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  • Jun 17, 2021

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Evolution of Industry from Industry 1.0 to Industry 4.0 & Industry 5.0: From Craft to Digital Manufacturing to Digital Society

In 1776, the first wave of Industrialization in the World began when James Watt FRS improved the already functional steam engine of Thomas Newcomen's with his Watt steam engine. The first one of which was deployed initially to pump water at the Staffordshire colliery & the second one was used for blowing air into furnaces at John Wilkinson's forges. By the 19th century, stationary steam engines were powering the factories of the Industrial Revolution. Steam engines replaced sail for ships, and steam locomotives operated on the railways. The wheel of Industrialization had started to move.

However, the second major breakthrough had to wait for almost a century, till 1879 when Carl Benz developed the first stationary gasoline engine. By 1885, he created a lightweight car powered by a gasoline engine, in which the chassis and engine formed a single unit & which he patented on 29th Jan 1886. Despite his path breaking patent, this phase of industrialization had to wait for a few more decades and it was for Henry Ford, who moved the world of manufacturing from centuries old craft production system into the age of mass production but procuring same models repeatedly. Remember his famous saying,” You can have any color as long as it's black”.

This philosophy had to give way for another radically new wave of change which hit the world from Japan when around 1950, after World War II, when Japan was rebuilding itself, Eiji Toyoda & Taiichi Ohno at Toyota Motor Company pioneered the concept of Lean Manufacturing also called “Toyota Way”. This philosophy was dramatically opposite to the American manufacturing system. The Toyota system is also known by the more generic terms like “lean manufacturing” and “just-in-time production” or “JIT Manufacturing.” It was such a path breaking idea that even after 70 years in practice, this is still being followed in almost all walks of activities for improving performance since it is more of a philosophy rather than anything else.

The pillars of Toyota Production system were certain key elements like Kanban (signaling system creating a pull instead of push system), Andons (Visual controls), elimination of Muda (reducing waste), Kaizen (continual improvement), and Jidoka (intelligent automation / automation with a human touch / automation with human intelligence). Over the time, with development of semiconductors and high end electronics, these very systems of TPS which were mastered manually are now being taken over by the newer technologies. Progressively these very systems are moving to real time data accessing, monitoring, capturing, analyzing & reporting in any kind of work being done, from a simple activity to a highly complex process. This automation has led to the next phase of Industrialization, what we call Industrialization Phase 3.0 onwards. The wheel of Industrialization was now picking up pace & was spinning at full throttle.

Why Such Changes or Progressions?

With the progression of human society, there has been a dramatic shift in consumer behavior, needs, choices & requirements. Over the time, people look for customized products to meet their individual requirements as well as to be different from others. However, since in the first two phases of industrializations, neither industries worried much about meeting these personalized requirements of customers nor customers demanded them as it was not a customer oriented market. The industries were only meeting the basic needs of society.

With progression of time, the consumers started getting more vocal with their demands for customized goods and ultra-personalized services. And when a company fails to deliver that, most consumers are quick to move to a competitor that offers a more tailored customer experience. Industry 4.0 failed to fully acknowledge this demand for personalization. Industry 5.0 is here to make amends.

This has forced the industries to change the way of their working in order to survive & grow and with this paradigm shift, the industries are continuously evolving in order remain competitive as well darling of customers.

Now let’s try to go a bit deeper to understand these phases of industrialization & their progression from version 1.0 to current state:-

Industry 1.0 (1780~1850): As shared above the process of industrialization had begun sometime 1760, when people started understanding power & force and devised ways to harness them & control them for reducing burden on human beings. Then they developed machines which utilized these raw powers under controlled conditions for the benefit of mankind. With time, availability of fuel sources like coal made these steam based machines more feasible, affordable and the idea of manufacturing with these machines quickly spread. The production capabilities increased, business also grew from individual cottage industry to bigger organizations to meet the increasing requirements of society. These machines allowed faster and easier production, and contributed in development of more innovations and technologies. This was the First Industrialization which was primarily a phase of taming raw natural power and putting them in use under controlled conditions, which now we call Industry 1.0.

