Industry 4.0: the fourth industrial revolution – guide to Industrie 4.0

Industry 4.0 and the fourth industrial revolution: definition, origins, benefits, challenges, components, strategy, cyber-physical systems, building blocks and evolutions – your guide to ‘Industrie 4.0’.

The Internet of Things, the convergence of IT and OT, rapid application development, digital twin simulation models, cyber-physical systems, advanced robotics and cobots, additive manufacturing, autonomous production, consistent engineering across the entire value chain, thorough data collection and provisioning, horizontal and vertical integration, cloud computing, big data analytics, AR/VR and edge computing amidst a shift of intelligence towards the edge: these are some of the essential components of the fourth industrial revolution.

The value created by Industry 4.0 vastly exceeds the low-single-digit cost savings that many manufacturers pursue today (Boston Consulting Group)

Those are quite a lot of terms and components indeed. Yet, Industry 4.0 is a rather vast vision and, increasingly, vast reality.

What makes it all the more fascinating (and at first sight complex) is that convergence of two worlds which have been disconnected thus far: Information Technology (IT) and Operational Technology (OT) with the hyper-connected digital industry, the bridging of digital and physical, cyber-physical production systems and the Industrial Internet of Things as parts (and names) that describe this fourth industrial revolution.

The integration of IT and OT is far from a fact yet, although there are differences, depending on the Industry 4.0 projects. As it is still early days in the maturity journey and vision of Industry 4.0, there mainly is a focus on projects (while Industry 4.0 at a more mature level is a holistic given) and such projects can vary a lot. Projects around energy efficiency, factory energy management and HVAC (Heating, ventilation and air conditioning), for instance, bring us to an entirely different world (with different solutions, skills and standards) than, for instance, additive manufacturing, robotics or augmented reality to name a few. In the end, integration and convergence is what it will be about as specialists will continue to be needed.

Despite the vastness, terminology and many concepts, in the end Industry 4.0 is about the digital transformation in and of industrial markets, in the beginning only manufacturing, and with a big role for the Industrial IoT, as we’ll see. And just like digital transformation it requires a strategic view and staged approach.

In this overview we make ‘Industrie 4.0’, as it’s originally called, tangible and look at and beyond the technologies and processes: as always, outcomes and goals need to come first.

Industry 4.0 is not just about manufacturing (anymore)

Although the term Industry 4.0 and the reference architecture model behind it originate from Germany (hence ‘Industrie 4.0’), it’s clear that the vision – and reality – of the fourth industrial revolution has caught the attention of organizations across the globe as we’ll explore at the end of this article. Moreover, Industrie 4.0 is not just about manufacturing anymore (even if manufacturing is the main sector involved today).

So, although Industry 4.0 originally was only used for manufacturing (in contrast with other leading initiatives such as the Industrial Internet and the Industrial Internet Consortium or IIC), it is de facto going further. In the early days of the Industry 4.0 view we wouldn’t have been able to say that; it was a manufacturing initiative, period. Today, we clearly see how the several parties which were involved in Industry 4.0 themselves move it to smart transportation and logistics, smart buildings, oil and gas, smart healthcare and even smart cities.

An increasing number of vertical industries is adopting the technologies, concept and principles of Industry 4.0.

We clearly see this expansion across other verticals on top of manufacturing in the material that gets published by leading Industry 4.0 institutes such as the German national academy of science and engineering (acatech). This doesn’t mean that they (alone) are broadening the scope, the opposite is true (as well): the mentioned vertical industries (and others) are increasingly adopting the Industry 4.0 concept, principles and technologies. How else could it be? It’s not as if manufacturing lives in splendid isolation and, despite the specific characteristics, processes and priorities in manufacturing, the underlying technological and transformational traits do overlap in this hyper-connected age.

The principles of Industry 4.0 have gone global, even if the term doesn’t ring a bell everywhere (the fourth industrial revolution is more widely recognized).

Industry 4.0 is a vision and journey. Organizations implement Industry 4.0 initiatives and prepare to turn the clearly document Industrie 4.0 vision, components, principles, technologies and architecture into reality, within their context.

This global diffusion of the Industrie 4.0 vision and technologies, at different speeds, is related with the universal challenges and possibilities across the globe and with the cross-fertilizations, enabled by collaborations with the US industry, the Japanese industry, EU industry initiatives and so forth. Still, there are several hurdles to take before the Industry 4.0 vision is realized in more companies than is the case today. More about how Industry 4.0 is a vision and a reality at the same time in the section on Industry 4.0 strategy and roadmaps.

This being said, time for a deeper dive. As per usual, everything starts with understanding what exactly we are talking about, what are the benefits and how it is all evolving and impacting organizations in real life.

So, let’s start with the roots of Industrie 4.0 before diving even deeper into those mentioned frameworks and so forth.

When Germany launched a project under the name ‘Industrie 4.0’ to digitalize manufacturing at the Hannover Messe in 2011, the government officials, industry leaders and academics who were working on the project probably had no idea that Industry 4.0 and specifically that fourth industrial revolution would become such a widely used concept.

Moving beyond its roots, Industry 4.0 and the Industrial Internet are meeting in a global collaboration towards the digital transformation of manufacturing and other industries.

Despite the vision aspect, ‘Industry 4.0’, is a very real phenomenon, transforming manufacturing and other sectors into connected and digital manufacturing (and more) with additional benefits and a range of technological evolutions and possibilities to move beyond the sheer operation dimension towards the so-called fourth industrial revolution.

We define Industry 4.0 as the digital transformation of manufacturing, leveraging third platform technologies, such as Big Data/Analytics and innovation accelerators, such as the (Industrial) Internet of Things; and requiring the convergence of IT (Information Technology) and OT (Operational Technology), robotics, data and manufacturing processes to realize connected factories, smart decentralized manufacturing, self-optimizing systems and the digital supply chain in the information-driven cyber-physical environment of the fourth industrial revolution.

The initial goals in Industry 4.0 typically are automation, (manufacturing) process improvement and productivity/production optimization; the more mature goals are innovation and the transition to new business models and revenue sources with information and services as cornerstones. Industry 4.0 is also called ‘smart industry’ or ‘smart manufacturing’. In many senses it is related to the Industrial Internet and since 2016 the Industrial Internet Consortium and Industry 4.0 platform, “Plattform Industrie 4.0”, indeed started collaborating.

This is probably not the shortest Industry 4.0 definition ever and it does contain some terms we might need to explain further such as the third platform and innovation accelerators as they exist in the DX (digital transformation) economy, as well as the integration of IT and OT, which is key in the cyber-physical context of Industry 4.0 as we’ll see.

A shorter definition of Industry 4.0: the information-intensive transformation of manufacturing in a connected environment of data, people, processes, services, systems and production assets with the generation, leverage and utilization of actionable information as a way and means to realize the smart factory and new manufacturing ecosystems.

The original definition of Industry 4.0 (or better: Industrie 4.0)

The definition of Industrie 4.0 as proposed in 2011 was pretty lengthy too. In a paper, entitled “Industrie 4.0 – Smart Manufacturing for the Future”, GTAI (Germany Trade and Invest) looked at the questions what is smart industry (a synonym of Industry 4.0) and what Industrie 4.0 means.

An extract: Smart industry or “INDUSTRIE 4.0″ refers to the technological evolution from embedded systems to cyber-physical systems…INDUSTRIE 4.0 represents the coming fourth industrial revolution on the way to an Internet of Things, Data and Services. Decentralized intelligence helps create intelligent object networking and independent process management, with the interaction of the real and virtual worlds representing a crucial new aspect of the manufacturing and production process”.

And it’s not done! More in the paper (PDF opens) and in our Industry 4.0 definitions list below.

What is Industry 4.0 (according to several sources)?

If you wonder what Industry 4.0 is in practice, you’ll find more on the various aspects and evolutions further below.

However, if you need a description Industry 4.0 and seek an Industry 4.0 definition, which you can use for whatever purpose, take a look at the Industry 4.0 definitions we gathered from various other sources which, in many cases, are also excellent starting points to learn more about the pretty broad reality of Industry 4.0, the fourth industrial revolution and all its aspects.

