ometime in the last decade, manufacturing entered a period of transformation.
New technologies found their way onto the shop floor in force. Advances in computer processing power and data storage resulted in new manufacturing use cases for a range of products. A climate favorable to development made prohibitively expensive technologies affordable and scalable. In rapid succession, new industrial applications emerged for artificial intelligence, cloud computing, Internet of Things connectivity, big data analytics, quantum computing, 3D printing, cyber-physical systems, and a host of other technologies.
Together, these technologies inaugurated a Fourth Industrial Revolution.
Also known as Industry 4.0, manufacturing is changing at a rate and scale comparable to the advent of steam power or software-driven automation. The impacts of this digital transformation have been profound, and the potential remains great. Gartner estimates the markets for a number of key Industry 4.0 products (advanced cyber security, augmented reality) to hover between $150 and $200 billion. Over a dozen others (additive manufacturing, wearable sensors) have a conservative market value of $2 to $20 billion. According to KPMG’s 2018 report, the total market for Industry 4.0 will exceed $4 trillion by 2020.
Technologies creating value during Industry 4.0
But Industry 4.0 has implications beyond profit, and its reach extends beyond manufacturing. At its core, Industry 4.0 is not reducible to any one technology, or even a suite of technologies. Rather, it is a fundamental reconfiguration of work in the digital era.
How businesses strategize their digital transformation will determine who will sink and who will thrive during Industry 4.0. McKinsey and WEF, for example, have observed that early adopters experience a 112% cashflow advantage from their Industry 4.0 ventures over those who wait for the price of new technology to drop. Similarly Accenture estimates the first wave of IIoT adopters could see 30% improvements in productivity, and Symantec found that early adoption can lead to 26% reductions in annual inventory.
This guide is designed to be a resource to anyone interested in Industry 4.0. and particularly to those considering a digital transformation. It is written to be a practical as possible. In the chapters, you’ll find a mix of historical and contextual information alongside actionable tips to help you strategize your digital transformation.
What is Industry 4.0?
The term Industry 4.0 (“Industrie 4.0”) first appeared in a German government memo. In its earliest usage, Industry 4.0 referred to Germany’s attempts to integrate digital technologies into its national manufacturing strategy.
The term quickly caught hold. “Industry 4.0” became common parlance in manufacturing communities by the early 2010s.
Writing in 2014 of a rapidly changing business landscape, head of the World Economic Forum Klaus Schwab summarized the developments he considered essential to the recently named Industry 4.0:
It is the fusion of these technologies [AI, big data, IoT, bioinformatics] and their interaction across the physical, digital, and biological domains that make the Fourth Industrial Revolution fundamentally different from previous revolutions — diffusing faster and more broadly than any of the previous revolutions.
What makes Schwabs definition so compelling is his identification of the scope and the reach of Industry 4.0. Industry 4.0 for Schwab is not strictly technological. It is a new way of connecting and communicating that links digital technology to the human body and physical objects.
Though Schwab’s definition is hard to beat for concision and accuracy, a short review of different definitions can go a long way toward highlighting what is significant about Industry 4.0.
Perhaps because of the complexity of the era, Industry 4.0 has been defined in a number of ways. While the emphasis in each definition may differ, there is broad consensus that Industry 4.0 is characterized by:
- A suite of digital technologies achieving scalability and ROI in industrial contexts
- A changing relationship between humans, machines, and labor
- A dispersion and pace sufficient to earn the title “revolution”
Further, commentators agree on three main drivers of Industry 4.0 in manufacturing:
- Simultaneous maturation of old and new technologies
- A convergence of use-cases in manufacturing
- Increasingly wide-spread adoption at scale
Technology as a Driver of Change
Many definitions of Industry 4.0 privilege specific technological advancements. In these definitions, the authors point to the emergence of business use-cases for technologies such as artificial intelligence, big data, Internet of Things integration, ubiquitous internet connectivity, 3D printing, and cyber-physical systems.
Many of these technologies are not new. Their costs, however, have decreased dramatically in the last decade, and their capabilities have increased proportionally. For example, advances in cloud architecture make it possible to collect and store data in previously unimaginable quantities, while the affordable cost of cloud solutions now makes it possible for businesses to use the technology at scale.
For some, Industry 4.0 is characterized by the convergence of many technologies into responsive technological ecosystems. Here, the fact that Industry 4.0 technologies enhance, enable, and augment each other as systems makes it worthy of the name.
Industry 4.0 as Changes in the Nature of Human and Machine Work
Several commentators have argued that Industry 4.0 is best understood as a change in the relationship between technology and work more broadly. Here, advanced technologies usher in a new era because they fundamentally change relationships between worker and machine on the factory floor.
