Industry 5.0.pptx

The presentation considers where we are today in manufacturing and how we may come to be a futuristic manufacturing nation and your potential role in fulfilling the dream.

1. The Journey towards Industry 4.0 and beyond Creating Value for People, Society and the Environment Alasdair Gilchrist

2. A Futuristic Industry Presentation The presentation considers where we are today and how we may come to be a futuristic manufacturing nation and your potential role in fulfilling the dream. 2

3. The Path to Industry 4.0 and beyond Roadmap to Industry 4.0 and beyond … The Connected World (where we want to be) Defining the prerequisite - Industry 4.0 Considering the effects of Industry 4.0 Defining the Industry 5.0 evolution What are the key objectives of Industry 5.0 What are the Technology enablers What are the Business Drivers and Potential What are the Economical and Business Benefits (use cases) Industry 5.0 – Powered by Industry 4.0 Jumping the gap from Industry IR3.0 to IR5.0 Building an Industry 5.0 Reference Architecture 3

4. The Connected World 4 The Internet of Things, Big Data and Cyberphysical systems play a vital role in our modern connected world. Where they will combine and collaborate so effectively is believed to be at the heart of the 4 th Industrial Revolution instigated by Industry 4.0. IoT is ubiquitous it provides the connectivity Big Data is key in all of these domains Cyberphysical systems live here!

5. IoT, Big Data & Cyberphysical systems What are the big 3 tech enablers in the connected World? IoT – is the interconnectivity of smart devices in an industrial context this means a networking of sensors, actuators and controllers with human operated devices. Big Data – the 5Vs but larger, more complex data sets, originating from new data sources. These data sets are so voluminous that traditional data processing software just can't manage them. Cyberphysical systems - these are systems of collaborating computer controlled machines which are connected with their surrounding physical world and its processes, providing and using, at the same time, data-accessing and data-processing services from the IoT. Where are they used and what did they lead to? 5

6. The Industrial Revolution The Industrial Revolution, in modern history is  the process of change from an agrarian and handicraft economy to one dominated by industry and machine manufacturing . These technological changes introduced novel ways of working and living and fundamentally transformed society. (Britannica) So we could say that the emergence of big data, the IoT and social media may lead to the 4 th Industrial Revolution but there is scant evidence of this. Instead these terms are simply a construct of the fertile minds of consultants and their labels assigned by the technology industry – historically, there is only – The Industrial Revolution. The most important aspects of the Industrial Revolution are simply condensed as; (1) the migration from agriculture to factories, 2) invention of machines to do the work of hand tools, (3) the use of steam and later of other kinds of power, and (4) the adoption of the factory system. 6

7. ‘ Industrie 4.0’: The Connected Factory The Original “ Industrie 4.0” Initiative encompassed the digitalization of production processes based on devices autonomously communicating with each other along the value chain to create the connected factory. ( ( German Ministry of Education and Research 2011  ) Smart factories are  an opportunity to create new forms of efficiency and flexibility by connecting different processes, information streams and stakeholders (frontline workers, planners, etc.)   in a streamlined fashion . (EU Council 2014) Technologies such as Wireless Sensor Networks (WSN) enable machine-to-machine communication (M2M), which interact and “talk” to each other in a digital way and Cyber-Physical Systems (CPS), which merge the physical world with the digital world. Big Data and advanced analytics surfaces patterns hidden within the data, which in return can be translated into new business opportunities for organizations’. Big Data, that these sensors generate, enables IoT to create value through real-time data analysis and deliver improved decision-making for organizations. Industry 4.0 aimed for data-driven factories. 7

8. The History of Industry 4.0 The first official use of the label, Industrie 4.0, was coined in Germany around 2011 to signify the concept of h eralding a futuristic 4 th Industrial Revolution, as a strategic initiative. It was introduced by the German government with the goals to: 1. Identify various trends that were taking place 2. Encourage projects for the digitalization and introduction of high level technology in manufacturing. In the following years (from 2011 to after 2014), companies and governments outside of Germany began to step in. The most important move came when the European Commission established a priority: It institutionalized Industry 4.0 as a pan-European policy and set a target for the industrial sector to hit 20% of value add to GDP within the European economy up to 2020 thus increasing productivity, competitiveness and overall enterprises added value. To achieve this target, government initiatives, dissemination efforts, specialized financing policies and tools were established. The EU Council settled on the name Industry 4.0 in homage to Germany’s huge contribution to the new initiative. Industry 4.0 is based on the integration of the company’s value chain (suppliers, partners and customers), business and manufacturing processes as well as the adoption of ICT (both hardware and software) to current industrial production systems. Industry 4.0 is as much about evolving business processes as it is system integration and even emerging technology - 8

9. Defining Industry 4.0 What is Industry 4.0? “ profound transformation of business models by enabling the fusion of virtual and real words and the application of digitization, automation, and robotics in manufacturing ” “a name for the current trend of automation and data exchange in manufacturing technologies, including cyber-physical systems, the Internet of things, cloud computing and cognitive computing and creating the smart factory”.   “Industry 4.0 is the transformation of industrial manufacturing and production systems by introducing new technologies.” What it is not: “Industry 4.0 is the 4 th industrial revolution” Industry 4.0 is poorly defined with some who should know better simply stating it is a synonym for the 4 th Industrial Revolution! Ask yourself what has been the effect on society and our lives since 2010 that could make us claim we are living through the 4 th industrial Revolution? Since its initial German conceptualization in 2011, both the technological landscape and the understanding of the Industry 4.0 have evolved significantly leading to several ambiguities. In parallel, similar concepts often used i ncorrectly as synonyms − such as “smart manufacturing”, “digital transformation”, and “fourth industrial revolution” − have increased the sense of confusion around the scope and characteristics of the phenomenon. 9

10. Industry 4.0 vs the 4 th Industrial Revolution 10

11. Industry 4.0 is a Roadmap A common erroneous practice especially in the US is to use the term Industry 4.0 synonymously with the Fourth Industrial Revolution (something which has yet to manifest itself and perhaps may never happen) - making the term Industry 4.0 effectively meaningless! In Fact: The term 'Industry 4.0' refers to the notion that it may bring about an expected upcoming fourth industrial revolution  [ Kagermann 2013]; In reality: Industry 4.0 is a detailed published and institutionalized framework for building advanced and futuristic manufacturing processes using emerging technologies to create customer-centric, highly customizable products via data driven solutions. - Its not just interfacing machine-tools with the Operations Backbone as System Integrators will have you believe. Industry 4.0 spans the entire product life cycle and supply chain—  design, sales, inventory, scheduling, quality, engineering, and customer and field service . For Industry 4.0 to be workable it must be implemented across the entire organization both vertically ( top C-suite to bottom – plant floor of the organization) and horizontally (logistics, warehousing, transportation, etc.) including the external supply chain! This is incredible difficult to do if you do not have a starting place such as a common framework to work upon hence why Industry 4.0 and all its international variants – Made in China, Thailand 4.0, etc. have come about. 11 If you don’t know where you’re going, any road will get you there. –  Lewis Carroll