Industry 2.0 (1850~1960): Once with usage, when people started understanding these power & forces in more depth, the second industrial revolution picked up. Historians sometimes refer to this period as the period of “The Technological Revolution” when electricity became the primary source of power. It was easier to handle, to transmit & control than any of the earlier known energy sources of power. Introduction of electricity as a power source meant that businesses could be located nearer to the area of consumption of goods, which may be far away from power sources.

With increase in volumes, more & more people were getting engaged in manufacturing activities, which allowed people to develop a number of management programs that made it possible to increase the efficiency and effectiveness of manufacturing facilities. Division of labor as well as time motion studies were developed. These new management techniques allowed workers to do their job with lesser fatigue, lesser wastage of time & lead to increase in productivity. Mass production of goods using assembly lines became commonplace. American mechanical engineer Frederick Taylor introduced approaches of studying jobs to optimize worker and workplace methods.

At the end of World War II, when Japan was rising from ashes, Toyota pioneered the concepts like Kanban, Andons, Muda, Kaizen and Jidoka (refer the beginning of this article to understand these terminologies) & evolved a new distinctive manufacturing system with unique features such as lean manufacturing (now known as Toyota Production System). These were powerful tools with far reaching impact on productivity, process improvement & reducing wastes & with advent of semiconductors and rise of the electronic industry, these visual control systems slowly paved the way to automated control systems when the 3rd wave of industrialization hit the industries.

Industry 3.0 (1960~2010): With the invention of the transistor in 1947 by John Bardeen, Walter H. Brattain, and William B. Shockley of the Bell Lab, the third Industrial Revolution was already knocking on the doors and it was only a matter of time that it entered the manufacturing domain. When in 1958, Kilby demonstrated the first working IC the stage was set.

Around 1970, with the development of & use of electronics and IT (Information Technology), was already in use to automate the manufacturing which began with the first computer era. These early computers were often very simple, unwieldy and incredibly large relative to the computing power they were able to provide, but they laid the groundwork for a world today that one is hard-pressed to imagine without computer technology. The invention and manufacture of electronic devices, such as the transistor and, later, integrated circuit chips, made it possible to more fully automate individual machines to supplement or replace operators.

In 1970, when Gordon Moore formulated his imperial observation as Moore law stating that the number of transistors on a chip will double every 24 months & the cost of manufacturing a transistor drops will be dropping by half about every 2 years the wheel of dramatic changes in manufacturing in coming times was to become unstoppable. Post 1970, the period saw massive development in hardware & software systems to capitalize on the electronic control system. Slowly, these systems were seen everywhere, from hand-held devices like packet radios, music players to very complex industrial setups.

This was also the period when due to pressure for reducing costs caused many manufacturers to move operations to low-cost countries and the world really started becoming a global village. The extended geographic dispersion resulted in the formalization of the concept of information management & supply chain management. However the real impact of this was felt when the Internet exploded in 2000. With ever increasing speed & accessibility of the Internet, this time saw massive advancement of automation in manufacturing, their interconnected system as well as flow of information. During Industry 3.0, more & more automated systems were introduced onto the assembly line to perform repetitive tasks. Although automated systems were in place, they still relied on human input and intervention & another gear change was needed.

Industry 4.0 (2010~2020): The phrase Fourth Industrial Revolution or Industry 4.0 was first introduced by Klaus Schwab, executive chairman of the World Economic Forum, in a 2015 article & in simple terms it was referred as a phase to optimize the computerization of Industry 3.0. With more & more automation the manufacturing processes of the Industry 3.0 gradually moved towards the Industry 4.0 with inter connected systems of computers, not directly wired but many times over the cloud through a series of servers via Internet and were communicating with one another to ultimately make certain decisions, without human involvement.