Obviously not all definition of Industry 4.0 are the same. It’s as Marijn ten Wolde of Bosch Siemens Home Appliances said in an interview: “Industry 4.0 has a different meaning or for each company. Even within Bosch there isn’t one definition of Industry 4.0. It’s dependent on the strategy for each factory. The most important principles for manufacturing are connectivity and operational excellence”.

Benefits, goals and excellence before definitions (but below are those definitions anyway).

The evolving reality of Industry 4.0

So, Industry 4.0 was originally a project in Germany with several components and workgroups.

Companies are implementing Industry 4.0 but in rather ad hoc and isolated ways

One component was and still is the smart factory of tomorrow, or as some call it the digital or connected factory. A factory that is not just making manufacturing faster, more flexible and more efficient but also is ‘intelligent’. Indeed, machine-to-machine communication and processes whereby machines and technologies can identify issues and take autonomous decisions, based on third platform technologies, an integrated IT/OT environments and the so-called Industrial Internet of Things. It’s clear that also security plays a big – and increasing – role here.

Among the several third platform technologies and their innovation accelerators in Industry 4.0: Big Data (Analytics), cloud computing (and, more recently fog computing) artificial intelligence and cognitive, robotics, augmented reality and virtual reality, advanced security, simulation methods such as digital twins and, as said, the Internet of Things (IoT). We take a close look at the Internet of Things in Industry 4.0 and compare it with a key building block of Industrie 4.0, the cyber-physical systems, below. However, it’s not just about IT; OT (Operational Technology) and the convergence of the many operational technologies and realities with IT as we know it, are at least as important. That will become clear if you read about architectural frameworks and the mentioned cyber-physical systems.

IoT is a key component in this whole equation, mainly from an industrial Internet of Everything perspective, which looks a bit more at the processes, data analysis and people picture than the Internet of Things does. Also the Internet of Robotic Things plays an increasing role in Industry 4.0.

The technologies in fact were a second component that was studied in the ‘Industrie 4.0’ workgroups, on top of the smart factory and the other dimensions such as (the future) of work, the economic context of the manufacturing industry and so forth. Other technological factors include network technologies, security, all the advanced mechanics and components of cyber-physical systems, the list goes on.

The principles and technologies of Industry 4.0 were connected to a concept of a fourth industrial revolution as is known (hence the 4).

Industry 4.0 and the fourth industrial revolution

As a reminder the classic view of these four industrial revolutions, as Industry 4.0 became increasingly popular, was:

  1. The first industrial revolution, which REALLY was a revolution, and, among others thanks to invention of steam machines, the usage of water and steam power and all sorts of other machines, would lead to the industrial transformation of society with trains, mechanization of manufacturing and loads of smog.
  2. The second industrial revolution is typically seen as the period where electricity and new manufacturing ‘inventions’ which it enabled, such as the assembly line, led to the area of mass production and to some extent to automation.
  3. The third industrial revolution had everything to do with the rise of computers, computer networks (WAN, LAN, MAN,…), the rise of robotics in manufacturing, connectivity and obviously the birth of the Internet, that big game changer in the ways information is handled and shared, and the evolutions to e-anything versions of previously brick and mortar environments only, with far more automation.
  4. In the fourth industrial revolution we move from ‘just’ the Internet and the client-server model to ubiquitous mobility, the bridging of digital and physical environments (in manufacturing referred to as Cyber Physical Systems), the convergence of IT and OT, and all the previously mentioned technologies (Internet of Things, Big Data, cloud, etc.) with additional accelerators such as advanced robotics and AI/cognitive which enable Industry 4.0 with automation and optimization in entirely new ways that lead to ample opportunities to innovate and truly fully automate and bring the industry to the next level.

Some also like to add the injection of technology and connectivity in the human/digital mind and body convergence to Industry 4.0.

The injection of AI, hyper-connectedness and data analysis into how things, machines, communicate, act and lead to actionable insights with an omnipresence of the Internet of Everything in virtually each piece/machine of the Industry 4.0 dream is one thing, the convergence of man and machine (or technological extension) is still a bit further away and it’s so complex and will lead to so many more debates (also ethical) that it’s already called the fourth platform by IDC.

In the view of the Boston Consulting Group (we tackle their Industry 4.0 research below) Industry 4.0 refers to the convergence and application of nine digital industrial technologies: advanced robotics, additive manufacturing, augmented reality, simulation, horizontal/vertical integration, Industrial Internet, the cloud, cybersecurity and Big Data and Analytics.

It’s clear that today some companies have invested in a few of these technologies; predominantly the traditional pillars of the third platform such as cloud and Big Data / Analytics and, increasingly in the Industrial Internet of Things from an integrated perspective and thus overlapping with several of these “technologies” or maybe better: sets of technologies and connected benefits.

Obviously, it wasn’t just in Germany (and Europe) that the digital transformation of manufacturing (and some related industries and processes) was occurring with industrial giants in the Industry 4.0 space (Bosch, Siemens, you name it).

As mentioned, in the US, GE and a range of other industrial players (including non-American ones who are also members of the “Plattform Industrie 4.0”) launched the Industrial Internet Consortium.

By 2018, only 30 percent of manufacturers investing in digital transformation will be able to maximize the outcome; the rest are held back by outdated business models and technology (IDC)

The Industrial Internet, as we wrote previously a term coined by American industrial giant GE, looked pretty much like Industry 4.0., although in the Boston Consulting Group image above it is mentioned as one of the enabling industrial technologies in the network of machines and products and networked objects communications sphere of IIoT.

The difference between Industry 4.0 and the Industrial Internet, however, is that, originally, the Industrial Internet was seen as the third industrial innovation wave. So, a third wave of innovation instead of a fourth revolution in the industry.

It only shows how relative revolutionary terms are as the three industrial Internet innovation waves respectively were:

  • The Industrial Revolution. The real one and more or less a combination of the first and second revolution in the Industry 4.0 view.
  • The Internet Revolution: ‘computing power and the rise of distributed information networks’.
  • The Industrial Internet: what is called the fourth industrial revolution in Industry 4.0.

Today the concept of four industrial revolutions, however, has gained widespread adoption and so has Industry 4.0.

Globalization, architectures and standardization: the collaboration between Industry 4.0 and the Industrial Internet Consortium

The Industrial Internet Consortium had a more cross-industry approach than German “Plattform Industrie 4.0” (the Industry 4.0 Platform), which was more focussed on manufacturing (although, as stated, now it’s also used for logistics and more).

As both the Industrial Internet Consortium and Plattform Industrie 4.0 shared many efforts and views, and more and more companies became member of both platforms, both organizations started looking at similarities and collaboration. After all, we still do live in a globalized world, certainly in industrial production and related markets.

So, collaboration became obvious, even more so because both industry bodies were working on an architectural framework. In the context of Industry 4.0 and “Plattform Industrie 4.0” this framework is known as RAMI 4.0, short for the Reference Architecture Model for Industrie 4.0. The Industrial Internet Consortium’s framework is known as IIRA, short for the Industrial Internet Reference Architecture.

Early 2016 the Industrial Internet Consortium and Plattform Industrie 4.0 announced their collaboration, with a focus on standardization, the architecture for the “new” manufacturing, the business goals and the role of the Internet of Things in it all.

If you look at Industry 4.0 today you’ll notice that there is also an increasing attention for industries, other than manufacturing as already was the case in the Industrial Internet Consortium and that cyber-physical systems, which we’ll tackle next are seen beyond the scope of cyber-physical production systems but also as the enablers of, among others condition monitoring and remote possibilities, which in term don’t just enable and drive the smart factory.

The #Industry40 Race – Time to accelerate? @BCG #Germany US# #Manufacturing

– ScaleIT (@scale_it_org) 12 januari 2017

All revolutions and associations aside, the question is how far we are in Industry 4.0. Are manufacturing companies fully ready? And what means readiness in this industrial context to begin with?