12. Global Industry 4.0 Initiatives Top Industry 4.0 Initiatives Around The World China: Made in China 2025 Europe: Industry 4.0 Japan: Society 5.0 (Japan’s term for Industry 4.0 Initiative) India: India Industry 4.0 And many others … Eventually the United States: Industrial Internet Initiatives (formerly the IIoT )   Why do we need precision on the definition of an Industry 4.0 Initiative? Industry 4.0 initiatives and the ensuing plans are public statements, which ideally identify and summarise all the critical points that stakeholders need to implement a program successfully. That means describing objectives and goals and getting the stakeholders’ seal of approval on: High-level vision that shapes the overall plan  — The nation’s overriding outlook about manufacturing technology and its role in transforming the economy, for example. What’s most important to those stakeholders  — Initiatives set goals and prioritises the industry’s future approaches to achieving them. Methods used to achieve goals  — Clearly defined goals help all stakeholders envision the future but presenting the methodology helps guide them through the entire process. Fair representation  — Any good initiative should assign roles to government, business, and academic stakeholders. 12

13. The People Party in the Streets A prerequisite of an Industrial revolution is that it must have had a significant impact on society So why did Industry 4.0 stall and the much heralded 4 th Industrial Revolution not manifest itself globally? Where is the 4th Industrial Revolution? In my lifetime I have witnessed the introduction of the home PC, the Internet, Social Media and probably the most pervasive technology of all, the mobile phone. But strangely connecting machine-tools to a Operations Backbone didn’t have that same effect on society. Did I sleep in and miss this? Of course this does not mean the objectives of Industry 4.0 were not valid and a roadmap for a futuristic vision for manufacturing not feasible because it certainly was.   13

14. Principles of Industry 4.0 The 4 Design Principles of Industry 4.0 1. Interoperability The ability of machines, devices, sensors, and people to connect and communicate with each other via the Internet of Things (IoT) and then make use of that information to function and execute improvements. The next step within interoperability is to integrate this data with your LMS, MES, ERP, or other smart factory solution and analyze the data in real-time. This principle dwells on the technology's ability to provide enhanced information for future decision-making. 2. Information Transparency Information Transparency is an essential design principle of Industry 4.0 because the information is easy to access, providing a fast and powerful method to extrapolate knowledge, which helps you monitor processes on the shop floor and allows management to instantly adjust and optimize for higher efficiency. 3. Technical Assistance Technical assistance is the ability of cyber-physical systems to support humans by aggregating and visualizing information comprehensibly so that making informed decisions and solving urgent problems at short notice is simple and effective. 4. Decentralization of Decisions The decentralization of decisions stems from the ability of cyber-physical systems to make choices independent of people. Naturally, this leads to machines and systems that can take action and perform their tasks with little to no human intervention, making factors like problem-solving, calibration, adjustments, and notifications a fast and autonomous system. Only in the case of exceptions, interferences, or conflicting goals are tasks delegated to a higher level. A decentralized system is also highly adaptable and scalable which determines how efficiently you can respond to industry changes. 14

15. Business Drivers of Industry 4.0 15 Industry 4.0 benefits manufacturing and industrial processes that have resulted in huge improvements in operational efficiency, lower costs and higher profits from organizations capable of implementing the roadmap. It achieves this from a business perspective by: Changing the emphasis from products to a service - buy light not light bulbs Addressing the service paradigm – extract value through data and business intelligence Delivering value from data as a product – value added service Creates new services for profit and business agility – X as a Service Designs new data collection and simulation models to reduce operational costs Encourages fast prototyping and modeling to lower time to market Collects data from everywhere for better informed decision making Data analysis drive logistics and supply chain efficiency (lower inventory, less waste, improved time to profit)

16. Goals of Industry 4.0 16 The key objective of Industry 4.0 is to be faster, more efficient, and customer-centric an d to discover new business opportunities and models. 

17. Why Industry 4.0 - The Economic Reality 17 Despite a common misconception Manufacturing all over the world is in decline

18. The Status Quo of Manufacturing 18

19. Manufacturing Outputs - US 19 US Manufacturing Output The top graph shows clear improvement in order-book revenues since 2010 - 2021 The lower graph shows consistent decline relative to other US industries that contribute to GDP This is due to sharp rise in inflation since 2010 ( 1Dollar in 2010 how equals 1.30 in 2022 approx. 30% rise) so the figures don’t look so clever now.

20. Manufacturing Output EU 20 The EU also shows steady decline since 2016 2020 shows steep loss of orderbook revenue due to Covid-19 pandemic EU’s ambitious goals for Industry 4.0 fall well short of that target of 20%

21. EU to US comparison 21

22. Consumer Markets 22

23. Likely Impact of Industry 4.0 Consultants love to wax lyrical regards Boeing, Airbus and T esla but w hat consultants often ignore is that Manufacturing isn’t just for large businesses. In fact,  98.6%  of all manufacturing companies in the United States are small businesses and the majority of them have fewer than 20 employees. When looking at the relationship between manufacturing companies and how many employees they have, the vast majority of manufacturers have very few employees. According to the Small Business Administration analysis of the US manufacturing segment: 355,467 manufacturing companies have no employees 187,862 manufacturing companies have between 1-20 employees 60,099 manufacturing companies have between 21-499 employees 3,813 manufacturing companies have more than 500 employees Overall, 75.3% of manufacturing companies have  fewer than 20 employees . In the European Union, in the manufacturing sector, 99.2% of EU-27 companies are SMEs, accounting for 59% of employees, 45% of VA and 39% of sales. ‘Manufacturing’ is the most important sector for medium-sized SMEs, which are companies that have fewer than 50 employees and a turnover less that 10 million Euro. The majority of these businesses simply do not have the financial resources or core competencies to implement Industry 4.0 or to even attract new employees with the education and skillsets to let them digitalize their existing processes. In order to transform into data driven organizations the vast amount of manufactures will not be able without government assistance and a framework on which to build their digital strategy move to become manufactures of the future. Hence the need for an institutional global standard Industry 4.0 policy. Possibly supported through certification and accreditation through a global awards body. 23

24. Industry 4.0 in the Post-covid EU What is the effect of the industrial revolution 4.0 to society? Industry 4.0 coupled with machine learning and artificial intelligence, will substantially change conditions for workers: “ Many jobs will disappear while we will gain a lot of new jobs, and many repetitive tasks will shift from manual labour to automation . It will have a big impact.” It certainly has but what has been its revolutionary effect on society! According to the European Commission’s Spring forecast, the Covid crisis has accelerated and intensified existing structural changes due to decarbonisation and digitalisation in our sectors. We are witnessing massive and simultaneous sectoral restructuring across our economies. During the last few months In the automotive industry, over 100,000 job losses have been announced. A similar situation is happening in aerospace, where we see a lot of European cooperation. Airbus, the poster child for European industrial cooperation, currently has 15,000 jobs at stake. Meanwhile in basic metals, especially the steel sector, we risk losing half of Europe’s steel capacity and thousands of jobs through this crisis without urgent targeted action. Since 2015 to 2022 the Value Added to GDP coming from manufacturing has slipped from 15% to around 13.5%. 24

