“The Fourth Industrial Revolution is creating a demand for new skills and new competencies” by Nicky Verd.
From the very first industrial revolution (mechanization through water and steam power) to the mass production & assembly lines using electricity in the second, the fourth industrial revolution will take what began in the third with the adoption of computers and automation and amplify it with smart and autonomous systems powered by data & machine learning. Industry 4.0 is the digital transformation of manufacturing/production and related industries and value creation processes.
The 4th Industrial Revolution, generally known as Industry 4.0, appears to be modifying the way business’s function and, by extension, the stakes by which they are compelled to compete. Organizations must decide where & how to invest in these new technologies and recognize which ones might best encounter their needs. Without full knowledge of the changes & opportunities Industry 4.0 brings, companies may be at risk.
Industry 4.0 manufacturing is a transformation that makes it possible to collect & analyze data across machines, enabling quicker, more systematic, and more supple processes to manufacture higher-quality goods at lower costs.
Industry 4.0 signals the promise of a new Industrial Revolution 4.0—one that combines advanced production & operations techniques with smart digital technologies to develop a digital venture that would not only be autonomous & interconnected but could analyze, communicate, and use data to lead further intelligent action back in the physical world. It constitutes how smart, connected technology would be implanted within organizations, assets, people, and is signaled by the exposure of capabilities.
In the year 2011 at Hannover Messe, the German government first declared a new initiative to digitize manufacturing – an initiative known as Industry 4.0. Now, it’s less than a decade but the consumption of Industry 4.0 principles – not only in Germany and Europe but around the globe – has been magnificent.
Industry 4.0 integrates physical & digital technologies, including robotics, analytics, high-performance computing, additive manufacturing, advanced materials, natural language processing, artificial intelligence & cognitive technologies, and augmented reality. It consists of 3 steps:
Enormously, respondents saw Industry 4.0 manufacturing as an important initiative – with 90% saying that over the next 5 years it will have a significant impact, and only 9% devaluing the impact. The main goal of Industry 4.0 is to make manufacturing & related industries such as logistics – faster, more customer-centric, more efficient, and while at the same time going far away from automation & optimization and find new business opportunities and models.
Below, we survey some key insights that can enable business leaders to imagine how the 4th Industrial Revolution could affect their worlds.
The Industrial Revolution 4.0 just doesn’t touch “manufacturers” but it can affect all of us. Industry 4.0 has its roots in the supply chain & manufacturing which constitute the backbone of the world as we know it. What things are made of, where they are made, how they are made, and how they get to us, and where they go when we need them fixed: All of these things are part of the product life cycle.
Industry 4.0 principles will modify how we make things, but it could also affect the way how those things are moved (through distribution & autonomous logistics), how consumers interact with them.
The goals of Industry 4.0 projects are: increasing profitability, saving costs, automating to prevent errors & delays, decreasing waste, hurrying up production to work more in real-time, digitizing paper-based flows, and also being able to intervene quicker in case of production issues. Industry 4.0 provides various solutions to optimize, from optimized asset utilization & smoother production processes to better logistics & inventory management during lean transformation.
Industry 4.0 is about the complete life cycle of products & manufacturing doesn’t stand on its own. If you look at the complete value chain & ecosystem within which manufacturing operations live in there are many stakeholders involved. These are all customers. And customers also want to improve productivity, regardless of where they fit in the supply chain. If the final customer wants good products quickly and has increased expectations regarding customer experience, service, quality, and products that are delivered at the exact time they want, this affects the whole supply chain transformation, all the way up to manufacturing and beyond.
In the wider environment where everything is interconnected with software, sensors, IoT technologies, systems of insight & the customer, you can also improve the quality of your products. Automation plays a good role here and so do the components of cyber-physical systems and the Internet of Things by which quality aspects can be observed in real-time and robots decrease errors. Enough companies have increased the usage of robots and at the same time hired more. The reason we mention it in the context of quality is that this is certainly one area where you see cobots popping up (cobots is a term for advanced collaborative robots or say more simply: robots that fit cooperation between man and machine).
When a central industrial asset, such as an industrial robot in a car manufacturing plant lay down, it’s not just the robot that’s smashed. Production is affected, It costs loads of money & unhappy customers, and sometimes production can be fully disrupted. It’s anyone’s worst dream as business continuity is an especially high concern.
On top of all the fixing work, resources, and costs, reputation can be damaged, orders can be canceled. If industrial assets are connected and can be observed through the Internet of Things and issues are handled before they even happen the benefits are vast in VUCA.
Alerts can be set up, assets can be proactively maintained, real-time monitoring & diagnosis becomes possible, engineers can fix issues and the list goes on. A world of new maintenance services opens up as we’ll see. No wonder that asset management & maintenance are the second largest area of IoT investments in manufacturing.