For one management scientist, Industry 4.0 “assumes a blurring [of] the differences between the work of people and the work of machines.”
This is true. But what does it mean?
For much of the history of manufacturing, work was either performed by a human or a machine. While there was always some grey area in this distinction–How do we categorize operators of machines? The engineers who program machines? What constitutes “work”?–under Industry 4.0, the division of labor became murkier.
The modern factory relies on increasingly complex relays between humans and machines, with cognition and problem solving as well as assembly and processing distributed between the two.
Deloitte has described these relays between humans and machines as a “physical-to-digital-to-physical (PDP) loop.” For these analysts, the interdependence of human and machine labor across digital and physical spaces is the defining feature of Industry 4.0. “It is the leap from digital back to physical,” they write, “the ability to act upon data and information that has been analyzed–that constitutes the essence and value of Industry 4.0.” [Deloitte graphic]
Industry 4.0–Worklife Resembles Private Life
There are some for whom Industry 4.0 means something totally different. For Dan Ron, a process engineer at Dentsply Sirona, Industry 4.0 is about “leading a work life that is similar to our personal life.”
By this, Ron means that we have accepted the presence and utility of digital tools in our daily lives. We go about our days with devices to aid us, apps to supplement us, and ubiquitous internet to connect us–for better or worse.
This is not the case in manufacturing. Many factories still run on analogue technologies, the consumer equivalents of which have long receded into irrelevance (almanacs, cassettes, paper records). Until now, these technologies worked, and alternatives were prohibitively expensive for all but the best funded organizations.
For Ron and others, Industry 4.0 is an opportunity to take the best developments from our personal lives and apply them to manufacturing contexts.
What Makes Industry 4.0 a Revolution?
Calling something a revolution is a big claim. Certainly many “revolutions” have not lived up to the hype.
It’s fair to ask, then, what makes Industry 4.0 a true Fourth Industrial Revolution.
What distinguishes our current moment from others is the potential of new digital technologies to disrupt established orders. Commentators have noted that blockchain, artificial intelligence, and threats to cybersecurity–in their most extreme implementations–have the potential to undermine core institutions. Governments, banks, energy infrastructures–all could be massively transformed by decentralized, intelligent technologies.
We are a long way from science-fiction scenarios of intelligent computers toppling nations, or even from blockchain democratizing banking through distributed consensus networks. But the underlying point remains valid. The effects of advanced digital technology have much in common with paradigm-shifting industrial advances that instigated previous industrial revolutions: steam, electricity, and computing.
To put this in context, it serves to briefly survey the previous three industrial revolutions.
First Industrial Revolution
Most historians attribute the First Industrial Revolution to the invention of the modern steam engine in the 18th century. Though relatively weak at first, the steam engine improved in power and reliability throughout the 18th and 19th centuries. By 1886, steam engines reached a capacity of 10,000 horsepower.
Steam and water power allowed humans to build machines that allowed for mechanization of basic processes. In the first half of the 19th century, manufacturers developed processes that converted a number of repetitive, manual tasks into machine work. Many of the world’s most powerful nations build their fortunes through advantages gained on the back of mechanical advances during this era.
Second Industrial Revolution
The Second Industrial Revolution is characterized by electrification and conveyor production. These changes reached national and then global scale at the beginning of the 20th century.
Like the first, the principal changes of the Second Industrial Revolution (2IR) occurred in the domain of energy. The development of modern industrial science greatly accelerated the pace of development and the breadth of dispersion of 2IR technologies. By the early 20th century, electricity and conveyor belt production could be found in the world’s most and least developed nations alike.
The Digital Revolution
Also known as the Digital Revolution, The Third Industrial Revolution did not occur with a fundamental transformation in energy. Instead, it was a result of advances in computing and communications technology. Incipient robotics, capable computers, and breakthroughs in data storage and communication introduced digital electronics into the factory. They also greatly increased the number of processes that could be automated. It was a short leap, then, to more sensitive forms of automation, data analysis, and global connectivity.
The Fourth Industrial Revolution
Like the digital revolution, the Fourth Industrial Revolution is fundamentally rooted in advances in computation and communications. In this case, ubiquitous connectivity created and infrastructure that allowed numerous other technologies to communicate across space and distance.
Schwab, revisiting his 2014 report, has identified velocity, breadth and depth, and systems impact as the factors that make this transformation a revolution rather than an acceleration. In other words, this transformation moves faster, affects us more powerfully, and has the capacity to alter world systems. This revolution impacts who we are, not just what we do and how we do it.