The definition of a strategy is challenge number one in Industry 4.0 (Boston Consulting Group)

In other words: what are the characteristics, principles, technological maturity levels, (achieved and desired) benefits and realizations and where do we start with Industry 4.0 or the Industrial Internet? As you’ll notice the answers to these questions are very similar to those in digital transformation across any industry and as in any digital transformation strategy challenge. After all; in the end, regardless of the different technologies and market context in manufacturing, digital transformation is a universal given in any industry whereby similar capabilities and outcomes are sought. Yet, as mentioned in the beginning of this article, Industry 4.0 is a vision and reality with projects and clear steps towards the vision.

Industry 4.0, which in more than one way as said is the digital transformation of manufacturing, today still is mainly focused on the first stages of transformation and ‘maturity’ from a benefit and potential perspective: enhancing productivity, automation and the optimization of operational processes, business processes and, the number one Internet of Things use case from an IoT spending perspective: manufacturing operations, followed by (predictive) maintenance and smart maintenance services.

This is also what the Boston Consulting Group found in a December 2016 report: companies are implementing Industry 4.0 but in rather ad hoc and isolated ways.

This is exactly the same phenomenon we see in any industry that is in digital transformation – or revolution if you prefer. It’s that first stage in a broader ecosystem of possibilities as organizations move from more or less obvious goals to true innovation and even disruption. The illustration below from the Boston Consulting Group shows some aspects of this broader ecosystem of possibilities, beyond the enhance productivity dimension.

In other words: MOST manufacturing and industrial companies (there are plenty of exceptions and we mention several across this site) are still in that stage where the intention to transform exists and isolated efforts exist but there is often a lack of a bigger picture, a broader strategy or, as the Boston Consulting Group calls it in the Industry 4.0 context ‘a comprehensive program’.

Industry 4.0 ranks high on the agenda, yet in practice one or two isolated aspects of Industry 4.0 are implemented, the company says. Examples: big data and/or robotics.

This is really the first stage of maturity whereby there is also a focus on the mentioned optimization and automation goals and gains, which is perfectly normal but it shouldn’t stop there.

You can perfectly compare this with the findings of IDC regarding the gradual evolution from Internet of Things pilot projects to more scalable deployments, whereby IDC found that the sought benefits of these deployments are mainly focused on internal goals and on operations.

This situation is poised to remain like that for a while tough as, despite the increasing number of large IoT projects, the Internet of Things is more seen as strategic and tactical than transformational and internal goals are key.

As the image below shows, enhancing productivity, reducing costs and the automation of internal processes dominate. It’s clear that in companies that are further from a benefit perspective and look at better customer service, new revenue streams, changes in business models and innovation, IoT deployments go further.

Where the Boston Consulting Groups says that the vast majority of respondents see Industry 4.0 as an opportunity to improve productivity – and analyzes how this is done in practice- the parallels are crystal clear. So, what does it take to move to those next maturity stages?

Industry 4.0 is the current trend of automation and data exchange in manufacturing technologies. It includes cyber-physical systems, the Internet of things and cloud computing. Industry 4.0 creates what has been called a “smart factory”. (Wikipedia)

Not for the sake of maturity but for the sake of moving beyond that enhanced productivity towards higher agility, real-time opportunities, the development of an innovative capability and true innovation, identifying new information-driven and service-oriented sources of revenue and many more goals?

The answers are again the same as in all digital transformations, as are the challenges. Developing new competencies, finding new opportunities in the equation of intelligence, people, processes and innovation, and creating competitive benefits and services which can have an important impact on the business model and even the industry as a whole, requires more than projects and more than productivity.

And it’s here that also in Industry 4.0 we find those eternal hurdles. The Boston Consulting Group, among others, identified:

  • The definition of a strategy (for Industry 4.0), challenge number one.
  • The rethinking of the organization and processes to maximise outcomes.
  • Understanding the business case.
  • Conducting successful pilots.
  • Making the organization realize action is needed.
  • Change management, so often overlooked.
  • Company culture.
  • A true interconnection of departments.
  • Talent….

They are all challenges we’ve seen in so many other areas and there are at least two we want to add (there are more):

  1. Information management excellence as it’s all about actionable intelligence and connected information and process excellence in a context of relevance, innovation and timely availability for any desired business, employee AND obviously customer goal.
  2. (Cyber)security (and privacy). The increasing number of attacks in the Industrial Internet of Things are a fact as IT and OT converge. Moreover, one of the main reasons which hold IIoT initiatives back are concerns regarding security and IIoT is, as said a key component of Industry 4.0.

On top of these challenges there are several others, practical, technological and ecosystem-related:

  • The challenges regarding the integration of IT and OT.
  • Data compliance questions.
  • Managing risk and lowering costs in uncertain times.
  • Dealing with the complexity of the connected supply chain.
  • A better understanding of IT and OT technologies and, more importantly, how they can be leveraged.
  • Altering customer and industrial partner demands.
  • Competition and the fact that Industry 4.0 champions gain a competitive benefit fast.
  • The eternal and extremely important human challenge (talent, future of work, employment,…..).

While leading manufacturers are overcoming the mentioned challenges and some already have, others will need to step up their pace. It’s not a coincidence that the Boston Consulting Group report is entitled ‘Sprinting to Value in Industry 4.0’.

Is fear of others taking the lead a good advisor? No? Do you need to start somewhere? Yes, and you can. Is it, even if fear is a bad advisor, time to sprint to value in Industry 4.0 in a world where digital transformation is a marathon with several sprints? Looking at what the best in class are doing we would say yes.

Moreover, there are some predictions you might want to look at, such as this first one from an IDC article with 10 predictions for the manufacturing industry, as summarized end 2016: By 2018, only 30 percent of manufacturers investing in digital transformation will be able to maximize the outcome; the rest are held back by outdated business models and technology.

More about the steps to move further in Industry 4.0 on this site (e.g. in industry cases), in examples across industries, in future contributions and in the presentation of the Boston Consulting Group and the accompanying article (among many other sources).

Benefits of Industry 4.0

Whether it’s Industry 4.0, Smart Industry or the Industrial Internet, there are ample benefits for manufacturers to transform the way they work.

We’ve mentioned some benefits, risks and challenges earlier in this overview but let’s look a bit closer at some of the main advantages. Several of them are also explored more in depth in other articles on this site.

The essential goal of Industry 4.0 is to make manufacturing – and related industries such as logistics – faster, more efficient and more customer-centric, while at the same time going beyond automation and optimization and detect new business opportunities and models.

Most of the benefits of Industry 4.0 are – obviously – similar to the benefits of the digital transformation of manufacturing, the usage of the Internet of Things in manufacturing, operational and business process optimization, information-powered ecosystems of value, digital transformation overall, the Industrial Internet and many other topics on our website. However, let’s summarize a few of the key benefits of Industry 4.0.

As mentioned in the section on the state of Industry 4.0, optimization of processes and of productivity is the first benefit that manufacturers see.

It’s also one of the first goals of Industry 4.0 projects. In other words: saving costs, increasing profitability, reducing waste, automating to prevent errors and delays, speeding up production to work more in real-time and in function of the overall value chain, where speed is crucial for everyone, digitizing paper-based flows, being able to intervene faster in case of production issues and so forth.

It’s the low hanging fruit, yet important. On top of the research from BCG we mentioned earlier, the signs that investments are done in these areas first are clear. Again, it’s not a coincidence that, from a spending perspective, the number one use case in which manufacturers invest their Internet of Things (IoT) budgets is manufacturing operations (a whopping $102.5 billion on a total of IoT $178 billion across all manufacturing use cases in 2016). Industry 4.0 offers various solutions to optimize, from optimized asset utilization and smoother production processes to better logistics and inventory management.

While we just mentioned speed in a context of optimization, automation and enhanced productivity, it is a benefit in many other ways as well.

A lot of the productivity improvement benefits are rather about the internal goals of costs and process optimization. Yet, at the same time several also fit in a perspective of enhanced customer-centricity.

Industry 4.0 is about the entire life cycle of products and manufacturing obviously doesn’t stand on its own. If you look at the entire value chain and ecosystem within which manufacturing operations reside there are many stakeholders involved. These are all customers. And customers also want enhanced productivity, regardless of where they sit in the supply chain. If the final customer wants good products fast and has increased expectations regarding customer experience, quality, service and products that are delivered on the exact time they want, this impacts the whole supply chain, all the way up to manufacturing and beyond. Speed is not just a competitive advantage and customer expectation in an increasingly real-time economy, it’s also a matter of alignment, costs and value creation. Moreover, customers simply expect it.