25. Core Industry 4.0 Technologies Machine-2-Machine operation (System Integration) Cyber Physical Machines (Interoperability of data, robots, and computers) Intelligent systems – self learning machines, self calibrating processes with fix-before-break operation) Intelligent products – smart products that know what they are, how they are to be made, and their history Deterministic networks – essential for real-time manufacturing Deterministic feedback and control Big Data collection (Cloud & Edge deployments) Digital Twins (clones of machines or processes used for analysis, modeling, simulation and testing) Real time and batch analysis – streaming and in-memory analytics to enhance process control and gain insights into operational efficiencies 25 What is the future, what is the strategy? The future will be based upon manufacturers devising their own digital strategy built upon the Industry 4.0 framework and utilizing some emerging technologies

26. Technology Enablers of Industry 4.0 Some of the key technologies that enable Industrial 4.0 are very new but others have been around for a long time, it’s their current state of maturity and our ability to interconnect them that enables Industry 4.0 today. Some key technologies are: Internet of Things Cyber Physical Systems Cloud – provides global reach and near infinite resources (newish) Advanced Robotics –high speed, accurate and tireless Additive Manufacturing (3D Printing) – P.o.C , remote assembly Simulation – Digital Twins Big Data – provides for storage and data handling methods at vast scale Machine Learning - provides the advanced algorithms we need to make sense of machine-tool data Artificial Intelligence – delivers the means for predictive and advanced analysis of machine-tool data 26

27. Industry 4.0 Levers and Value Drivers 27 This is an Industry 4.0 framework – It’s a structure that allows you to consider how to build your digital Strategy. It also determines how to extract value so its not just some ambiguous term that relates to perhaps a future event or even a preferred happenstance.

28. The Economical and Social Impacts 28 I4 helps governments foster an open, flexible, knowledge- and skills-based economy, I4 promotes trade outside traditional trading blocs, improves efficiency and effectiveness of health and social care systems  I4 offers a “first mover” advantage in manufacturing for those that make best use of emerging technologies. Industry 4.0 provides other tangible benefits and impacts policy-makers thinking such as: Industry 4.0 will have a strong impact along whole value chains and provide a set of new opportunities regarding business models, production technology, creation of new jobs, work organization, and workflows. Undoubtedly there will be jobs lost! I4 provides the means to reverse the decline in manufacturing in many countries and bolster value add to GDP There will be a net gain in jobs eventually

29. The Real Economic and Social Factors 29 While Industry 4.0 holds great promise for the economy and society, Governments need to be aware that change will be inevitable and action required to address: (GDP, level of investment, consumption, employment, trade, inflation, and other macro factors) Computer models suggest that 47 percent of current U.K. jobs will be at risk, which presents a massive social challenge. What role should government play in managing the inevitable turbulence the 4IR could bring? How do policy-makers protect employment, regulation and taxation of technology? A guaranteed basic income for all? Yet, still be Open for Business One central concern is the impact of Industry 4.0 on employment and jobs…

30. Adoption of Industry 4.0 30 The key reason organizations adopt Industry 4.0 are not always aligned to all of the objectives. In this survey by Jitterbug the key reason are biased towards Processes Improvement with little interest it seems in the Strategic or Organizational goals. Industry 4.0 has focused less on the original principles of social fairness and sustainability, and more on efficiency and flexibility of production. The concept of Industry 5.0 provides a different approach and aims to Reimagine Industry 4.0 with a focus on Humans, Society and the Environment.

31. Introducing the Industry 5.0 Evolution Industry 5.0 complements and extends Industry 4.0. It reaffirms the environmental and social factors and not just economic or technological, by framing how industry and emerging societal trends and needs can co-exist. By developing innovative technologies in a human-centric way, Industry 5.0 can support and empower, rather than replace workers; by doing so we increase industries’ resilience and make it more sustainable. Greening the economy will require that industry takes a strong leadership role. Industry 5.0’s environmental goals can be achieved by incorporating new technologies and rethinking the production processes in respect to the environmental impacts. 31

32. Industry 5.0 Powered by Industry 4.0 32 Industry 5.0 is an evolution of I4 as it needs the underlying architecture, tenets and principles to provide it context hence the concept of standing on the shoulders of I4. Industry 4.0 provides: An inter-connected world driven by real-time data Data is collected from everything and everywhere Data drives decision making, automation and controls processes Automated processes and integrated value chains reduce costs and increase profit Smart Factories using interconnected cyberphysical systems to produce smart products For Business - Industry 4.0 delivers the potential for growth, revenue and capturing greater market share For Governments Industry 4.0 adds to a country’s industrial contribution to GDP Industry has the potential to re-industrialize through the on-shoring of manufacturing So what does Industry 5.0 bring to the table?

33. The Goals of Industry 5.0 33 Industries have a responsibility in providing solutions to challenges for society including the preservation of resources, climate change and social stability. Hence, Industry 5.0 has goals beyond just process efficiency and productivity so it reinforces the role and the contribution of industry to society. Therefore, I5.0 takes a predominantly human centric stance by placing the worker at the centre of the production process and uses emerging technologies to provide prosperity while respecting the production limits of the planet. As such, Industry 5.0 brings benefits for industry, for workers and for society as: It empowers workers, as well as addresses the evolving skills and training needs of employees. It increases the competitiveness of industry and helps attract the best talents. It is good for our planet as it favours circular production models and supports technologies that make use of natural resources more efficiently. It revisits existing value chains and energy consumption practices, which can also make industries more resilient against external shocks, such as the Covid-19 crisis.

34. The Industry 5.0 Model 34 Adopting Industry 4.0 alone as a purely profit-driven initiative is increasingly untenable. In a globalized world, a narrow focus on profit fails to account correctly for environmental and societal costs and benefits. For industry 5.0 to address any of I4.0’s shortcomings it must revisit and reaffirm the human, environmental and societal factors. This includes responsible innovation, that increases prosperity for all involved: investors, workers, consumers, society, and the environment.