Slowly, a combination of cyber-physical systems, the Internet of Things (IoT) and the Internet of Systems made the smart factory a reality in the Industry 4.0 revolution. As a result of which smart machines started becoming smarter as they get access to more data & more computing powers. This led to factories becoming more efficient and productive and less wasteful. Ultimately, it's the network of these machines that are digitally connected with one another to create, store and timely share information resulting in the true power of Industry 4.0. These smart machines autonomously exchange information, trigger actions and control each other without human intervention. They can enable systems to share information, analyze it and use it to guide other equipment for intelligent actions. Industry 4.0 incorporates cutting-edge technologies including additive manufacturing, robotics, artificial intelligence and other cognitive technologies, advanced materials, and augmented reality etc.

The development of new technology has been a primary driver of the movement to Industry 4.0. Some of the programs first developed during the later stages of the 20th century, such as manufacturing execution systems, shop floor control and product life cycle management, were farsighted concepts which could not be brought to manufacturing that time as technology wasn’t ripe for their complete implementation. Now, Industry 4.0 has brought these programs to their full potential where exchange of information has been made possible with the Industrial Internet of things (IIoT) as we know it today. Key elements of Industry 4.0 include:

  • Cyber-physical system – a mechanical device that is run by computer-based algorithms.
  • The Internet of things (IoT) – interconnected networks of machine devices and vehicles embedded with computerized sensing, scanning and monitoring capabilities.
  • Cloud computing – offsite network hosting and data backup.
  • Cognitive computing – technological platforms that employ artificial intelligence.

Industry 4.0 did achieve these goals:

  • Improved connectivity - Digitize all data exchanges, enable digital-to-physical processes, and improve horizontal integration.
  • Optimize processes - Increase networking, digitization, and automation; boost efficiency; improve/eliminate error-prone processes; reduce waste.
  • Increase coordination - Move to fully digital supply chain management from sourcing to post-sales.
  • Create new business models such as servitization (meaning industries using their products to sell “outcome as a service” rather than a one-off sale) and enhanced product development.

If we need to summarize the evolution on Industry till now as one picture, it can rightly be depicted as below:

Industry 5.0 (2020 & beyond): A Darwin’s Evolution

Less than a decade has passed since talk of Industry 4.0 first surfaced in manufacturing circles & still in achieving its full potential, yet visionaries are already forecasting the next revolution – Industry 5.0. If the current revolution emphasizes the transformation of factories into IoT – enabled smart facilities that utilize cognitive computing and interconnect via cloud servers, Industry 5.0 is set to focus on the return of human hands and minds into the industrial framework.

The specific time frame for beginning of Industry 5.0 cannot be stated but certainly we can say 2020 is a definitive milestone for Industry 5.0 when with the advent of COVID-19 impact, its need was strongly felt. In the challenging times of COVID-19 times, while dependence on manpower in manufacturing had to be reduced yet the full judgment could not be left to machines and in such contradictory requirements, we need the fully grown model of Industry 5.0.

The term Industry 5.0 refers to people working alongside robots and smart machines which have smart learning capability. It’s about robots helping humans work better and faster by leveraging advanced technologies like the Internet of Things (IoT) and big data. It adds a personal human touch to the Industry 4.0 pillars of automation and efficiency. For example, in manufacturing environments, robots have historically performed dangerous, monotonous or physically demanding work, such as welding and painting in car factories and loading and unloading heavy materials in warehouses. As machines in the workplace get smarter and more connected, Industry 5.0 is aimed at merging those cognitive computing capabilities with human intelligence and resourcefulness in collaborative operations.

Industry 5.0 is a logical evolution of Industry 4.0, a revolution in which man and machine reconcile and find ways to work together to improve the means and efficiency of production. Funny enough, the fifth revolution could already be underway among the companies that are just now adopting the principles of Industry 4.0.

Industry 5.0 – Human-centric AI – driven solutions

Currently, two visions emerge for Industry 5.0. The first one is “human-robot co-working”- In this vision, robots and humans will work together whenever and wherever possible. Humans will focus on tasks requiring creativity and robots will do the rest. Another vision for Industry 5.0 is bio economy. Smart use of biological resources for industrial purposes will help to achieve a balance between ecology, industry, and economy. According to the European Commission, bio economy is “the production of renewable biological resources and the conversion of these resources and waste streams into value-added products, such as food, feed, bio-based products, and bioenergy. It includes agriculture, forestry, fisheries, food, and pulp and paper production, as well as parts of chemical, biotechnological and energy industries. Its sectors have a strong innovation potential due to their use of a wide range of sciences (life sciences, agronomy, ecology, food science, and social sciences), enabling and industrial technologies (biotechnology, nanotechnology, information and communication technologies (ICT), and engineering), and local and tacit knowledge."