Once again the crucial role of data and information surfaces.

Industry 4.0, smart factories, supply chains, informed customers, alignment: it’s all about data, from the actual operations to the delivery of a product to an end customer and beyond.

The more data you gather early on and the more timely this data gets where it matters when it matters, the more value down the supply chain. In fact, this is the essence of one of the three dimensions of RAMI 4.0, the Reference Architecture Model Industry 4.0, which we tackle below.

When an industrial asset gets broken it needs to be fixed. That costs time, money and very often a lot of moving around by support people and engineers.

When a key industrial asset, such as an industrial robot in a car manufacturing plant gives up, it’s not just the robot that’s broken. Production is affected, costing loads of money and unhappy customers, and sometimes production can be fully disrupted. It’s everyone’s worst nightmare as business continuity is an extremely high concern.

On top of all the replacement/fixing work, resources and costs, reputation can be damaged, orders can be cancelled and with each hour that passes money is thrown away. If industrial assets are connected and can be monitored (health status monitoring, for instance) through the Internet of Things and issues are tackled before they even happen the benefits are huge. Alerts can be set up, assets can be proactively maintained, real-time monitoring and diagnosis becomes possible, engineers can fix issues, if they do occur from a distance, the list goes on. Moreover, patterns and insights are gained to optimize in areas where things seem to have issues more often and a world of new maintenance services opens up as we’ll see. No wonder that asset management and maintenance are the second largest area of IoT investments in manufacturing.

We mentioned that customers want speed. However, that doesn’t mean they are ready trade quality for speed, well on the contrary.

If you have everything in your production system and its broader environment hooked up with sensors, software, IoT technologies, systems of insight AND the customer, you can also enhance quality of your products. Automation definitely plays a big role here and so do the typical components of cyber-physical systems (more below) and the Internet of Things whereby quality aspects can be monitored in real-time and robots reduce errors.

On the flip side and one of the risks and challenges to tackle, as mentioned earlier: the more you automate, the less work for people, in theory. And the same goes for other mentioned benefits such as maintenance (the less you need engineers for support, the less support engineers you need). It’s a dilemma and known issue which we’ll cover later. In the meantime do know that robots are not going to take all human jobs over soon. Ample 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 fancy term for advanced collaborative robots or put more simply: robots that fit a collaboration between man and machine).

Talking about people, the human (and social) dimension is ubiquitous in Industry 4.0. Moreover, if we look at the possibilities and benefits, that human, social and even environmental aspect is key in the goals of Industry 4.0.

Improving working conditions based on real-time temperature, humidity and other data in the plant or warehouse, quick detection and enhanced protection in case of incidents, detection of presence of gasses, radiation and so forth, better communication and collaboration possibilities, a focus on ergonomics, clean air and clean factory initiatives (certainly in Industry 4.0 as the EU wants to be leading in clean air and clean anything technologies), the list goes on.

We all know it: consumer behavior and preferences have changed. Digital tools have changed the ways we work, shop and live.

People have also become more demanding, among others with regards to fast responses and timely information/deliveries as mentioned earlier. On top of that consumers also like a degree of personalization, depending on the context. Take sports shoes, for instance. Once a few colors of the same shoe were enough, know we want the ability to customize them in whatever way.

On top of that another phenomenon is taking place and it does disrupt traditional supply chains. Consumers increasingly get (and want) possibilities to have a direct interaction with a brand and its manufacturing capability. Digital platforms to customize products as mentioned, shortened routes between production and delivery, possibilities to co-create and so on. In many manufacturing environments these things already happen. And it’s not just in a consumer environment. We increasingly see customization in a B2B context as well, even if it’s just to stick a label, add a custom feature or adapt any characteristic of the product whatsoever.

If you want to offer these services at scale and even turn them into a competitive advantage, automation and several technologies and processes in industry 4.0 become a necessity. A real-life example without disclosing the details: a large bank wanting specific office equipment to use across all its branches (customer-facing context) with its own look, feel and features as part of a rebranding. There are plenty more examples.

Now that we speak about competitive benefits and customization we also need to tackle agility, scalability and flexibility.

The same scalability and agility which we expect from supporting IT services and technologies, such as the cloud, are expected in manufacturing. This is partially related with the previous topic of customization but mainly is about leveraging technologies, Big Data, AI, robots and cyber-physical systems to predict and meet seasonal demand, fluctuations in production, the possibility to downscale or upscale; in other words: all the adjustments that are sometimes more or less predictable, can be made more predictable or are not predictable but can be handled thanks to increased visibility, flexibility and a possibility to leverage assets in function of optimal production requirements from a perspective of time and scale.

Digital transformation, as you can read in our digital transformation strategy overview, is a matter of many levels, steps and capabilities.

You can transform processes, specific functions, customer service, experiences and skillsets but in the end true value is generated by tapping into new, often information-intensive, revenue sources and ecosystems, enabling innovative capabilities, for instance in deploying an as-a-service-capacity for customers, advanced maintenance services and so on.

In the end, Industry 4.0 is also about that. It’s a topic we wrote about very often. You can read more about it in our article on the digital transformation of manufacturing.

As mentioned previously, it’s important to point out that Industry 4.0 is still mainly a vision. Does this mean it is just a vague idea? No, on the contrary.

What we do see indeed though is that most organizations are still in the early stages of preparations for Industry 4.0 and mainly working ad hoc for now. Yet, the vision of Industry 4.0 is far more studied and documented that that of other evolutions.

Industrie 4.0 is a vision AND a reality with a documented strategic roadmap towards realizing the vision

Let’s compare digital transformation and the role in it of the Industrial Internet of Thing, which along with evolutions in mechanics, engineering and manufacturing, essentially are what Industry 4.0 is about.

Digital transformation, although being academically looked upon and despite the existence of numerous digital transformation frameworks and roadmap strategies, which are developed by numerous people, has no universal definition nor clear industry-wide approach. The same goes for the implementation of the Industrial Internet of Things.

Just like digital transformation and the Industrial Internet of Things, adoption of Industrie 4.0 happens in the individual context of an organization. However, Industry 4.0, which is about more than automation in manufacturing and ultimately also shows a vision of transformation in the end, is thoroughly studied, prepared and presented by a big platform with academia, companies and far more as it was a clear mandate.

In essence this means that in Industry 4.0 there is a body of work, reference models, roadmaps and well-described components before the actual implementations really happened. That is pretty unique.

So, just like digital transformation, Industry 4.0 requires a staged approach whereby the initiatives in the earlies maturity stages and areas ultimately lead to the realization of an integrated vision and reality. Yet, as opposed to digital transformation this vision and reality is far more studied, documented and standardized (despite the mentioned need to work in the context of the individual business as well).

Industry 4.0 maturity models and roadmap basics

In the Industry 4.0 maturity models there are several ways to look at the mentioned staged approaches. One such maturity approach looks at the information and actual operations and manufacturing systems perspective with autonomous machines and systems as true Industry 4.0.

In this gradual approach, whereby each stage builds upon the next one and adds more value, we move from data to information to knowledge to wisdom and action from a data perspective. Indeed, the good old DIKW model.

From the perspective of systems and equipment/machines these stages correspond with, respectively seeing what is happening (data), knowing why it’s happening (analytics, knowledge), predicting what will happen (based upon the patterns and capabilities we developed before and AI) to the ultimate step Industry 4.0 strives for: an autonomous reaction by autonomous machines within the self-optimizing Industry 4.0 systems.

A second maturity approach revolves more around the business as such and corresponds with what you would typically see in any project.

What do we want to achieve and what do we have today (assess), where do we want to go and what are the missing links to get there (called the methodological analysis in Industrie 4.0, of which gap analyis is part) and then the deployment of a strategic plan with a clear roadmap with regards to processes, security, skills, technologies and implementation.

And, as is always the case this is of course followed by monitoring and improvement.