35. Industry 5.0 - The Circular Economy In a typical linear economy, we extract raw materials from the Earth, make products from them, and eventually throw them away as waste. In a circular economy the goal is to prevent waste being produced in the first place. The circular economy is based on three principles, driven by design: Eliminate waste and pollution Circulate products and materials (at their highest value) Regenerate nature It is underpinned by a transition to renewable energy and materials. A circular economy decouples economic activity from the consumption of finite resources. It is a resilient system that is good for business, people and the environment. This process is not Recycling as that begins at the end - the ‘get rid’ stage of a product’s lifecycle. The circular economy, however starts at the beginning with a goal to prevent waste and pollution from being created in the first place. In the face of our current environmental challenges, recycling won’t be enough to overcome the sheer amount of waste we produce. 35

36. Industry 5.0 technologies Industry 5.0 identifies the following six enabling technologies; 1 - Individualized human-machine interaction technologies that interconnect and combine the strengths of humans and machines. 2 - Bio-inspired technologies and smart materials that allow materials with embedded sensors and enhanced features while being recyclable. 3 - Digital Twin simulation to model entire systems. 4 - Data transmission, storage, and analysis technologies that are able to handle data and system interoperability. 5 - Artificial Intelligence to detect, for example, causalities in complex, dynamic systems, leading to actionable intelligence. 6 - Technologies for energy efficiency, renewables, storage and autonomy 36

37. I5.0 Enabling Technologies 37 Bio-inspired technologies and Smart materials Recyclable Lightweight Self-healing/Self-repairing Human Machine Interaction Multi-lingual speech recognition Tracking of employees’ physical or mental stress Collaborative robots - Cobots Augmented reality Enhanced human physical capabilities – exoskeletons, etc. Enhanced cognitive human capabilities – decision support systems, Digital Twins Virtual simulation of products and processes Multi-scale simulation for modelling products and processes Simulation of impact on environment and society

38. Industry 5.0 – Enabling Technologies Bio-inspired technologies Smart Materials Renewable energies 5G Communications Advanced Wi-Fi Advanced Cyber Physical Systems Smart Additive Manufacturing (SAM) Banking 4.0 Cryptocurrency Advanced Blockchains AI Advanced Algorithms Machine Learning 38

39. Bio-inspired Technology Biomimetic devices are  designed and produced by materials, structures, and systems that are modelled on biological entities and processes .  More specifically, biomimetics is  a creative form of technology that uses or imitates nature to improve human lives Sometimes the best solution to a problem isn’t always the most complex, and, similarly, the best answer isn’t always a new one. While us humans may just be getting our feet wet (relatively speaking) with ingenuity, the animal kingdom has millennia of evolutionary trial-and-error to learn from. Biomimicry, as it's called, is a method for creating solutions to human challenges by emulating designs and ideas found in nature. It's used everywhere:  buildings, vehicles, and even materials 39

40. Smart Materials Smart materials are designed to respond in a controllable and reversible way by modifying some of their properties as a result of external stimuli. They can b e manipulated by mechanical stress an electric or magnetic field or a certain temperature, among others. Synthetic spider web.  This material is not only five times stronger than steel, but also has great elasticity. Its potential uses include: bulletproof clothing, artificial skin for burns or waterproof adhesives. Shrilk .  Its main component is chitin, a carbohydrate found in krill shells. It was created by researchers from Harvard University and is considered the ideal substitute for plastic — since its decomposition time is only two weeks and it also works as a stimulant for plant growth. Graphene.  Its potential uses are almost unlimited:  batteries  with more autonomy,  cheaper photovoltaic solar cells  faster computers, flexible electronic devices, more resistant buildings, bionic limbs, etc. All this is possible thanks to their multiple properties. 40

41. Renewable Energy The global energy system today is still largely dominated by fossil fuels. Coal, oil, and natural gas account for about 84% of primary energy, with about 12% from renewable energy and 4% from nuclear in 2019. Renewable energy  is energy that has been derived from earth’s natural resources that are not finite or exhaustible, such as wind and sunlight.  Solar - sunlight is functionally endless. With the technology to harvest it, there is a limitless supply of solar energy, meaning it could render fossil fuels obsolete. Wind - Wind energy is also limitless and a clean energy source Hydroelectric - is very versatile and can be generated using both turbines and dams on large or small rivers Geothermal -  is naturally produced underground heat released as steam and therefore does not run a risk of depleting (on a human timescale) Ocean - can produce two types of energy: thermal and mechanical Hydrogen – when separated from another element it can be used for both fuel and electricity. Biomass - The use of biomass in energy production creates carbon dioxide that is put into the air, but the regeneration of plants consumes the same amount of carbon dioxide, which is said to create a balanced atmosphere.  41

42. Private 5G Networks 42 A private network is an enterprise-dedicated network that provides communication connections to people or things belonging to a specific enterprise and provides specific services necessary for the business of the enterprise. The enterprise operates its own network and uses it exclusively. Unlike public networks, only allowed people and devices can access this network, and data generated within the enterprise is processed locally only within the enterprise's dedicated network, ensuring high security and data privacy.

43. Wireless Connectivity – 5G The introduction of 5G into the manufacturing workspace will be potentially huge for Industry 4.0. 5G itself is a vast game-changer as it bring huge capacity, bandwidth, low-power consumption and very low latency. Up to 10Gbps data rate - > 10 to 100x speed improvement over 4G and 4.5G networks 1-millisecond latency 1000x bandwidth per unit area Up to 100x number of connected devices per unit area (compared with 4G LTE) 99.999% availability 100% coverage 90% reduction in network energy usage Up to 10-year battery life for low power IoT device Private 5G Networks – Manufacturers can run their own private 5G networks to provide guaranteed spectrum, coverage and security. 43

44. Private 5G Deployment Models Two basic types of 5G Private Networks: Dedicated, on-premises networks.  An enterprise deploys a dedicated, on-premises network (radio access network and core) that is purpose-built for the sole use of a single enterprise. The enterprise deploys its own edge computing assets. Hybrid networks.  The network is based on a combination of public mobile network components and dedicated on-premises elements. For example, a slice of the public radio network may be combined with a dedicated on-premises core network. Spectrum.  There are four main types of spectrum, Industrial spectrum. Shared spectrum.   Public spectrum.  This approach uses a mobile network operator’s public network spectrum to support enterprises. Operators lease their spectrum to enterprises for a fee. Unlicensed spectrum.  Unlicensed spectrum bands are designated by regulators, are non-exclusive and free-to-use, but are making 6GHz license-exempt spectrum available for 5G and Wi-Fi use in some countries (such as the USA). 44

45. Private 5G Networks: Organizations Why are organizations using private LTE/5G networks? The demand-side factors for private LTE/5G networks include the following: Operational efficiency.  The demand for private LTE/5G networks is growing because large organizations' digital transformation programs are underway. Enterprises are in the process of digitizing their data and using it to drive processes and create new digital products and services. IT and OT convergence.  The convergence of IT and OT is also a key consideration. Ultimately, the need for high-bandwidth, low-latency networks to support increased automation will grow as enterprise data processing requirements increase. Data privacy.  Enterprises deploy private networks because data privacy is a key concern. They require more control and visibility of their data. Cable substitution.  Enterprises deploy private LTE/5G networks to support new applications as a more cost-effective alternative to extending their fixed networks. Replacing legacy networks.  Existing networks such as TETRA are reaching the end of their life and cellular technologies offer viable alternatives. Wi-Fi limitations.  Enterprises have used Wi-Fi successfully but have found that it has limitations in terms of supporting mobility and/or other factors such as reliability. 45