Improving working conditions based on humidity, real-time temperature & other data in the plant, Fast detection & improved protection in case of incidents, detection of the presence of radiation, gasses & so on, better communication & collaboration possibilities, a focus on ergonomics, clean air & clean factory initiatives the list goes on.
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Digital transformation technology is so far used in manufacturing, but with Industry 4.0, now it will modify production. It will drive to prominent efficiencies & change traditional production relationships among producers, suppliers, and customers—as well as between human and machine. Learn Transformation Experts tells some technology trends which shape Industry 4.0 manufacturing.
The smart factory is a supple system that can self-optimize performance across a wider network, self-adjust to & learn from new conditions in real or near-real time, and freely run complete production processes.
The smart factory, a quintessential term from Industry 4.0 & smart factory, use an amalgam of connected devices, data & artificial intelligence to make manufacturing more flexible and responsive, actually revolving around big data analytics, Industrial IoT, connected physical equipment, production techniques, & what can be done with it in a cyber-physical scope.
The strategic importance of smart factories is unquestionable, as early acceptors have reported operating more efficiently & driving more to the conclusion. In the US alone, 86 % of manufacturers believe that smart factories will be the main driver of competition by 2025. Moreover, 83 % believe that smart factories will modify the way products are made.
Research constantly discloses improvement in quality, cost, safety, throughput, and revenue growth through the implementation of smart factory technologies that integrate capabilities in the industrial internet of things (IIoT), robotic process automation (RPA), cloud and edge computing, machine learning, artificial intelligence (AI) and augmented and virtual reality systems, among others. Leaders have a wide range of choices & opportunities concerning smart factory transformations, both in terms of which technologies to use, and how to deploy them during the process of business transformation.
What manufacturers genuinely need is a partner skilled in all 3 features, who has sound knowledge of machines & the manufacturing process, who can find how and where digitalization can help, and who can install and service the tools needed to get there.
The productivity gains achieved through smart factory initiatives will help the manufacturing industry to add $2.2 trillion of value to the global economy by 2023. So far, even if the expected average added value from smart factories is high with $1.9 trillion & expectations concerning smart factory benefits are on the hike.
5G could be the prime factor leading the growth of smart factory solutions. Analysts predict that 5G will be a prime answer to smart factory adoption since it provides higher bandwidth & speed as well as low latency. It can enable more organizations to adopt smart factory solutions like autonomous guided vehicles, warehouse automation, automated assembly lines & condition-based monitoring,
Many companies have started developing 5G enabled smart factory technologies.
Mitsubishi Electric has been experimenting with 5G networks to strengthen human-machine interfaces for manufacturing. At its 5g connected plant in Texas, Ericsson has also been working on 5G infrastructure equipment. The first millimeter-wave Street Macros base stations were gathered at the factory initially this year. In South Korea, many big telecommunications operators including KT Corp, SK Telecom & LG Uplus Corp have evolved 5G enabled smart factory solutions to help SMEs in magnifying their manufacturing output & reducing costs.
“How will you make certain that you can modify your processes & people when they have been working for so many years, and give them tools involve them?” In this section, we take envision from some interviews to expose the key elements of smart factory transformations.
The Familiar Themes: Change Management in Smart Factory Transformations-
Successful smart factory transformation leaders know that it is a need to consider user-oriented perspectives to achieve business objectives when designing smart factories. Take some time to understand how individual roles to work & what tools they need, involving a “human-centered approach to understand what [the user’s] trouble points are & making sure we understand how they need to use information, why they need to inspect it, what they need to look for & how they need to take action on it.”.
By concentrating on the user first, you can find issues to address & behaviors that need to change, and only then think about how technology can support those efforts. The purpose is to ask not only “How do we make the technology sticky?” but also, “How do we make the application pertinent & valuable to the user?” The human element is the analytical ingredient which if you don’t get right can lead the projects to that point where it is an investment failure.”
Change champions can provide support at a leadership transformation level as well as on the ground to eliminate barriers, achieve organizational buy-in & define the business case for smart factories. Leaders know the importance of executive-level sponsorship as these initiatives often need wide investments of resources—whether time, people, financials, or assets. They speak regularly about the need for a project sponsor to lead projects forward.
More than that, support from every side is important when the rubber meets the road. Senior leaders in operations, strategy, supply chain & other functions can think strategically about how the smart factory transformation can lead value more widely at the network level. Those on the ground— manufacturing operators, plant managers, technicians, plant engineers & others—can drive change & results on the shop floor. As one individual noticed, “If any factory wants to introduce Industry 4.0 or a smart factory. It has to be a top-down, bottom-up approach. It must be both sides. That would be the greatest key to success.”