The building blocks of Industry 4.0: cyber-physical systems

Cyber-physical systems (CPS) are building blocks in Industry 4.0 on one hand and part of the Industry 4.0 vision on the other.

Cyber-physical systems are combinations of intelligent physical components, objects and systems with embedded computing and storage possibilities, which get connected through networks and are the enablers of the smart factory concept of Industry 4.0 in an Internet of Things, Data and Services scope, with a focus on processes.

Simply put, as the term indicates, cyber-physical systems refers to the bridging of digital (cyber) and physical in an industrial context.

Cyber-physical systems (CPS) in the Industry 4.0 vision

This might still seem complex but, then again, cyber-physical systems are complex. Moreover, the term isn’t new and is better known in an engineering and industry context.

It fits more in the Operational Technology (OT) side of the converging IT/OT world which is typical in Industry 4.0 and the Industrial Internet. So, if you want to understand Industry 4.0 or the Industrial Internet, you’ll need an understanding of some essential operational, production and mechanics terms.

Cyber-physical systems in the Industry 4.0 view are based on the latest control systems, embedded software systems and also an IP address (the link with the Internet of Things becomes clearer, although strictly both are not the same but they certainly are twins as we see in the next ‘chapter’.

In the Industry 4.0 context of mechanics, engineering and so forth, cyber-physical systems are seen as a next stage in an evolution of an ongoing improvement of enhancement and functions integration.

Looking at Industry 4.0 as the next new stage in the organization and control of the value chain across the lifecycle of products, this ongoing improvement in which CPS fits started from mechanical systems, moved to mechatronics (where we use controllers, sensors and actuators, more terms that are familiar in IoT) and adaptronics, and is now entering this stage of the rise of cyber-physical systems.

Cyber-physical systems essentially enable us to make industrial systems capable to communicate and network them, which then adds to existing manufacturing possibilities.

They result to new possibilities in areas such as structural health monitoring, track and trace, remote diagnosis, remote services, remote control, condition monitoring, systems health monitoring and so forth.

And it’s with these possibilities, enabled by networked and communicating cyber-physical modules and systems, that realities such as the connected or smart factory, smart health, smart cities, smart logistics etc. are possible as mentioned previously.

In the original definitions, going back over a decade, IP addresses where not specifically mentioned in cyber-physical systems.

In 2008, Professor Edward A. Lee from the University of California, Berkeley, defined Cyber-Physical Systems as follows: “Cyber-Physical Systems (CPS) are integrations of computation and physical processes. Embedded computers and networks monitor and control the physical processes, usually with feedback loops where physical processes affect computations and vice versa”.

On his page on the Berkeley website, Professor Lee links to where you find his definition and a CPS concept map in the form of a mind map where you can click the various components to read more. For the German Industrie 4.0 academia and industry people, CPS (and that bridging of cyber/digital and physical) was key in Industry 4.0.

Cyber-physical systems also include dimensions of simulation and twin models, smart analytics, self-awareness (self-configuration) and more . We’ve tackled some of these topics, including digital twins, previously.

Hopefully, the essence of the concept, context and reality of the evolution towards cyber-physical systems has become a bit clearer now. Note: there is a difference between cyber-physical systems and cyber-physical manufacturing systems or cyber-physical production systems (CPSS) where we move from the technological component to the far more important process and application dimension.

Next, we take a deeper look into the Internet of Things and its place in Industry 4.0. You’ll notice that both are virtually twins.

Before doing so we summarize some key characteristics of cyber-physical systems as they are related with the Internet of Things:

  • Cyber-physical systems are seen as a next evolution in manufacturing, mechanics and engineering. The essential dimensions are the bridging of digital and physical, which is possibly thanks to Internet technology, and the bridging/convergence of Information Technology and Operational Technology.
  • Cyber-physical systems can communicate. They have intelligent control systems, embedded software and communication capabilities as they can be connected in a network of cyber-physical systems.
  • Cyber-physical systems can be uniquely identified. They dispose of an IP (Internet Protocol) address which means that they use Internet technology and are part of an Internet of Everything in which they can be uniquely addressed (each system has an identifier).
  • Cyber-physical systems have controllers, sensors and actuators. This was already the case in previous stages before cyber-physical systems (mechatronics and adaptronics); however as we’ll see with the Internet of Things it plays an important role.
  • Cyber-physical systems are the basic building blocks of Industry 4.0 and the enablers of additional capabilities in manufacturing (and beyond) such as track and trace and remote control (more about these capabilities in the next section on CPS and the Internet of Things).
  • The capabilities which are possibly thanks to cyber-physical systems enable smart factories, smart logistics and other smart areas of applications, among others in energy, oil and gas, and logistics.

As promised, time for the Internet of Things. The Internet of Things (IoT) is omnipresent in Industry 4.0 and its international counterparts, as mentioned previously.

As you can read on our page on the Industrial Internet of Things (IIoT) and deduct from the graphic above on cyber-physical systems, CPS essentially is mainly about the Industrial Internet of Things.

The presence of an IP address by definition means that cyber-physical systems, as objects, are connected to the Internet (of Things). An IP address also means that the cyber-physical system can be uniquely identified within the network. This is a key characteristic of the Internet of Things as well.

The main Internet of Things use case in manfacturing, from a spending perspective, concerns manufacturing operations

Cyber-physical systems are also equipped with sensors, actuators and all the other elements which are part of the Internet of Things. Cyber-physical systems, just like the Internet of Things need connectivity. The exact connectivity technologies which are needed depend on the context (in both).

The Internet of Things consists of objects with embedded or attached technologies that enable them to sense data, collect them and send them for a specific purpose. Depending on the object and goal this could be capturing data regarding movement, location, presence of gasses, temperature, ‘health’ conditions of devices, the list is endless. This data as such is just the beginning, the real value starts when analyzing and acting upon them, in the scope of the IoT project goal.

IoT devices can also receive data and instructions, again depending on the ‘use case’. All this applies to cyber-physical systems as well, which are essentially connected objects. There are more similar characteristics but you see how much there is in common already.

Moreover, the new capabilities which are enabled by cyber-physical systems, such as structural health monitoring, track and trace and so forth are essentially what we call Internet of Things use cases.

In other words: what you can do with the Internet of Things. Some of them are used in a cross-industry way, beyond manufacturing.

Below are two examples of CPS-enabled capabilities we tackled previously and how they really are IoT uses cases.

Track and trace possibilities in practice lead to multiple IoT use cases in, among others, healthcare, logistics, warehousing, shipping, mining and even in consumer-oriented Internet of Things use cases. There are ample applications of the latter with numerous solutions and technologies. You can track and trace your skateboard, your pets, anything really, using IoT.

Structural health monitoring is also omnipresent, mainly across industries such as engineering, building maintenance, facility management, etc. With the right sensors and systems you can monitor the structural health of all kinds of objects, from bridges and objects in buildings to the production assets and cyber-physical assets in manufacturing and Industry 4.0.

Smart factories, smart plants and smart applications

The new capabilities, of which we just mentioned two and which are possible thanks to CPS in the Industry 4.0 view, in turn enable smart plants, smart factories and anything smart.

What is a core enabler of smart logistics and so forth? Indeed, the (Industrial) Internet of Things, beyond its simple aspects of sensors, actuators, communication capabilities and data collection/analytics. You can perfectly compare this with the Internet of Everything view of connected objects, people, processes and data as the building blocks of smart applications.

It is another key similarity between the CPS view of industry 4.0 and the reality of the Internet of Things, which is key in Industry 4.0.

To conclude: in fact, you can call cyber-physical systems the (albeit advanced) things in the Industrial Internet of Things in manufacturing. So, CPS and IoT are de facto more than twins.

A key component of the Industrial Internet of Things is connectivity. According to research, industrial manufacturers still have some catching up to do in regards with connectivity overall.

Among others, the adoption of cloud-based services and the connection of legacy systems to digital networks is lagging somewhat behind. Yet, as IIoT strategies are being envisioned and designed, the number of Industrial Internet of Things connections is growing rapidly and changes occur in the types of connectivity solutions that are used.