46. Advanced Cyber Physical Systems Robots were once considered fit only for dangerous, dirty and dull work. Today the typical applications of industrial robots include welding, painting, ironing, assembly, pick and place, palletizing, product inspection, and testing, all accomplished with high endurance, speed, and precision. Three types of robots: Industrial arm robots: 6-axis arms used for repetitive or potentially dangerous tasks SCARA robots Delta or Spider robots Collaborative robots: designed to safely work alongside humans to perform the dull repetitive tasks Software robots: used for the automation of reading, processing and completing forms, data entry with decision-tree intelligence. 46

47. Industrial Robots Industrial robots are typically large, fixed equipment designed for high-volume, extremely high-accuracy, and high-speed production. A serial robot arm can be described as a chain of links that are moved by joints which are actuated by motors. An end-effector, also called a robot hand, can be attached to the end of the chain. As other robotic mechanisms, robot arms are typically classified in terms of the number of degrees of freedom. Typical industrial use cases: Assembly and Handling Welding and Cutting Packaging and Palletizing Painting and Dispensing Industrial robots can present safety risks to human workers, so they usually require safety measures such as a cage to keep humans out of the robot’s work envelope . 47

48. 6-axis Robotic Arms The number of axes corresponds to the number of ‘joints’ – or points – along the arm where it can bend or twist. Load capacities for industrial 6-Axis arms have the largest range, anywhere from small 3 kg units to monster 1000 kg systems. Strengths: Very flexible and can mimic the motion of a human arm. Very good at reaching in and around objects. Weaknesses: Can be more compliant and a little slower than other configurations due to the nature of the design. Number of Axes: Six, usually, but there is a new “snake” variant robot that adds a 7th axis that gives the system an even better ability to reach in and around obstacles. Typical Load Capacities: 3-600 kg 48

49. SCARA Robots The SCARA or Selective Compliant Assembly Robot Arm is your high speed work horse, but they aren’t limited to assembly or pick-and-place applications such as building mobile phones. They can be very useful in applications such as dispensing, where you need to precisely follow a path at constant speeds while dispensing things like adhesives. Strengths: High Speed and very rigid with very good repeatability. Weakness: Available work area can be limited and not suited for manipulating objects in a vertical plane. Number of Axes: Three or Four – the fourth is determined if you need a wrist or twist axis about the Z-Axis (vertical). Typical Load Capacities: 1-20 kg 49

50. Delta Robots Also referred to as “Spider Robots”, Delta Robots are one of the latest entrants into the main stream industrial robot world. They are best suited for super high speed pick-and-place applications with relatively light loads. Added vision technologies allow Deltas to distinguish and select different size, colour, or shape options and pick and place based on a programmed pattern. Strengths: Very High Speed. Weakness: Available work area can be limited in the vertical plane at the extents of its reach and it’s not suited for manipulating objects in a vertical plane. Due to the duty cycle requirements, there can be significant mechanical maintenance required. Number of Axes: Three or Four – the fourth is determined if you need a wrist or twist axis. Typical Load Capacities: 1-3 kg 50

51. Collaborative Robots 51 Cobots are ideal for manufacturers with low-volume, high-mix production or who need to safely automate processes alongside human workers. That might include automating a repetitive task and handing a part off to a human for inspection or to complete a complex decision-based assembly process Cobots typically have lower upfront costs and are easy to program with no previous experience, so they offer fast ROI. They are small and lightweight enough that they can be easily moved and redeployed to automate different processes throughout a manufacturing facility. Collaborative Robots are affordable, safe, highly adaptable, easily programed or hand trained and have interchangeable end of arm tooling ( EoAT ). This makes them best suited for working along side humans in a shared workspace or for providing assistance to an industrial robot in a cage.

52. Autonomous Mobile Robots Collaborative robots have been an important development in the robotics industry - the first automation technology that allows safe operation directly alongside human workers. Autonomous Mobile Robots Mobile robots are currently seen as the work-horses of ‘Industry 4.0' and their adoption rate into production processes is expected to increase in the next few years. 52

53. Robotic Exoskeletons 53 Exoskeletons are increasingly being used by manufacturing workers. The primary benefit of the robotic exoskeleton is to prevent injury due to muscle fatigue. Research has shown that when using this technology muscle activity in the back, shoulder and knees drops by 50%. If muscle activities drop that means the risk of muscle injury is less. Workers are more productive, Insurance costs are lower, Less workdays lost to injury. There's less cost and more productivity. SuitX's are now being tested by car manufacturers General Motors and Fiat. Labour-intensive industries like manufacturing and agriculture have always depended on a workforce that must endure a certain level of physical exhaustion and risk.

54. Teaching Robots in the Virtual World In the IoT robots are cyberphysical systems as they straddle the real and the virtual worlds. They learn through interacting with the real world and through ML and AI enhanced big data in the virtual world. As industrial robotics become more and more advanced and traditional factories are upgraded to smart factories, the amount of work and expertise that goes into training these robotics arms will increase commensurately. Teach Pendant: an operator using a teaching pendant can slow down the equipment so that they can plot the movements of the robot’s arm to accommodate the change in procedure. Programming by Demonstration: as with the teach pendant, the operator has the ability to “show” the robot, with a high degree of precision, a series of new movements and store that information into the robot’s computer. Offline Simulation: A danger to teaching the robot is the downtime so offline simulation is an attractive alternative. The movements of travel can be analyzed and plotted using a computer and the resulting code downloaded to the robot. Machine Learning: have an operator show the robot how to perform a particular task and then allow the robot to analyze that information to determine the most efficient sequence of motions that need to be completed in order to replicate the task. As the robot learns the task, it has the opportunity to discover new ways to improve the way in which the task is performed. 54

55. Robot Process Automation RPA: “RPA tools are the ‘Babel fish’ of the technology world as they can interact with any type of system.” The ideal task for RPA is predictable and repetitive. RPA is not new – it shares its origins with rules engines and other basic business and workflow automation tools. However, RPA developed to solve a specific problem: systems that were not, and could not easily be, connected. RPA sets out to free human operators from repetitive tasks, and to boost efficiency and accuracy. It is especially useful where data needs to move between disconnected applications. When teamed with ML, AI and Sentiment Analysis Algorithms it can learn how systems are interconnected and the required flow of data which can lead to developing smart products. Its used in industries such as financial services, telecoms, government and healthcare – businesses with rules-based processes that involve rekeying data. More recently, the technology has gained ground in manufacturing and logistics. RPA can replicate almost all human-cognitive tasks on the production line if they conform to rules or decision-tree logic. 55

