

For InnerWeb® Commercials Service : Email 

Tel: +48 668 669 328

The post Live Permits: real-time Permit-to-Work (PTW) appeared first on Industry4o.com.

As the world grapples with geopolitical volatility and uncertain economic tides, India stands tall, emerging not just as a resilient player but as a beacon of hope for the future. With a projected GDP growth of 8.2%, India is carving its path to become a global economic powerhouse. Yet, the country’s success story is far from linear—there are multifaceted challenges and opportunities ahead, particularly in the realms of innovation, sustainability, and inclusive growth.

Key Trends Shaping India’s Future :

Resilient Growth Amid Global Challenges :

India’s economy is projected to grow robustly, with a per capita consumption reaching approximately $3,000 by 2050. While the per capita consumption for consumer goods is currently at $54, this offers immense room for growth, particularly in rural areas where women’s participation in the workforce has risen to 35-40%. This demographic shift holds the promise of increased economic activity and greater social equity.

Innovation and Intellectual Property (IP) :

India’s R&D and IP patent landscape must see dramatic growth if it is to emerge as a global leader in technology. Fostering a culture of innovation will be crucial as India aspires to lead in fields like AI, biotech, and semiconductors.

Inflation and Consumer Sentiment :

Controlling food inflation is essential. The subdued consumer demand in recent years signals the need for more nuanced fiscal and policy interventions to ensure that growth benefits reach all sections of society.

Private Equity and Mutual Funds :

Private equity (PE) investments have been one of the key growth engines for businesses, while the mutual fund sector is growing at 15%—outpacing traditional bank deposits and fixed deposits (FDs). This shift signals a growing investor confidence in the Indian market.

Financial Reserves and Currency Volatility :

With $650 billion in reserves, India is well-positioned to handle financial shocks. However, the looming depreciation of the rupee and the looming risk of the exchange rate crossing the 100/USD mark could be a silent tax on exporters and citizens alike.

Strategic Challenges and Solutions :

Proactive Policy Management :

India must move beyond reactive policymaking and adopt a more strategic, anticipatory approach. Whether it’s negotiating tariffs or addressing geopolitical challenges, foresight and long-term planning are crucial to avoid the “firefighting” approach that hinders sustainable growth.

Global Trade and Negotiations :

India must strengthen its global negotiating position. While countries like Mexico and the U.S. have demonstrated an aggressive stance in renegotiating trade terms, India has often been seen as an adjustable, not indispensable, partner. To elevate its global status, India needs to leverage its market size and geopolitical importance to secure better trade deals.

The Role of Youth and Education :

India’s demographic advantage is undeniable—by 2050, the country is expected to have over 100 million high-net-worth individuals (HNWIs). However, the country must invest heavily in skilling, re-skilling, and up-skilling its workforce, particularly in emerging fields like AI, semiconductors, and renewable energy. This requires an overhaul of education systems, aligning them with future job market needs.

The Vision for India’s Economy in 2050 :

Digital Payments and Currency :

By 2030, digital payments in India are projected to exceed 80%, and the Digital Rupee could account for 25-30% of retail payments by 2040. India’s digital-first economy will serve as the backbone of its future growth, contributing significantly to GDP expansion from $4T to $30T.

AI and Wealth Management :

AI-driven models are expected to reduce non-performing assets (NPAs) by 40%, while the wealth management industry is set to evolve to cater to an increasing number of HNWIs. CXOs must balance technology adoption with ethical considerations, particularly in the areas of finance, healthcare, and retirement planning.

Sustainability and Green Growth :

India’s future economic growth will also be defined by sustainability. The country must aim for 50% of its energy needs to be met from renewable sources by 2050, while simultaneously advancing green financing initiatives to drive low-carbon growth.

A Comprehensive Action Plan for India’s Economy :

A – Access :

Ensure universal access to digital infrastructure, healthcare, education, and global markets. Bridging the urban-rural divide is crucial to fostering inclusive growth.

B – Backlogs :

Fast-track judicial, infrastructure, policy, and project backlogs to increase efficiency and development pace.

C – Costs & Corruption :

Reduce transaction costs and curb corruption through digitization, transparent procurement, and real-time audits. Transparency must be enforced at every level

D – Regulatory Delays :

Establish time-bound approvals, single-window clearances, and predictable policies to boost ease of doing business and attract global investment.

E – Employment :

Job creation must be a priority, particularly in manufacturing, MSMEs, green energy, and the digital economy.

F – Foreign Policy :

Strengthen strategic multi-alignment, leveraging India’s role as a bridge between the Global North and South to navigate geopolitical tensions.

G – Geopolitics :

India must use its demographic, economic, and diplomatic weight to counter supply chain risks and enhance regional stability.

H – Human Capital :

Skilling and up-skilling should be aligned with emerging technologies such as AI, semiconductors, and climate tech.

I – Infrastructure :

Build world-class infrastructure—roads, ports, logistics, and energy grids—to support India’s $5T+ economy aspirations.

J – Judicial Reforms :

Speed up justice delivery with tech-enabled courts and alternative dispute resolution systems.