In 2017 research from ABI Research, it is estimated that in 2017 there will be 13 million extra (new) wireline and wirelines connections across the globe. In total this would bring the number of Industrial IoT connections to 66 million. In the years after, this growth continues and even accelerates (18 million new connections per year by 2021).

Looking at the various types of Industrial IoT connection connection solutions in manufacturing and thus Industry 4.0, it is expected that revenues from cellular and satellite connectivity fees will reach more than $138 million in 2017.

The major part of connections consists of fixed line deployments but wireless is growing and will account for approximately a quarter of all new connections in 2017. Moreover, on the longer term it is expected that LPWA will be the fastest grower and that the shift to 4G LTE continues.

Research Director Jeff Orr points ou t that with the lowering costs in storage and processing, Industry 4.0 comes in reach of all manufacturers. With the evolutions in the connectivity options and solutions in that crucial component of Industry 4.0, which the Industrial Internet of Things is, this is even more the case.

While, as mentioned the Industrial Internet Consortium has a framework, called IIRA (Industrial Internet Reference Architecture), German ‘Plattform Industrie 4.0’ developed the so-called Reference Architectural Model Industrie 4.0 (RAMI 4.0).

RAMI 4.0, although originating from Germany, just as Industrie 4.0, is playing an increasing role in other countries as well. As a matter of fact, ‘Platfform Industrie 4.0’ is seeking alignment at European levels and with other countries across the globe.

Even if some EU countries use different terms such as intelligent factory, future industry, digital production or smart manufacturing, the European Commission (EC) is also intervening.

The 3-dimensional RAMI 4.0 model shows that the production object must be tracked across its entire life cycle (video ZVEI, see below)

Early 2017, a forum was held in the scope of the EC’s ‘Digitizing European Industry’ project. Industry 4.0 and RAMI 4.0 are also clearly mentioned within various programs on the website of the EC (and a PDF with the essence of the Reference Architectural Model Industrie 4.0 is available on it, not without reason).

At the mentioned forum, the so-called ‘Stakeholder Forum’, held early 2017, international collaboration around Industry 4.0 was one of the topics. ‘Plattform Industrie 4.0’ used the occasion to further expand bilateral relationships with, among others the French Industry of the Future Alliance (Alliance Industrie du Futur) and Italy’s Intelligent Factory project (Fabbrica Intelligente). Outside of the EU, partners include the mentioned IIC (Industrial Internet Consortium) and Japan’s Robot Revolution Initiative (meanwhile, Japan announced its all-encompassing Society 5.0 initiative at the CeBIT 2017 tradeshow).

An overview of the ongoing acceptance and leverage of Industrie 4.0 technologies, concepts and principles, as mentioned previously, at the bottom of this page with over a dozen Industry 4.0 initiatives across the globe.

If you are looking for some examples of Industry 4.0 cases in practice, it’s probably interesting to know that you can watch a map, translated in English by ‘Platfform Industrie 4.0’, right before the forum.

Click on a place on the map and read more about the specific case (for now only German examples).

What are some of the key aspects you need to know about RAMI 4.0 (the architectural model overviewis embedded below)?

First, know that there are two documents which laid out the foundations of Industry 4.0 and RAMI 4.0.

The Industrie 4.0 workgroup findings report

In 2013, the so-called “Umzetsungsempfehlungen” document was published. It’s essentially the report of the ‘Industrie 4.0’ workgroup that, among others covered principles and foundations, including:

  • Horizontal integration across value-added networks.
  • Vertical integration and networked/connected production systems
  • The technologies for CPPS (cyber-physical production systems)
  • The consistency of engineering across the entire value chain.
  • The new social infrastructures of labor/work.

We mention these topics of that first document as we’ll tackle them more in depth.

The Industrie 4.0 strategic implementation document: where RAMI 4.0 comes in

The second document, the “Umsetzungsstrategie”, a document with the recommendations for the strategic translation and implementation of Industry 4.0, was published in 2015 and contains the RAMI 4.0 model, the Industry 4.0 components and a research roadmap for implementation.

It’s this document and more specifically, RAMI 4.0 AND the Industry 4.0 components which we tackle here. The RAMI 4.0 architecture reference model is explained using 3 dimensions:

  1. The first dimension consists of the hierarchy levels.
  2. The second dimension covers the life cycle and value stream.
  3. The third and final dimension covers the so-called RAMI (architecture) layers.

The hierarchy dimension consists of 7 aggregation levels, being 1) the connected world, 2) the enterprise, 3) work centers, 4) stations (or machines), 5) control devices, 6) field devices (sensor and actuators) and 7) products.

Important to note: while traditionally these levels are seen as a “real hierarchy” and depicted as a pyramid, in Industry 4.0 they are more conceived and depicted as a mesh in a reality of ubiquitous connectivity of everything, including processes, devices, products, organizations, ecosystems and so forth. In the pyramid that shows Industry 3.0 there are only 6 levels with the enterprise at the top. While it’s true that the connected world is far more connected from a technology and business perspective, we must point out that there is such a thing as the extended enterprise with its ecosystems since long before anyone even talked about Industry 4.0.

The hierarchy dimension is what we covered several times in our articles on ubiquitous connectivity and digital transformation but in a different scope of hierarchy with smart products and smart factories as part of this connected world.

It also about technologies (where we similar decentralizations all across the board) (IT and especially OT) and about the ubiquitous interaction of participants across hierarchy levels, whereby the product is seen as part of the network.

The life cycle and value stream dimension

The life cycle and value stream dimension, as the term already describes, covers the various data mapping stages across relevant life cycles in RAMI 4.0 and across the entire value chain and the various processes (and stakeholders).

We’ll cover this more in depth later as it’s key in the data part, starting from the pre-production development product data model, starting at the idea and development (data on, among others, , all the way across further stages downstream, including actual production and the various processes until the production object is end of life and gets recycled or trashed). The idea: the more data early on, the more value later on.

The architectural layer

The third dimension, the architecture layers, consists of 6 components: business, functional, information(a), communication, integration and asset.

Essentially we’re talking about 1) the enterprise and its business processes, 2) the functions of assets, 3) the required data, 4) communication as access to information, 5) integration as, quote, ‘transition from real to digital world and 6) assets as physical things in the real world.

Bring all three dimensions together and, on top of a nice visual, you have a 3D service-oriented architecture. More in the video from German ZVEI (the German Electrical and Electronic Manufacturers’ Association) below. It is by far the best RAMI 4.0 explainer you’ll find in English in a video format.

Below is a list with more resources in case you want to dive deeper into the reference architecture model and the components of Industry 4.0. There is also a paper regarding the interoperability of the frameworks of the Industrial Internet Consortium and the Industry 4.0 Platform.

Industrie 4.0 principles: horizontal and vertical integration

After this introduction to RAMI 4.0, which as mentioned was laid out in the 2015 document with recommendations for Industry 4.0 strategies and implementations, let’s take a look at some other so-called Industry 4.0 principles.

These were established in the 2013 report in which the Industrie 4.0 workgroups presented their findings on, among others those principles and foundations. Remember that, as mentioned and as we’ll cover more in depth, those recommendations, principles and so forth mainly were about manufacturing but that de facto Industry 4.0, its principles, vision and elements are going beyond manufacturing – and will continue to do so as Industry 4.0 moves from vision to reality in meeting the inevitable transformation of other industries as they are already taking place today.

Despite the fact that there is a difference between horizontal and vertical integration the goal is the same: ecosystem-wide data information between various systems and across all processes, using data transfer standards and creating the basis for an automated supply and value chain.

Horizontal integration refers to the integration of IT systems for and across the various production and business planning processes.

In-between these various processes there are flows of materials, energy and information. Moreover, they concern both the internal as external (partners, suppliers, customers but also other ecosystem members, from logistics to innovation) flows and stakeholders.

In other words: horizontal integration is about digitization across the full value and supply chain, whereby data exchanges and connected information systems take center stage. As you can imagine this is not a small task. For starters, within organizations there are still quite some disconnected IT systems. This is a challenge for all organizations, industrial or not. If you start looking at seamless integration and data exchange with suppliers, customers and other external stakeholders, the picture becomes even more complex.