56. SAM One of the prominent features of Industry 5 . 0 is additive manufacturing referred to as 3D printing which is applied to make manufacturing products more sustainable. Additive manufacturing in Industry 4.0 focused on customer satisfaction by including benefits in products and other services. It also facilitates customization, transparency, interoperability, automation and practicable insights. I n Industry 5.0 SAM defines the various processes in which the component to be manufactured is developed by adding materials and the development is executed in various layers. SAM has the capability to save energy resources, helps to reduce material and resource consumption which leads to pollution free environmental production. To obtain the complete benefits of Industry 5 . 0, SAM is merged with integrated automation capability to streamline the processes involved in supply chain management and reduces the delivery time of the products. 56

57. 4D Printing 4D printing is the process through which  a 3D printed object transforms itself into another structure  over the influence of external energy input as temperature, light or other environmental stimuli. 3D Printing is about repeating a 2D structure, layer by layer in a print path, from the bottom to the top, layer by layer until a 3D volume is created.  4D Printing is referred to as 3D printing transforming over time. Thus, a fourth dimension is added: time. So, the  big breakthrough about 4D Printing over 3D Printing technology is its ability to change shape over time . 57

58. 5D Printing In 5D the print head & the printable object have five degrees of freedom. Instead of the flat layer, it produces curved layers. The main advantage of this technology is to create a part with a curved layer with improved strength. Instead of 3 axes used in 3D printing, 5D printing technologies use five-axis printing technique which produces objects in multiple dimensions. In this five-axis printing, the print bed can move back and forth on two axes besides of X, Y and Z axis of the 3D printing technologies. Thus this technology is highly capable of producing stronger products in comparison to parts made through 3D printing. 58

59. Banking 4.0 Banking 4.0 The future of banking is not just about payment and credit utility—it's embedded in voice-based smart assistants like Alexa and Siri, available 24/7 to pay, book, transact or enquire. Bank 4.0 means that either your bank is embedded in your world, or it isn’t. 59 With the advent of Industry 5.0, Fintech Hubs will increasingly interconnect with each other to become ‘Smart Digital Fintech Hubs’. This new age digital infrastructure will have the power to assist in building a new digital financial system.

60. Cryptocurrency Cryptocurrency has made tremendous inroads into everyday life since Industry 4.0 was first introduced in 2011. As a form of currency it is still in its infancy due to its volatility. But any decentralized payment system can only be a good thing. For the full potential of Industry 4.0 to be realized and create significant global value the development of an open and global payment protocol is required T he potential of cryptocurrency is it performs frictionless and transparent financial transactions, without the intervention of intermediaries Cryptocurrency and blockchain technology are ideal for implementing the shift to the global, trustless, and open new economy. One concern though is the vast energy requirements as this is not aligned with Industry 5.0 goals. 60

61. Blockchain Whereas cryptocurrency may be counter to the objectives of Industry 5.0. The underpinning technology is still attractive as data collected by  IoT-based sensors  can be transmitted through a blockchain-based tamper-proof ledger. The use of encryption algorithms ensure that information remains secure, while the decentralized nature of the network eliminates single points of failure. Blockchain is already being used for asset tracking applications in various industries. By employing blockchain together with IoT, manufacturers will be able to streamline how they aggregate, store and share data with partners across the supply chain. 61

62. Artificial Intelligence in Industry 5.0 M anufacturing is responsible for a significant part of the worldwide energy consumption and artificial intelligence has an enormous potential to benefit environmental sustainability and pave the way to a more eco-friendly and energy-efficient manufacturing. Artificial intelligence can solve a number of issues that are critical for sustainable manufacturing. This includes: ex cessive use of materials, redundant production of scrap waste, inefficient supply chain management, logistics and unequal distribution of energy resources. AI can eradicate all of these difficulties. Artificial intelligence is an advanced technology that has the potential to fundamentally transform the manufacturing industry and create unparalleled working opportunities within the “missing middle” and forge the path towards smart, efficient and sustainable manufacturing.  62

63. AI in Industry 5.0: Product Development Generative Design for Manufacturing It is a design branch focused on the union of h uman creativity with artificial intelligence. By selecting parameters such as weight, size, materials, manufacturing and operating conditions with generative design software, engineers can generate different design solutions in a short time and AI facilitates all possible design options for a given product. 63

64. Machine Learning in Industry 5.0 Manufacturing companies are committed to understanding market trends, changes, and finding applications to remain competitive. ML facilitates compliance with industry regulations and standards, improve safety and address environmental concerns. The intelligence derived from the analysis and monitoring of real-time data is essential to generate profitable and sustainable solutions. Avoiding bottlenecks within production chains is not a chimera since it is possible to visualize the processes at all times.  64

65. Predictive Maintenance 65 Industry 4.0 makes   predictive maintenance  feasible and significantly reduces operational expense (OpEx) . Predictive maintenance means businesses can schedule maintenance activities  based on accurate predictions about an asset’s lifetime . Predictive maintenance offers many business benefits when compared to the conventional reactive and preventive models: Improved Asset Utilization and OEE : With predictive maintenance, enterprises make the best possible use of their assets and improve their OEE. Avoidance of Unscheduled Downtimes:  Predictive maintenance provides visibility on the actual condition of the assets, which minimizes possible unscheduled downtimes. Optimal Planning of Maintenance Activities:  Information about the asset’s conditions and their anticipated EoL can be combined with insights on business operations (e.g., production schedules, demand forecasts) towards maximizing revenues and minimizing MRO costs.

66. ML in Industry 5.0 M achine L earning facilitates predictive maintenance, anticipating equipment failures, scheduling maintenance at the right time, and reducing unnecessary downtime.  The ML models that depend on the objective or approach of the prediction that is sought are; RUL (Remaining Useful Life) models: Regression models to predict the remaining useful life. Historical and statistical data are used to predict how many days until a failure occurs. Classification models to predict a failure in a defined period. Used to define a model that predicts failures within a defined number of days. Anomaly detection model to identify items with potential problems. The approach predicts failures by comparing and identifying differences between normal system behaviour and failure events. 66

67. ML – I5.0: Digital Twins  Digital Twins provide simulation models for real-time diagnostics and evaluations of the production environment. T hey deliver performance and monitoring predictions, and the visualization process for all kinds of key parameters. To generate the models that understand the physical systems, machine learning unsupervised algorithms are used. As the data is processed, these algorithms look for patterns of behaviour and detect anomalies. They also can process external data, such as research, industry data, social media, and media. Digital Twins are a tool not only applicable for product design, but also for simulating the performance of existing physical products, services and even entire ecosystems. 67

68. ML-I5.0: Quality Control Machine Learning can be applied for product inspection and quality controls. ML-based algorithms learn from historical data or derived from computer- v ision that distinguish good products from those with defects, thus automating the inspection and supervision process. D eep learning architectures, such as convolutional neural networks detect visual clues indicative of quality problems in products and parts in highly complex assembly processes. The advantage of this branch of machine learning is that it is much more scalable through image learning and object detection. 68