Industry 4.0: Use Cases
There are as many use cases for Industry 4.0 technologies as there are manufacturers.
Even so, the many use cases can be boiled down to a few categories. McKinsey recently identified four areas in which early adopters have achieved reliable success.
Digital performance management
The consulting firm recommends digital performance management because it serves as a crucial first step in developing Industry 4.0 capabilities and infrastructure. Digital performance management tools rely on Industrial Internet of Things connectivity and cloud storage to processes continuous, real-time data from workers and machines. Digital dashboards and manufacturing apps let operators view and respond to process performance in real time. Flexible performance management solutions let engineers tailor KPIs to their operations. Constant interaction with data encourages an evidence-first mentality, an important early step toward a more analytical operation.
As MES, manufacturing software, and analytical systems have improved, so has predictive maintenance. But with advances in big data, human performance tracking, and machine learning, predictive maintenance tools are growing more sensitive by the day. For factories with a base level of connectivity, deep-learning algorithms can create maintenance schedules that only grow more accurate over time. They have already driven huge improvements in OEE, and delivered large reductions in machine downtime as AI hones in on inefficiencies. More advances in this area will arrive as computer vision and wearable sensors turn human movements into actionable data.
Industry 4.0 promises to collect data from machines, and to analyze that data with sophisticated algorithms. But this need not be limited to single processes, or single lines. Rather, early-adopters are seeing significant gains as they use their data to develop systems within departments, and then connect those systems into a responsive, fully connected whole. Some of the greatest Industry 4.0 gains will come from optimizing the full value stream.
Most of the leading research firms project that the use of robotics will expand in manufacturing in the next ten years. But automation doesn’t end with robotics. McKinsey also predicts that many knowledge workers will also contend with automation, as algorithms are increasingly capable of managing demand, scheduling inventory, and performing root-cause analysis
The State of Industry 4.0
So what does the modern connected factory look like?
The truth is there isn’t a single answer. Still, it’s helpful to look at the trends.
According to a recent BCG survey of manufacturers, 53% of respondents said that adopting Industry 4.0 was a priority. While far from unanimous, it is significant that over half of the respondents identified technological transformation as a priority. In price-sensitive industries (semiconductors, electronics, automotive), as many as 80% believe Industry 4.0 should be an immediate priority.
The respondents are confident that these trends will continue. The same survey found that 70% of manufacturing experts believe that factory digitization will be “highly relevant” by 2030.
At the end of the day, projections are still speculation. How are factories actually realizing Industry 4.0?
A 2018 McKinsey survey of global manufacturers, a large cohort of companies have taken significant steps toward a digital transformation. The survey found that 64% of respondents have connectivity programs in the pilot phase, while another 23% are beginning to experiment with connectivity. 70% are piloting intelligence programs, and 61% are already piloting flexible automation. Of those that responded, only 30% have achieved Industry 4.0 impact at scale.
What this means is that a majority of manufacturers are taking steps to integrate digital technologies into their operations. They’re making their factories more connected, smarter, and increasingly automated.
But manufacturers are not adopting all Industry 4.0 technologies at the same rate. In 2016, BCG found that cybersecurity and big data analytics were the most commonly implemented technologies, followed closely cloud computing. The technologies with the lowest level of adoption are those most likely to be associated with a “futuristic” factory. Additive manufacturing, advanced robotics, and augmented reality all had implementation rates around 28%.
In the most recent assessment, a consortium of research groups concluded that roughly 40-50% of the existing machines are connected to a digital infrastructure, if only partially.
Though, according to recent WEF estimates, 70% of manufacturers are piloting Industry 4.0 technologies, considerable investment is still necessary to turn experiments into value at scale. For SMEs and multinationals alike, it takes the right mix of strategy, investment, and foresight to avoid “pilot purgatory.”
Common Roadblocks to a Successful Digital Transformation
At this stage in this guide, we want to move out of the historical and contextual portion and into the practical. From here, you’ll find advice on how to implement an Industry 4.0 digital transformation, and tips on avoiding “pilot purgatory” yourself.
There is no one-size-fits-all strategy for a successful Industry 4.0 transformation. Strategies will vary depending on company size, industry, geography, and competitive forces, among others.
According to a recent WEF report, there are two, complementary routes to scale for companies looking to leverage Industry 4.0 technology to their advantage.
- Innovate the production system: expand competitive advantage through operational excellence.
- Innovate the end-to-end value chain: create new businesses by changing the economics of operations.
Along this road there are some common stumbling blocks.