Also keep in mind the life cycle and value stream dimension of RAMI 4.0 here where we talked about the importance of early data collection and provisioning.

Whether it concerns product data or information about the various mentioned and other processes across the horizontal value chain (so, the path from supplier and production to end customer and/or other stakeholders/partners), there is still quite some work to do in this regard.

Nevertheless, it is critical for Industry 4.0 and for business overall. The benefits and drivers for this need for horizontally connected information systems are pretty comparable to those we find in information management, as are the disadvantages if systems are not integrated.

We’re talking about customer service and satisfaction (with many customers in supply chains), planning, employee productivity and satisfaction, speed and so forth. Compare it with information management challenges in an insurance scenario: if back-office information on, for instance a claims process, is not connected with the front end, customer service agents can’t help the customer fast enough if he/she seeks information or help on the (status) of the process. It’s exactly the same in Industry 4.0 and manufacturing. We’re just talking about more stakeholders, highly interdependent processes and stakeholders, far more processes and data and so forth.

It’s a no-brainer that horizontal integration helps with horizontal coordination, collaboration, cost savings, value creation, speed (as an enabler of smooth service and operations but also of faster time to market and worker’s efficiency) and the possibilities to create horizontal ecosystems of value, based on information.

However, it’s not because it’s a no-brainer that it’s easy. Ask any organization in any industry. Last but not least: we’re not just talking about information. It’s the knowledge, insights and action which matter in the end.

Whereas horizontal integration is about IT systems and flows in the supply/value chain and the various processes happening across it, vertical integration has a hierarchical level component.

In other words: it’s about the integration of IT systems at various hierarchical production and manufacturing levels, rather than horizontal levels, into one comprehensive solution.

These hierarchical level are respectively the field level (interfacing with the production process via sensors and actuators), the control level (regulation of both machines and systems), the process line level or actual production process level (that needs to be monitored and controlled), the operations level (production planning, quality management and so forth) and the enterprise planning level (order management and processing, the bigger overall production planning etc).

Typical solutions and technologies in this vertical integration include PLCs which control manufacturing processes and sit on the control level, SCADA which enables various production process level and supervisory tasks and is de facto commonly used in industrial control systems, MES or manufacturing execution systems for the management level and ERP for the enterprise level, which is the highest level in this hierarchical picture.

Industry 4.0 and technologies

Previously in this overview of Industry 4.0 we touched upon several technologies. If you look at the presentation and data from the Boston Consulting Group, you’ll see some of the main technologies in Industrie 4.0.

As a reminder: BCG mentions advanced robotics, additive manufacturing, augmented reality, simulation, horizontal/vertical integration, the Industrial Internet (of Things), cloud, cybersecurity and, finally Big Data and Analytics.

Most of them are really umbrella terms for several technologies. We already tackled horizontal and vertical integration, cyber-physical systems and the Industrial Internet of Things as really vast realities with many technologies and components before on this page (and elsewhere). We also have literally dozens of articles on other evolutions in the mentioned convergence and application of nine digital industrial technologies as BCG calls them.

Yet, instead of sending you to other pages and taking into account the specific aspects of some technologies in an industrial scope we’ll zoom in on a few more which are rather typical in manufacturing and industrial markets. Those that are less typical (with typical ones being the integration of IT and OT, additive manufacturing, industrial robots and so forth) are probably the ones you are looking at today: IoT, Big Data, the cloud, maybe 3D-printing etc. They are the technologies that we meet in IDC’s so-called third platform with transformational pillars and innovation accelerators.

So, what technologies are really key to Industry 4.0? It depends but the Internet of Things is clearly critical as it is what makes most so-called Industry 4.0 levers (see below) possible.

Security is also an inherent part of the Industrie 4.0 vision. In fact, most of the mentioned technologies are essential as they are inevitably connected and interdependent. So, where do we start?

The best way to start is by looking at your goals and challenges and at the capabilities you need on your Industry 4.0 journey.

Big Data, analytics, the cloud (and the fog), AI and simulation, to name a few, are about the adaptability, flexibility, modularity, scalability and rapid deployment and integration capabilities that we want to see with Industry 4.0. These capabilities come back in many of the Industry 4.0 resources we previously listed (such as Gartner’s page) and are also means to an end.

Do note that several consulting firms and analysts zoom in on other digital technologies as enablers of Industry 4.0. Mobile devices and technologies are just one example. More advanced interfaces in the relationship between human and machine are another (or better: new interfaces in the relationship between human and technologies as machines makes us overlooks the critical software dimension in a world where software as they say is eating that world. Think artificial intelligence agents and bots or in another context phenomena such as Robotic Process Automation or RPA).

Obviously you can’t implement all technologies at once, nor should you. We looked at the strategic dimension of Industry 4.0 before and will continue to focus on it.

If you want to have a more value-oriented and purpose-driven view at the technological journey, you might want to check out the so-called digital compass which McKinsey made a few years ago, especially the value drivers in it.

For the many organizations who are still in the beginning of their Industry 4.0 journey it might look a bit overwhelming but when you look closer it isn’t.

At the center are the value drivers which we all know and touch upon 8 areas/dimensions: time to market, matching supply and demand, quality, inventories, labor, asset utilization, resource/process and service/aftersales.

So, these are really some main areas where, in the scope of that compass, you could create more value towards one or more stakeholders at the same time. Because obviously, it’s not just about these 8 dimensions as such but about the question how you can improve the various processes and experiences of those involved with a clear connection to tangible value.

The second part of the compass shows the Industry 4.0 levers which are connected with the value drivers. As an example: in order to better utilize your assets, remote monitoring and control and predictive maintenance can help you achieve that goal.

From a technology perspective, it’s a matter of knowing what technologies are needed to ‘do’ remote monitoring/control and/or predictive maintenance and it’s here that we start looking at technologies such as Big Data analytics and of course the Internet of Things as you can’t get data from your assets for monitoring/maintenance purposes if they aren’t connected with the purpose of doing so.

Although companies such as McKinsey and many others are absolute leaders in Industry 4.0 it remains important to start from your individual goals and means to achieve them, after having conducting analysis and drafting a plan and roadmap that serves your business.

In that sense we say the exact same thing regarding Industry 4.0 as we did about digital transformation: the technologies are enablers and there is far more to look at.

While that might sound like common business sense it is often forgotten. So, be careful with an overemphasis on ‘the technologies you really should have’ and also be careful with the many models, frameworks and compasses out there.

The reality of Industry 4.0 ad of supply chains looks like a big complex mesh with loads of moving connections, nodes and dimensions if you try to visualize it. Yet, technologies and Industry 4.0 are about reducing our complexity and that of our processes, partners, customers and supply chains in a prioritized and staged way. It’s in this exercise of looking at our complexity that the capabilities are built to innovate and develop capabilities and flexibility, which in the end are mainly about dealing with and removing complexity with novel approaches for our various stakeholders by tapping into the opportunities we detect in a complex reality.

And that requires a different approach for each organization, even if there are many common lessons and strategies we can learn from. Yet, there is never a one size fits all. Take a look again at the digital compass of McKinsey, for example. You might want to improve customer service; the dark green part of the compass. But that doesn’t mean that predictive maintenance, remote maintenance and virtually guided self-service are the solutions to make it happen. The labor part, for example, is also key in customer service. And so is the inventories piece. And what about time to market and quality? Or the flexibility in utilizing your assets. They all play a role in better servicing the customer. The ways that work best for your customers and your business depend on how all these levers and all the other service aspects that aren’t necessarily even mentioned as they’re not part of that Industry 4.0 compass, interact, what your customers want and who they are today and could be tomorrow.

That’s why Industry 4.0, just like digital transformation, is by definition a holistic given and can’t be captured in an illustration, whether it’s one we made, McKinsey’s digital compass or any framework out there. Take them for what they are: instruments and compasses to think about dealing with complexity and offering ideas or approaches which we can leverage in our own, increasingly digital, reality of challenges and opportunities, in which industrial transformation and technologies fit.