69. ML in I5.0: Quality Improvement C ustomers expects flawless products, as defective products cause non-conformities that damage the reputation of the company and its profit margins. M L can foresee quality problems right down the production line. Artificial vision  is an example of a ML solution, in which high-resolution cameras are used to monitor defects. This can be combined with a cloud-based data processing framework to generate an automated response. 69

70. ML in Logistics and Inventory Management can address 9 key pain points: Predicative Analysis Automated Quality Inspection Real-time Visibility Streaming Production Planning Reduce Cost and Response Time Warehouse Management Reduce Forecasting Errors Advanced Last-mile Tracking Fraud Detection and Prevention 70 ML in I5.0: Logistics & Inventory Mgmt

71. AI & ML in I5.0: Sustainability Issues Sustainable manufacturing covers the three basic elements involved in manufacturing i.e., processes, products and systems which enables economic growth and sustainable value creation in industries. To ensure sustainability in manufacturing these three elements must individually demonstrate the benefits at the social, economic and environmental levels. Sustainable manufacturing can be described as the integration of systems and various processes to produce a high quality of products with minimum resource utilization, sustainable resources, being safer for customers, employees and communities In Industry 5.0 it is in the interest of small and medium-sized businesses to pay attention to sustainability and environmental issues. For example, information that arises during the production process could be used to improve the energy consumption and capacity of machines. The positive effect for the environment then stems from the reduction in greenhouse gas emissions.  71

72. Contradictions regards ML & AI D espite the millions of dollars invested in analytics technologies, the majority of companies still struggle to establish an efficient and programmatic way to do analytics at scale. According to Gartner Inc., over 60% of models developed with the intention of operationalizing them were never actually operationalized. Furthermore the costs are prohibitive and the waste unsustainable – it can cost upwards of 100K dollars just to run one instance on a training model. 72

73. Jumping the Gap from I3.0 to I5.0 73 Digitally transform the business and its processes and culture Digital transformation of the organization is critical to Industry 4.0 Harvest data from everything and everywhere Optimize the Value Chain Reimagine the vertical value chain and understand how it functions Reimagine the horizontal value chain and understand its importance to operational efficiency Optimize the value of Supply Chain 4.0 Optimize Quality Improvement and Lean thinking to reduce waste Optimize processes through continual improvement methods Automate processes where feasible Optimize operational efficiency and reduce maintenance costs and downtime Today, despite deploying advanced robots and the latest technologies most manufacturers remain at I3.0 level. This is because to travel to Industry 4.0 and beyond we need to understand the importance of the value chain and how we derive profit from efficiency. Consider the following prerequisites :

74. Getting from Industry 3.0 to Industry 5.0 Starting out on a transformation to industry 5.0 will require mastering Industry 4.0 first and to do that you will need to fulfill some prerequisites. Determining existing shop floor technologies Integrating legacy and remerging technologies Converge Operations Technology and Information Technology Vertical and horizontal value chain integration Systems Integration Identifying targets and goals 74

75. …legacy technologies I t’s not just about robots and big data you still have all the legacy technologies;   D ata communication/network technologies, Human Machine Interfaces (HMI) and SCADA , M anufacturing E xecution S ystems  (MES) , E nterprise R esource P lanning  (ERP, becoming i -ERP) , P rogrammable L ogic Controllers  (PLC) , sensors and actuators, Micro Electrical Mechanical Systems (MEMS) and  transducers   and all those innovative data exchange models These all play a key role in connecting the workplace. 75

76. Bridging the OT/IT divide Operations Technology - monitors and manages industrial process assets and manufacturing/industrial equipment. Information Technology - the study or use of systems (especially computers and telecommunications) for storing, retrieving, and sending information. 76 Identify IT/OT Convergence Points: Every factory floor has its crossover points from OT to IT and vice versa. Thus, it is essential to classify processes and map them appropriately.

77. Blurring the lines between OT/IT For the most part, IT and OT have constituted completely different and disjoint aspects of an organization’s infrastructure. But combining operational and enterprise information is the secret ingredient for manufacturing excellence. It makes success repeatable and scalable.  Since the advent of industry 4.0, there is an increasingly converging IT-OT pattern that is changing how an organization’s infrastructure functions. Assets like assembly-line machinery that have previously been offline are being brought online by the power of IoT to:  Minimize unplanned downtime using predictive maintenance Provide better decision making with decision support systems Use wireless technology in an operative environment Deliver i mprovement in critical data management Enhance efficiency and better first-pass yield rates D eliver b etter safety standards in the work environment Th There is no playbook that guides successful interoperability and interaction between IT and OT. This is because no organization has managed to perfect this. Blurring Lines Between I 77

78. Digitization: Harvest the Data Digitization is all about collecting our manufacturing plant data and transforming it into useful information which we can use to shape and optimize our processes. Gathering external information helps us learn about our supply chain and how customers use our products which leads to us making better and smarter products. But gathering internal data can be hard. Historically, manufacturing businesses have collected data manually, through shop floor paper-based systems and processed them via spreadsheets. There is a vast amount of process data that could be collected to aid in optimization but accessing it is not trivial. Collecting manufacturing data allows for the analysis and calculation of essential manufacturing performance metrics, including downtime, Overall Equipment Efficiency (OEE), and throughput, while also calling attention to problems such as equipment malfunctions, stoppages, supply chain quality and customer returns. 78 The goal of every manufacturer today should be to optimize (OEE). OEE is the overarching production efficiency measure that compiles a number of vital manufacturing KPIs into one objective measure of manufacturing success. With accurate and timely manufacturing data in hand, manufacturers can make better decisions that will drive OEE up and, as a result, increase business profitability.

79. Gathering Manufacturing Data “according to McKinsey & Company’s recent report,  Industry 4.0: Capturing Value at Scale in Discrete Manufacturing . The report shows that, although 68 percent of companies see Industry 4.0 as a top strategic priority, “only about 30 percent of companies are capturing value from Industry 4.0 solutions at scale today.” There are many sources of process data: IoT (Internet of Things) sensor integration. Line HMI (Human Machine Interface) system integration. PLC (Programmable Logic Controller) integration. RTU (Remote Terminal Units) integration. SCADA (Supervisory Control and Data Acquisition) systems. Cyberphysical systems Extracting data from all of these diverse sources and integrating it into a data lake of big data is not going to be easy. 79

80. Gathering Data from Production System Integration is the task of connecting all the disparate production floor equipment into an Operational Backbone, which connects all OT and IT systems into a centralized ‘Single Source of Truth’ such as a Data Warehouse. The various types of industrial communication protocols are: OT Domain Ethernet/IP BACnet Modbus RTU Modbus TCP DeviceNet OPC UA ProfiNet ProfiBus IO-Link EtherCAT CC-Link CAN Open IEC 61131-3 ASI-Interface LonWorks The challenge is to get data from all those sources onto the Operational Backbone for sharing across the organization or for harvesting the Big Data. 80 IT Domain & the Internet Ethernet

81. A Pub/Sub Pattern for Data Integration 81 Intelligent Gateway This provides the method for connecting diverse protocols and interface types to connect to a MQTT Broker