Moreover, other themes, such as space life, space industries, and space mining, may be the next or a part of the next revolution. Scientists are already cautioning us to be careful in using space resources. Space mining may turn into the next “gold rush”.

However, it’s a matter of time which will tell us, finally which version takes over, yet there are few factors which are pushing the industry towards its new version which is sometimes also called Society 5.0 instead of Industry 5.0.

Factor A: Need to cater to individual choices: Current generation’s product choices are largely driven by their beliefs, personal preferences, and individual identities rather than popularity alone. This generation is also looking for a personalized service when they go out and search for a product or service & they are willing to pay a premium for that extra service being provided to them. Statistics tell us that 58% of Gen Z consumers with a monthly income of $6,631 and above are willing to pay more for personalized offers while 70% of them will pay a premium for goods from brands that embrace causes they identify with. Similarly, 62% of customers are ready to pay more to customize their electronic devices, such as phones and tablets.

The modern customer is already spoiled by highly personalized digital services thanks to Amazon, Netflix and the like. Now they want to bring that newly developed habit to the physical realm.

Ultra-personalization and mass customization being done right now

There is a study which shows that by 2030, most American consumers expect personalized products and services to be commonplace and are willing to pay a premium for them. [CITE Research for Dassault Systèmes]

Factor B: Public concerns regarding sustainability and overproduction – Providing customers with the right products at the right time can reduce dead stock, production waste, and logistics costs associated with returns and recalls.

Factor C: The rise of on-demand services and sharing business models – For Millennial and Gen Z, the two generations with the most buying power at present, consumption no longer equals ownership. Bringing intelligent and connected products to the market and launching servitized offerings can help manufacturers maintain a connection with every customer long after the initial sale.

Factor D: Availability of technology –There are means, ways & technologies available to meet that requirement & with advancement of technology, there has been tremendous advancement in machine learning and deep learning, AI while industrial robotics have achieved a new level of quality. The newest generation of machine vision powered systems can inspect goods and detect potential defects with higher precision than any human operator. Some trailblazers in this industry have even gone a step further and have robots working alongside humans on manufacturing floors.

  • Heineken, for example, employs a machine vision system at a beer bottling facility in France that can inspect up to 80,000 bottles per hour with a 99.99% accuracy. The process industries heavily rely on sensors and AI-powered anomaly detection systems to register abnormalities in equipment behavior and detect potential damage.
  • Nike and Adidas are heavily investing in industrial robotics to improve their manufacturing processes and offset the cost of human labor.
  • Siemens, another leader in the Industry 4.0 space, has managed to automate approximately 75% of the production processes at one of their plants. Now roughly 1,500 of the company’s field employees are responsible for operating software and monitoring production instead of performing so-called “3D” - dirty, dangerous, and difficult – tasks. That’s the kind of synergy Industry 5.0 aspires to.

While the ultimate vision of Industry 4.0 was near-total automation, Industry 5.0 places a stronger emphasis on the interplay between humans and machines, there are several factors are contributing to the rise of ultra-personalized products and services:

  • Commoditization of big data analytics and machine learning
  • Major improvements in computer vision and 3D scanning/modeling
  • Lower prices for and wider use of cobots
  • Wider adoption of 3D printing for prototyping
  • Higher degree of supply chain digitization leveraging these innovations not only improves the quality, effectiveness, and speed of your manufacturing processes but lets you tap into the trillion-dollar value pool created by personalization.

The main goal of Industry 5.0 is to create a new vector of collaboration between humans and technology (robots, cobots, IoT devices, and other cognitive systems) at production facilities and beyond.