Industry 4.0 has gone global: Industrie 4.0 initiatives and evolutions around the world

As we mentioned in the introduction of our article and in the scope of the RAMI 4.0 reference architecture model for Industrie 4.0, the Industry 4.0 view and concept has clearly gone global and continues to do so.

In the US, Industry 4.0 is de facto having an important impact on smart manufacturing initiatives and there is the collaboration with the Industrial Internet Consortium.

Moreover, there is an increasing number of organizations and countries where Industry 4.0 is becoming adopted. Examples include the UK (Industry 4.0 and the work around 4IR, short for 4th industrial revolution by the EEF), Japan (where there is, as mentioned already a collaboration with Japan’s Robot Revolution Initiative), China (where the Industry 4.0 outline is at the basis of ‘Made in China 2025’) and the numerous EU initiatives of which we mentioned some previously. On March 23rd 2017, the EU alone looked at plans to align the already 12 existing and 9 coming national industry transformation initiatives. Essentially all of them are leveraging the Industry 4.0 concept, regardless of their many different names.

However, the global expansion of Industrie 4.0 is not just a matter of government initiatives or agreements. It is also a result of an increasing focus among industrial giants and leading consulting firms on Industry 4.0.

From PwC and Accenture to McKinsey; they’re all heavily involved in Industrie 4.0. One example of an industrial giant, from outside the EU, that is heavily involved in Industrie 4.0 is Infosys that supported the plans of the German Academy of Science and Engineering, Acatech (which coined the term Industrie 4.0), to create an Industrie 4.0 Maturity Index.

The consortium which was created in the Spring of 2016 to get the Industry 4.0 Maturity Index ready by April 2017, includes research institutions and several industry bodies, as well as companies such as Infosys.

Expect a range of announcements and partnerships to further drive the Industry 4.0 concept further across the globe. Last but not least, also remember that we’re not just seeing a global/regional expansion of Industry 4.0: there is also an increasing adoption of Industry 4.0 principles and technologies across vertical markets beyond manufacturing (healthcare, utilities, smart cities, oil and gas etc.).

Industrial Data Space: linking IoT and smart services in Industry 4.0 and beyond

Various research organizations, with a leading role for the Fraunhofer Institute, and the German government are pushing a reference architecture model and virtual construct for secure data sharing based on standardized communication interfaces.

That is a mouthful to say that Industrial Data Space, which aims to define the data architecture for the connection of smart services and IoT in a landscape of ever more data wants to become a global standard. Industrial Data Space focuses on the connection of several existing platforms and wants to enable partners to share data for digital transformation purposes within a clear pre-defined model whereby data sovereignty and data security are among the key focus areas.

The Industrial Data Space Association is conducting talks with other organizations with similar architecture frameworks, countries outside Germany and the EU in the scope of the movement towards a European Data Space. Although there is an important focus on Industry 4.0, the Industrial Data Space stretches across other industries as well. The illustration below from the presentation of Prof. Dr. Jan Jürjens on the website of the EU (which can be downloaded in PDF here) shows some of the core principles of Industrial Data Space.

Energy efficiency, power management and Industry 4.0

The fourth industrial revolution needs to be powered. Yet, the sources of power and how we leverage them inside industrial settings are changing.

Energy efficiency and power management are simply inherent to Industry 4.0. The focus on ecology, cost savings, changing regulations, the sheer possibility to create, combine, measure and optimize in entirely new ways, using pervasive metering, sensors, IoT and data analytics, the list goes on.

Moreover the energy sector as such goes through its digital transformation, also known as Energy 4.0. And obviously there is the need for maintenance and asset management, the increasing emphasis on continuity and productivity in a real-time economy, whereby systems can’t fail and power availability and reliability are essential, and the reality of the connection of new power sources. This also goes for the power critical facilities and buildings in Industry 4.0, from airports to factories and other buildings where energy efficiency and Industry 4.0 go hand in hand.

More articles and resources relating to Industry 4.0

Below are some more articles on our website which tackle aspects, components and evolutions that are relevant for Industry 4.0. Click the headlines for the desired article.

Digital transformation in manufacturing 2017 and beyond Industry 4.0, although having expanded to other industries is still primarily a matter of the manufacturing industry.

In this article on the digital transformation and digitization of manufacturing we tackle the evolutions, challenges and accelerators and look into research and data for 2017 and beyond with a worldwide focus.

The EU and Industry 4.0: boosting manufacturing and industry transformation In March 2017, the EU announced a series of initiatives to boost Industry 4.0 across the European Union.

In this article we look at, among others, the spending plans, the several national initiatives in the EU and in the UK and the creation of a European platform. Industry 4.0 initiatives are ubiquitous in EU member states and beyond.

Industry 4.0 in the US and beyond: Industrial Internet With a central role for the Industrial Internet of Things, US manufacturing giant GE (General Electric) developed what it called the Industrial Internet.

Along with several other leading companies, universities, consulting firms and so forth the Industrial Internet Consortium or IIC was launched. This large association includes many US organizations but also companies from across the globe, including from Germany.

The Industrial Internet Consortium works together with other associations and with the Industry 4.0 Platform as both have similar goals. This includes collaborations on standards and frameworks. In this article you learn more about Industrial Internet and the Consortium.

Japan: from Industry 4.0 to Society 5.0 Japan has its own industrial revolution and collaborates with the Industry 4.0 platform.

In March 2017, however, Japan announced a far-reaching program that aims to go far beyond the transformation of manufacturing and any other industry. Society 5.0 includes Industry 4.0 but touches upon Japanese society in the broadest possible sense, including culture, legislation and even philosophy.

Industry 4.0 in the UK: on the road to 4IR Manufacturing companies in the UK feel prepared for Industry 4.0.

However, on top of traditional barriers to move in the journey towards Industrie 4.0, the UK also has specific challenges, including the need for a more industry-wide plan and readiness strategies. Associations such as the EEF are helping manufacturers to take that journey of what is called 4IR in the UK (4th industrial revolution). This article provides an in-depth overview.

Industry 4.0 across the globe: gaps in Industry 4.0 readiness and the Industrie 4.0 Maturity Index An overview of research, conducted in 2015, about the state of Industry 4.0 across the globe.

In this article we look at the research’s findings, which cover China, the US, the UK, France and Germany, as well as the Industrie 4.0 Maturity Index which builds upon it, was announced in 2016 and is available since April 2017.

Industry 4.0: launch of a global network of Industrie 4.0 Digital Capability Centers As Industry 4.0 is going global, initiatives are taken to enable manufacturers to learn about Industry 4.0 in a practical way.

One of those initiatives, launched in March 2017, is the creation of a network of so-called Digital Capability Centers (DCCs) by McKinsey, academic institutions and companies such as PTC whereby a realistic factory environment serves as a showcase and test environment. There are Industry 4.0 DCCs in Germany, Singapore, China, the US and Italy.

Industrial data and analytics: the challenges and benefits, with an example Just as in most other industries, data is ubiquitous in the industrial markets of Industry 4.0. One can even wonder if Industry 4.0 isn’t all about data, in combination with analytics, artificial intelligence and other technologies where relevant.

The problem with industrial data is that, just as is the case with other forms of data and information in any area of information management, tends to reside in silos such as ERP and industrial control systems but also in applications that really aren’t fit for an advanced use. More about the role of data and an example of applying data, analytics and AI in the oil and gas industry.

Augmented reality and virtual reality in Industry 4.0 In bridging the digital and physical worlds, a range of technologies is used in Industry 4.0: from the Internet of Things and cyber-physical systems to augmented reality.

Spending on virtual reality and augmented reality is expected to grow strongly through 2021. Where discrete manufacturing and process manufacturing already account for a large part of AR/VR spending in 2017, the use cases of augmented reality in Industry 4.0 are evolving. On-site assembly and safety and process manufacturing training are important use cases, yet maintenance will increasingly become key. On top of that, applications such as prototyping, product design and simulations/test provide the case for AR/VR in Industry 4.0 as hardware and software matures.

Top image: Shutterstock – Copyright: MNBB Studio – All other images are the property of their respective mentioned owners. – Images used for first infographic – copyright: respectively elenabsl and Maxfarruh All other images are the property of their respective mentioned owners.


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