82. Digital Transformation Digital transformation is the transformation of business, industrial products, operations, value chains and services that are enabled through the augmentation of people, knowledge, and workplaces through the expanded use of digital technologies. Digital Transformation is about more than technology it is about: People - Digital transformation relies heavily on the knowledge and experience gained from subject matter experts (SMEs) – the operators, engineers and other workers expertise regarding the process, as well as business managers and data scientists regards data modeling and business objectives. Processes – Transformation needs a rethinking of existing processes to find end-to-end ways to meet customer needs, the seamless connection of work activities, and the ability to travel across silos. Technology - It’s about taking newer disruptive technologies and integrating them or even replacing aging systems, business models and aging processes with connected systems, connected data, connected operations, and connected supply chains in a connected enterprise. Services - transformation is about taking non-digital formats of information and turning them into digital formats. 82

83. DX: Execution in Industry 5.0 T o move beyond planning to digital transformation execution, it is crucial to establish why your organization needs to change. Align Business Goals with the Digital Vision Choose the right Data Analytics Capabilities Determine the Operational Impacts of DX Understand Employee readiness for technology change Craft Training to leverage the impact of technology change Design the Transformation from the top-down. Start with people and processes then customize the technology to accommodate them. Do not start with the technology and then try to fit your business process to it, unless there is no other way Involve IT and Technologist only when their expertise is required Remember this is a Business Initiative involving the integration of Business processes! Successful Execution Requires you Drive the Change not IT! 83

84. Integrating the Value Chain The Value Chain in Industry 4.0 consists of the Horizontal and the Vertical but t he two concepts centre on technologies, processes, and systems that enable the collection, collation, communication, and use of data. The Vertical Value Chain : is internal to the organization and connects all business units and processes. With vertical integration, data flows between and is made available to all business units. This includes the factory floor, marketing, sales, customer service, purchasing, accounting, HR, quality control, R&D, and more. The Horizontal Value chain: Horizontal integration applies within your production facility, and externally across multi-site operations, and even extends to third-party partners in your supply chain, both upstream and downstream. Within your production facility, horizontal integration is about achieving the Smart Factory, where all systems, processes, and machines are connected, enabling constant communication. 84

85. Supply Chain 4.0 “Supply Chain 4.0 - Is the application of the Internet of Things, the use of advanced robotics, and the application of advanced analytics of big data in supply chain management: place sensors in everything, create networks everywhere, automate anything, and analyze everything to significantly improve performance and customer satisfaction” Horizontal Value Chain i ntegration with Industry 4.0 involves connecting all parts of your supply chain to the manufacturing plant. This deeper alignment improves visibility, flexibility, and productivity while also enhancing levels of automation. The supply chain cloud forms the next level of collaboration in the supply chain between customers, the company, and suppliers, providing either a shared logistics infrastructure or even joint planning solutions. Especially in noncompetitive relationships, partners can decide to tackle supply chain tasks together to save admin costs, and also to leverage best practices and learn from each other. 85

86. Quality and Process Improvement 86 "Lean" is considered a philosophy of continuous improvement. A lean organization focuses on increasing customer value, the elimination of waste and optimizing operations. Lean thinking can provide improved value for the customer by: Improving the quality of work processes Reducing errors or defects in work processes Reducing costs Improving flow of the process Simplifying complex processes Reducing lead time Improving employee morale

87. Lean Continuous Improvement 1. Value. Value is always defined by the customer’s needs for a specific product. For example, what is the timeline for manufacturing and delivery? What is the price point? What are other important requirements or expectations that must be met? This information is vital for defining value. 2. Value stream. Once the value (end goal) has been determined, the next step is mapping the “value stream,” or all the steps and processes involved in taking a specific product from raw materials and delivering the final product to the customer. 3. Flow. After the waste has been removed from the value stream, the next step is to be sure the remaining steps flow smoothly with no interruptions, delays, or bottlenecks. “Make the value-creating steps occur in tight sequence so that the product or service will flow smoothly toward the customer,” 4. Pull. With improved flow, time to market (or time to customer) can be dramatically improved. This makes it much easier to deliver products as needed, as in “just in time” manufacturing or delivery. This means the customer can “pull” the product from you as needed (often in weeks, instead of months).  5. Perfection. Accomplishing Steps 1-4 is a great start, but the fifth step is perhaps the most important: making lean thinking and process improvement part of your corporate culture. 87

88. The Connected World 88 This is the world today the internet of everything.

89. Industry 4.0 Reference Architecture 89 This is Industry 4.0 manufacturing today And this is where we want to be to match demand from our connected world.

90. Smart Factory Architecture 90 IoT provides the connectivity Big data is produced and consumed here Cyberphysical systems connect to both worlds

91. Data and System Integration ISA 95 91

92. Operations Software In many manufacturing sites the IT landscape is a mixture of duplicated functionality, gaps in functionality and many isolated add-on solutions as Excel sheets, paper systems and other “best-of-breed” solutions. All with the purpose of trying to connect the ERP level and shop floor level systems without a layer in between. By introducing a Manufacturing Operations Management (MOM) layer between the ERP system and the shop floor level systems a predefined integration is achieved. This not only covers processes in the production but also influences the whole supply chain, distribution, quality assurance and maintenance. Overall, the following improvements can be achieved: Increase asset utilization by 10-20% through better planning, optimization algorithms, decrease of the changeover times and downtime. Improve on time deliveries by 6-10% Decrease lead time with 30-40% Reduce re-works by 5-10% Decrease waste (scrap) with 10% by “institutionalization” of the production process Reduce inventory costs up to 30% 92

93. Manufacturing Operations Management 93

94. Smart Factory Use-cases Remote Monitoring : With IoT-connected assets, you can monitor equipment usage and health in order to assess performance and deploy service should there be any problems. Supply Chain Management and Optimization: Real-time tracking of assets and products, forecasting greatly improves Digital Twins: A virtual, or simulated real-world object, concept, or area within a digital space, digital twins are an interesting and powerful use case of IoT.  Real-Time Machine Monitoring: provides a stream of data straight from the machine control to provide accurate data analytics that can be used for in-the-moment decision making or in-depth analysis. Predictive Maintenance: enables manufacturers to get the absolute most out of their maintenance spend while reducing downtime as much as possible. Production Visibility: operators have insight into all their machines with visual dashboards tracking the performance against production goals. Integrating Systems: is that each system can use the valuable data provided by other systems in order to perform its function in a better way. Compiling KPIs: IoT platforms are helping to compile and contextualize data into simplified reports and dashboards that can quickly explain how well a business is performing. Automation: Industrial automation is one of the largest promises of Industry 4.0.  as it helps to reduce downtimes, provide predictable maintenance, and improve decision-making. Asset Utilization: one of the  most important metrics in manufacturing , OEE gauges how well manufacturers are using their equipment and allows them to optimize their usage through data analytics 94