K – Knowledge Economy :

Transition from a service-based economy to an IP-led knowledge economy, focusing on AI, deep tech, and biotech.

L – Logistics :

Improve logistics efficiency and bring down logistics costs to global benchmarks through multimodal integration and effective supply chain management.

M – Manufacturing :

Position India as the global manufacturing hub, leveraging the “Make in India” and “PLI” schemes to replace China as the world’s factory.

N – National Security :

Strengthen national security—cyber, space, maritime, and border security—amid rising global tensions.

O – Open Markets :

Pursue balanced trade policies, with strategic FTAs that protect domestic industries while expanding export opportunities.

P – Policy Stability :

Consistent, long-term government policies to build investor confidence and foster trust in the Indian market.

Q – Quality & Standards :

Establish global quality standards across manufacturing, education, healthcare, and governance.

R – Research & Innovation :

Increase R&D expenditure and foster academia-industry collaborations to boost innovation and IP certifications.

S – Sustainability :

Balance economic growth with sustainability by advancing green energy, climate action, and renewable financing.

T – Technology Adoption :

Rapid adoption of technologies such as AI, block chain, machine learning, and Industry 4.0 to maintain competitive advantage.

U – Urbanization :

Develop smart, inclusive cities with efficient transport, housing, and digital governance systems.

V – Vigilant Governance :

Data-driven, accountable, and citizen-centric governance should be prioritized in all levels of government.

W – Workforce Mobility :

Facilitate the movement of the Indian workforce, both domestically and globally, by recognizing acquired skills and promoting global employment opportunities.

X – Exports :

Expand high-value exports—particularly in electronics, defense, pharmaceuticals, and professional services—to diversify markets and reduce dependence on a few.

Y – Youth Dividend :

Invest in the education, entrepreneurship, and innovation capacities of India’s young population to harness its demographic dividend.

Z – Zero Tolerance for Inefficiency :

Implement zero tolerance for inefficiency, delays, and systemic leakages to fast-track India’s rise as a global economic leader.

Conclusion :

India stands at a transformative juncture in its journey to becoming a global economic leader. With a strategic focus on digital infrastructure, innovation, sustainability, and inclusive growth, the country has the potential to redefine its role in the global economy by 2050. As we navigate these challenges and opportunities, India must be agile, proactive, and committed to long-term vision.

About the Author :

Mr. Jawahar Lalla
Technology & IT Consultant / Blogger/ Podcaster/ Digital Influencer

Mr. Jawahar Lalla is a seasoned Motivational Speaker, Industry Expert, and Professional Trainer.

Mr. Jawahar Lalla with over 40 years of extensive experience in the IT industry, brings a wealth of knowledge as a senior management executive, writer, blogger, and speaker.

Mr. Jawahar Lalla is also digital influencer having more than 2 Lakhs connects across social media and digital platforms.

Mr. Jawahar Lalla has contributed insightful articles to both Indian and international publications on industry-related topics.

Mr. Jawahar Lalla is frequently invited as a keynote speaker and panel judge at conferences and seminars, where his deep industry insights and leadership experience are highly valued.

Mr. Jawahar Lalla is a passionate reviewer, he has reviewed numerous books in the fields of technology and management.

Mr. Jawahar Lalla is also active as a blogger, podcaster, public speaker, and even a model.

Mr. Jawahar Lalla is a prolific co-author, he has contributed to more than 450 anthology books.

Mr. Jawahar Lalla interviews and podcasts are available on his YouTube channel: jawaharlalla3573.

Mr. Jawahar Lalla can be contacted at :

LinkedIn | YouTube | E-mail | E-mail2 | Mobile : +91 – 9819428307

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Is ASI – Artificial Super Intelligence here? Are T-1000 Terminator machines appearing?

Remember the Terminator movies, where Arnold plays the killer/savior Cyborg from the future? The line ‘Hasta la vista baby’ or See You Later? Several films have portrayed robots and cyborgs as good and evil machines. But are they the future of ASI?

Artificial Super Intelligence (ASI) is a conceptual construct of the future stage of AI. ASI will feature systems that supersede areas or domains of human cognitive capabilities. Some of the domains are cognitive skills, creativity, reasoning, and problem-solving.

Sam Altman, CEO of OpenAI, terms the era of ASI “The Intelligence Age.” This is when computers manage to improve on many complex tasks that only humans can do. He says that ‘deep learning has really worked. Algorithms are developed that truly learn any distribution of data, and the underlying rule to compute and give better results.

Mo Gawdat, in his book, cautions us and argues that ASI will surpass human abilities, think, see into the future, predict outcomes, and even use sensors to see around physical and virtual corners. ASI bots will certainly help humans to solve problems, provide healthcare, and improve the quality of life.

Popular movies and books however paint a dystopian and malevolent view of ASI. This perception is reinforced by sci-fi movies like M3Gan, 2001: A Space Odyssey, Blade Runner, Westworld, Avengers: Age of Ultron, Ex Machina, and many more, where AI bots are evil. They subjugate humans, create wars, and so on. These fantasy movies should not be taken seriously.