The tech prerequisites for ultra-personalized manufacturing in Industry 5.0

Transitioning to a more agile supply chain and manufacturing process is the first integral step toward mass personalization. However, to remain personal, these processes will also need to include a human touch i.e. input from customers and the production team that too on a real time basis. And at the end of the day, the viability of mass personalization strongly depends on its cost-effectiveness.

Some of the potential challenges expected with this evolution with probable solutions:

  • Data management platform & data governance processes

    Problem Most customer data required for hyperpersonalization is either trapped in silos or cannot be effectively delivered to a centralized repository for real-time analysis.

    Solution Create a unified data management platform that can collect and process all customer insights/inputs, transmit them further down the supply chain, and make them instantly available to different departments.

  • Multiscale dynamic modeling and simulation

    Problem Mass customization increases the complexity of the manufacturing process. Predicting the effectiveness and performance of modified products can be tough without prototypes. Yet creating prototypes for custom products increases manufacturing costs.

    Solution Creating a digital twin for complex processes, products, or services can be a viable alternative to prototyping. The current state of machine learning allows for the creation of highly accurate models of physical objects that can be used to run various simulations to improve performance, predict failure, and improve design

  • Intelligent autonomous systems

    Problem Mass customization increases the complexity of the manufacturing process. Predicting the effectiveness and performance of modified products can be tough without prototypes. Yet creating prototypes for custom products increases manufacturing costs.

    Solution More advanced AI systems, powered by deep and reinforcement learning, are required to run autonomous manufacturing of custom parts. To be effective, algorithms will need to be trained to make optimal decisions with incomplete information, e.g. when the customer fails to provide some input. The agents overseeing production will also require access to better monitoring solutions, in particular for inventory management, supply/demand matching, and maintenance.

  • Cognitive systems and new types of human machine interfaces

    Problem In most cases, industrial automation does not fully remove humans from the manufacturing floor. Instead, human agents need to safely work alongside their autonomous counterparts.

    Solution Thanks to advances in computer vision and deep learning, modern industrial systems can “see” and “sense” human agents working nearby and act accordingly. Newer cobots (collaborative robots) are also equipped with advanced cognition capabilities, making them excellent assistants in various workplace tasks such as palletizing, assembling small parts, packaging, polishing, and inspecting. The issue is that most cobots today have only basic learning capabilities, as they mostly rely on sensor data that communicates distance, speed, proximity, and some other variables required for safe and effective operations.

  • Additive manufacturing

    Problem Most off-the-shelf enterprise resource planning (ERP) solutions cannot track individual custommade parts, such as those produced by 3D printing. Some systems may consider customized parts as a single product (SKU). If no identification is manually added to each part, customers may receive the wrong item. Maintaining quality digital records from each stage of the design and manufacturing process is essential to control quality, reduce waste, and capture even more value from additive manufacturing.

    Solution To add additive manufacturing to their mix, most companies will need to rethink their data architecture and build a viable pipeline for instantly available insights.

  • The Human Touch

    Problem Automation isn’t a threat to human jobs.

    Solution It’s an opportunity to step away from 3D (dirty, dangerous, and difficult) work to 3C (collaborative, creative, and custodial) tasks.
    Despite all the current (and future) progress in AI and robotics, humans will remain uniquely qualified for certain roles. Ideation, for one, is a domain where humans will excel no matter what. We have a natural ability to conceive new things, bring seemingly incompatible ideas together, and develop new and creative approaches to solving problems. Self-learning algorithms, no matter how good they are, can only create new ideas. Their shortcoming is that they cannot assess how usable these ideas might be in the real world.

Person + machine – right-sizing the workforce for Industry 5.0

Upgrading tools and manufacturing processes is just one part of the AI driven industrial revolution. Investing in talent to support those new initiatives is far more crucial for long-term success. For 36% of manufacturers, the technical skills gap is a major stumbling block to realizing more value from their smart factory investments. In addition, 57% of industrial leaders say they lack AI talent – the enablers for all the autonomous and intelligent solutions that are to take over the 3D chores. Sourcing the right talent is just one piece of the puzzle, though. Up skilling and training existing employees is far more crucial. Smart tech isn’t taking over human jobs per se. But it is radically changing the ideal employee skill set.