Diversity reproduces vision. Skill sets include information technology (IT), engineering, production, supply chain, user interface designers, master data management, analytics, finance, digital marketing & human resources, among others.
Cross-functional teams decrease the probability that important controls, processes & cultural elements were missed during the transformation effort—and can help ensure that the smart factory could provide value more widely. Research shows that cross-functional teaming has resulted in greater organizational innovation & growth. This means transformation leaders should take pains to make sure that the right skills are implemented at the right time, and that a diverse mindset can inform the complete approach.
To successfully deploy the smart factory, organizations should assume how to bring skills into the company, and how to develop skills for the people already there. Adding & growing skills is one of the biggest issues faced by organizations; in a recent global quantitative survey, just 14 % of C-level manufacturing leaders strongly agreed that their organizations currently possess the skills they will need in the future during lean transformation.
As smart factories hold advanced technologies, roles within the facility will call for new & different skills than had been needed previously, making it challenging to upskill and train. Beyond developing in-house capabilities, other approaches can also help sustain smart factory systems and technologies, such as collaborating with universities and other schools to build a pipeline of talent, implementing alternative talent models, and gripping the skills of ecosystem partners.
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The “Smart Factory–specific” Themes
It all starts with connectivity. It would be fair enough to say the smart factory and its resulting value normally hook on the ability to connect assets, people, processes & devices. This is not a small task. In wider research: 33% of smart factory leaders in the Deloitte-MAPI survey identified a lack of necessary IT infrastructure as a significant hindrance to smart factory initiatives. If an application or process can’t connect to the network to share & access information, it will fail no matter how well thought out it is.
Yet that connectivity provides multiple opportunities to reform how value is captured within the smart factory, and beyond it. Leaders can think not only about how to connect & collect data from processes & assets within the four walls of the factory, but also plan for how that connectivity can scale, and how data can be shared throughout networks & ecosystems in leadership transformation.
The implementation of smart factory technologies across the network will favorably demand a carefully planned strategy, using certified advisers, for developing a flexible digital infrastructure, while also containing all demands of each environment.
The diversity of sensors, machinery& other devices that exist on the shop floor is important to consider. You must be able to connect it & make it all work together. Smart factory practitioners interviewed as part of the research:
27% of respondents in the Deloitte-MAPI survey identified difficulties in developing a wider combination between IT and OT as a big challenge to smart factory initiatives. Some OT leaders & teams may also experience discomfort with agile sprint methods, which are meant to enable change swiftly. IT organizations have historically made large investments in qualifying & securing technology assets. Obtaining balance among competing priorities, and understanding across different professional cultures can make all the difference.
How can companies shift from lessons learned from smart factory transformations toward outcomes, and the methods smart factory capabilities make processes & organizations better? We explore some of these opportunities.
The important thing is connectivity & the need to connect assets and data across a wide range of platforms, systems & data structures. Once its assets are connected, they free a flood of information to be unraveled, translated & acted upon. The addition of new data enables organizations to see things that were always present, but previously impossible to observe.
By combining their current systems digitally & leveraging the data, companies can evolve and enhance areas such as lean manufacturing & workforce management exploring new ways to lead higher productivity, optimize operations & leverage talent in organization transformation.
It is an amalgam of humans & technology, including IT and OT, that makes a smart factory smart. Applications of physical technologies such as robotics have led to major switches in the smart facility, while IoT & cloud, and edge computing have led to the creation and association of data and information. AI can be deployed in a variety of ways, for example, robots capable of navigating as well as capable of imitating human vision & hearing for quality sensing and asset health prediction.
It can lead to predictive maintenance; dynamically route inputs and analyze, sense, and energetically respond to circumstances. AI can also be used to observe & optimize the performance of products or processes through the deployment of digital twins & digital threads. Digital twins allow companies to capture value by detecting potential issues sooner. Likewise, AI can be installed in the digital thread, creating a digital record of the life cycle of products themselves. Some leaders reported double-digit % improvements in machine utilization, production processes, and throughput by installing AI-driven capabilities.
Scaling smart factory capabilities & processes throughout the enterprise’s network allows the organization to recognize smart factory value on an even wider scale. In one example, a consumer products manufacturer produced double-digit returns on investment in advanced analytics & AI to optimize input purchasing decisions across its manufacturing network.
In another, a biopharma company predicted a net value of US$50–75 million year over year in expense reduction. The inflow of data & information can lead to enhanced operations not just in one facility, but throughout the network & even the wider economy.
Technology-driven change in almost any organization appears inevitable. Industry 4.0 technologies permit us to connect all the stakeholders, including the product, into a resource for feasibility and future development in the penetrating society.