However, what if the nightmare becomes true? Find out what ASI is, technology, use cases in this blog.

What are AI Levels

It is essential to understand the various levels of AI and what each level can do. AI is defined at seven levels, from Level 1 to Level 7. Figure 1 illustrates the 7 levels and what AI does at each level.

L1 is the basic level and uses rules and logic circuits to automate some tasks. It is used mainly to reduce manual work. We are now at L3 and L4. Cyborgs and other entities are at Level 7+ and can be termed as ASI.

Still a long, long way to go? Let us look at the current research and emerging trends in ASI.

What are the latest Trends in ASI?

However, ASI will need exponentially advanced processors, hardware, a new environment or operating system, and programming languages. Likely systems in the future are discussed in the next section.

What future chips and Hardware are needed for ASI

Full-blown Artificial superintelligence will require a new generation and class of chips and processors, and advanced quantum computers. While these techs are not yet built, an assessment of future hardware and chips is speculated below.

New generation of frameworks and programming languages are needed for ASI. These are examined in the next section.

OpenCog Hyperon platform and MeTTa Programming Language for ASI

Artificial superintelligence will need a new platform operating system and programming language, among other developments. Let us look at OpenCog Hyperon and MeTTa Programming Language.

OpenCog Hyperon

MeTTa Programming Language

MeTTa, or Meta Type Talk, is a new programming language from OpenCog Hyperon. It is the language of thought and provides fundamental and general functionalities to handle symbols, groundings, variables, types, substitutions, and pattern matching.

The main objective of MeTTa is to provide a robust, flexible, and mathematically grounded foundation for developing ASI. It is used for human developers to script AI processes and for AI algorithms themselves to perform learning and reasoning activities.

MeTTa is the firmware that holds components of the OpenCog Hyperon cognitive architecture, allowing for seamless interoperability between diverse AI modules such as neural networks and probabilistic logic networks. It is the core running environment for the ASI Chain, a layer-1 blockchain infrastructure for decentralized AI applications.

Important components of MeTTa are:

Beneficial use cases of ASI

This is the most important question of artificial superintelligence. ‘How and where will artificial superintelligence be used?’ Let us look at areas where artificial superintelligence can be implemented for positive impacts.

Military use cases of ASI

Remember Skynet, the malevolent ASI from Terminator that took over humanity? Not sure if this will happen. But artificial superintelligence has several critical military use cases that are beyond current human and AI applications. It is expected to transform warfare and defense strategies.

Some of the possible use cases are:

The list is endless, as seen in several movies. However, the costs and resources needed to build these systems will probably exceed the global GDP. So, you can relax for now.

Can ASI take over humanity?

Manuel Alfonseca et al. argue that while ASI will be invaluable, it should be contained and secured so that it does not ‘escape’ and create a catastrophe for the world. One problem is that ASI will have all the knowledge that humans have, and it will figure out a way to crack the containment.

The concept of AI “taking over” humanity as narrated in science fiction is a speculative and controversial topic. Advanced artificial superintelligence can pose significant risks if not developed responsibly. A rogue military dictator or an evil corporation can attempt this exercise.

Such an effort will need massive, massive computing resources, global collaboration, and augmentation of human capabilities. This may not happen. However, one can never predict the irrational actions of deranged leaders.

Summing Up

The blog examined the fascinating concept of Artificial Super Intelligence (ASI). This technology of the future is expected to surpass human intelligence and cognitive skills. The technology is in the early development stage, but research is ongoing.

Several resources, such as hardware and processors, languages, frameworks, and investment, are needed. ASI promises several benefits that go beyond what humans can conceptualize. Certain negative impacts in military applications are also predicted.

Can artificial superintelligence compose original classics of Clapton, Willie, Waylon, Dolly, Emmylou, JP, IM, Motorhead, and other Monsters of Rock? An emphatic No! Once in a lifetime, geniuses created these classics, and ASI will attempt to copy them. I hope this never happens.

Legal Disclaimer: The views, thoughts and opinions expressed in this article are those of the author and do not reflect the views or positions of INDUSTRY 4.0. The content is provided by the author as-is and is published solely for informational or educational purposes.

INDUSTRY 4.0 does not guarantee the accuracy, completeness or usefulness of any information presented and is not liable for any errors, omissions or outcomes resulting from the use of this information. The responsibility for the content lies entirely with the author.

Banner Image Credit: Shashi Kadapa with Google Gemini

About the author :

Mr. Shashi Kadapa

Based in Pune, India, Mr. Shashi Kadapa is an engineer, MBA and has worked with leading IT and manufacturing firms. A multi-hyphenate, he has roles as a technical writer, and SEO content writer with a focus on IT and tech topics.

Creative fiction is his passion, and he serves as the managing editor of ActiveMuse, a journal of literature. His stories across multiple genres are published in more than 45 US and UK anthologies.

His creative works

Mr. Shashi Kadapa can be contacted at :

E-mail | LinkedIn | Blog | Mobile : +91 7387492371

Also read Mr. Shashi Kadapa earlier article:

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