Lack of executive vision
The executives who participated in Deloitte’s Digital Transformation survey agreed that a lack of a long-term, detailed executive vision is the greatest barrier in a digital transformation. Devising the right digital strategy requires detailed knowledge of an industry, and the foresight to anticipate which technologies will be most disruptive in a given space. The most successful digital transformations occur when executives set 1, 3, 5, and ten year goals for their digital transformation.
Starting too big
A full digital transformation doesn’t happen overnight. It’s a product of long-term, incremental changes to technological ecosystems. Still, many companies strive for full digitization without filling in the gaps. The best transformations will work from proof-of-concept to proof-of-concept, putting pieces into place as they work toward something larger. They’ll build on early successes, embrace failure, and gradually build a suite of technological solutions that work together.
Not connecting the dots
The ideal factory is seamlessly connected. But not all technologies are equally amenable to integration at an early stage. Failing to start with basic infrastructural improvements (wifi, server space, reskilling and talent acquisition) can hinder later initiatives. All the data in the world, for example, won’t help without data scientists to make meaning of it.
7 Steps to Implement a Digital Transformation
1.) Begin with concrete business goals
Many Industry 4.0 digital transformations fail because they lack a clear goal other than a digital transformation. Put differently, they fail because they aren’t motivated by a clear business outcome. When planning a digital transformation, first identify what new technologies can and should do for your business. Then explore what options will help you attain these goals.
2.) Have a roadmap
When it comes to a digital transformation, it’s not enough to think in the short-term. Manufacturers planning a digital transformation should place their early initiatives within the context of a long-term strategy. Bain has called this “a thousand points of digital lights,” or, many digital “stars” in the sky without a means of connecting them into constellations. This involves identifying how early programs will build the infrastructure for later developments. As PricewaterhouseCoopers argues, all digital transformations should take an “ecosystems” approach. Don’t just think of each piece of new tech in isolation. Envision and map the entire system you’ll like to see implemented on the shop floor.
3.) Experiment with single technologies, pilot projects
Pilot projects offer an opportunity to establish a foundation for a digital transformation. Because of their low cost and experimental nature, they provide an opportunity to fail without disrupting business. When pilots succeed, manufacturers can use the success as leverage to garner support for expansions. If they fail, they offer a chance to hone strategy.
4.) Focus on ROI
Digital transformations are a means to an end. At every stage, manufacturers working on a digital transformation should ask themselves what advantages their gaining from their efforts, and how every investment impacts the bottom line.
5.) Keep lines of communication open
It’s easy to think of the digital factory as one without humans. But humans aren’t going anywhere, and top-down digital transformations that fail to account for the needs and experiences of workers are bound to encounter friction. Executives should involve shop-floor workers in the digital transformation. No one knows a factory’s processes better, and few are better poised to provide information about needs and inefficiencies.
6.) Build education into the process
One consequence of Industry 4.0 is that old job descriptions are reaching obsolescence while others are springing into being. As a result, reskilling, upskilling, and ongoing education have never been more important. Managers can enhance their transformation by identifying candidates for upskilling, and making sure that the employees who need to develop new skills, can. In some cases, Industry 4.0 technologies can be used to augment training initiatives.
7.) Never stop improving
This may be obvious for the industry that turned continuous improvement into a science, but it bears repeating: a digital transformation is not something that happens once. Disruption is now the status quo. Staying successful means building agility into the foundation of a manufacturing operation.
Like few other events, Industry 4.0 has caused us to reflect on the state of work in the world. From Klaus Schwab’s germinal 2014 The Fourth Industrial Revolution to the World Economic Forum’s most recent Industry 4.0 report, commentators have stressed the potential human impact of advances in manufacturing. As a revolution in one of the world’s largest economic sectors, Industry 4.0 has the chance to shape our world for decades to come.
In many ways, this emphasis on the human is because manufacturing is undergoing the same digital transformation as every sector. Thomas Friedman recently argued that we now live in a world in which controlling the flow of information is more important than accumulating unique information. This is equally applicable to Industry 4.0. The manufacturers that control the data their factories produce will gain competitive advantage over those committed to hoarding unique knowledge.
At this stage, manufacturers should be plotting their digital transformation. By following the advice outlined in this guide, and by keeping track of industry trends, they should be able to maximize the value of Industry 4.0.
Tulip’s flexible and intuitive manufacturing app platform helps manufacturers thrive during Industry 4.0. Using Tulip, engineers can create applications that guide operators and collect data from the people, machines, and processes involved in production. With Tulip, companies can digitally transform their shop floors and gain real-time visibility of their production in days. Start building apps for your lines with a 30-day free trial!