The Change in Skill Requirements – Now & Future

Skill Today (what Adds to Value Today)
- Basics of modern programming or software engineering
- Manufacturing skills
- Great communication skills
- Innovation skills (e.g. brainstorming, design thinking)
- Traditional IT skills

Skill Tomorrow (what to grow or strengthen for future)
-Deep understanding of modern programming or software engineering techniques
-Digital dexterity, or the ability to leverage existing and emerging technologies for practical business outcomes
-Data science
-Connectivity
-Cybersecurity
-Manufacturing skills

How To Bridging the tech skills gap: Possible suggestions

Stage 1


Make a List of Current Sills/ Expected Changes
- Low-skilled jobs that can be supplemented or replaced by automation and AI
- Positions that require uniquely human skills
- High-skilled jobs that will require additional tech training
- New AI-specific jobs that require unique expertise

Stage 2


Develop an inventory of the core Industry 5.0 skills which will be needed. Then explore
-How many internal resources do we have to meet these needs?
-Which skills can we acquire externally (via outsourcing, partnerships, and contractors)?
-What is the size of the remaining gaps we’ll need to close by hiring, training, and up skilling?

Stage 3


Reimagine on-the-job learning programs with digital technologies
-Start assembling an e-learning portal that will contain your digital database of all training materials to promote self-learning.
-Use proprietary data collected from equipment along with tactical knowledge from senior employees to develop more targeted training.
-Leverage new technologies such as augmented and virtual reality to deliver immersive learning experiences.
- One need to be proactive about explaining the implications of AI and robotics to teams.
-Communicate about is organization planning to change roles and responsibilities and what benefits can be expected.

Stage 4


Explore alternative candidate sourcing models.
- Tap into the open talent ecosystem – a portfolio of contract employees, talent networks, and external service providers that can fill your workforce needs on an ad-hoc basis.
- Reactivate the retired workforce by providing retired employees with an option to work on shortterm projects where their industry expertise is required or to participate in training development.
- Engage with a managed remote team of domain specialists to work on new technological solutions.

Conclusion: What are we looking for from Industry 5.0?

Based on above paper, we can easily summarize that what we as society are looking forward for a

  • A Technology that performs the mundane, repetitive, error-prone tasks and where Humans set the strategy, provide oversight, and add creative input for above technology to perform
  • A technology that is able to cater the diverse, individual needs of customers as per their specific requirements without any overproduction, increase in dead stock and wastages
  • A technology which has mastery in optimizing logistic cost
  • Sustainability of operation without affecting the environment.
  • A technology that does the business without losing the human touch.

While in Industry 4.0 focus was on Mass production with high efficiency and low waste, the focus in Industry 5.0 shifts to Mass personalization with high accuracy and at low cost allowing tighter collaboration between cognitive systems, robots, and humans can help businesses harmonize manufacturing processes and become more agile to accommodate market changes and customization requests.

In This Regard, Probably, The More Exact Term Instead Of Industry 5.0 Is “Society 5.0” (Supersmart Society) an alternative That Was Offered In 2016 By Japan's Most Important Business Federation, Keidanren And Being Strongly Promoted By Council For Science, Technology And Innovation; Cabinet Office, Government Of Japan.

Unlike The Concept Of Industry 4.0, Society 5.0 Is Not Restricted Only To A Manufacturing Sector, But It Solves Social Problems With The Help Of Integration Of Physical And Virtual Spaces.

In Fact, Society 5.0 Is The Society Where The Advanced IT Technologies, IoT, Robots, An Artificial Intelligence, Augmented Reality (AR) Are Actively Used In People Common Life, In The Industry, Health Care And Other Spheres Of Activity Not For The Progress, But For The Benefit And Convenience Of Each Person

The Government of Japan has rightly said that in “Realizing Industry 5.0 as we move into Society 5.0 all people’s lives will be more comfortable and sustainable as people are provided with only the products and services in the amounts and at the time needed.”

Blog by - Mr Prabhat Khare

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