This post is a simplified version of the article “Demystifying Industry 4.0: Navigating Automation and Augmentation” published in IEEE Engineering Management Review.
If we had a use-to-talk ratio for Industry 4.0, the score would be sobering. Not because companies are not getting results but because most are a world apart from the engineering vision of a fully automatic factory. One plausible reason for the disappointing uptake is that manufacturing managers are confused about what Industry 4.0 is and what it can deliver for bottom-line performance. This article discusses the advancements toward fully automated, lights-out factories and introduces a straightforward matrix to demystify Industry 4.0 and its implementation.
From Industry 4.0 system vision to point solutions
If it is true that the best way to predict the future is to create it, then proposing a vision is a good start. And there is no lack of visions for the future of manufacturing—never has been. In 1952, John Diebold titled his book “Automation: The Advent of the Automatic Factory.” Three decades later, the buzz was about computer-integrated manufacturing (CIM). According to its visionaries, computers would enable “lights-out” factories with minimal need for a human workforce. In 2011, this vision got a more catchy name: “Industry 4.0.” But it wasn’t just a step change, according to the founders, it was the dawn of a new industrial revolution! Besides a compelling vision, “Industry 4.0” had an instant market appeal.
While entirely automatic factories have been a long-standing dream, perhaps this time, it would actually work? After all, the technological advances in computers and sensors, communication and cloud, and data storage and processing have been unprecedented in the past years. But technical feasibility does not mean it’s good for business or easy to do. Companies that attempted a complete transformation often rolled back, showcasing a few examples of high-tech amid low-tech operations. This is a somewhat disappointing discovery but a repeated one.
So, what conclusions can we draw? In its meeting with reality, the Industry 4.0 vision of complete system automation tends to collapse into managing portfolios of technological point solutions.
From automation to human augmentation
As companies wrestle with piloting and scaling various technologies, they are quickly reminded about the role of humans. Workers close to the value-adding processes are unlikely to be as receptive to automation technologies as vendors and decision-makers. Countless technology adoption projects have been killed off in their first meeting with human agency.
If only the technologies could seek to support rather than replace human workers, the chances for success could increase. While automation removes human labor from work tasks, augmentation supports humans in conducting the tasks. As could be expected, someone came up with the idea to one-up Industry 4.0 and suggested “Industry 5.0” as the better next-level manufacturing.
In 2021, the European Commission published a whitepaper on Industry 5.0 arguing how it added three critical and missing elements to the automatic factory vision: Human-oriented, resilient, and environmentally friendly. It was a welcomed contribution with good intentions and fair points, but it also watered down the focus on technology implementation, creating much confusion about the end game. A factory cannot be lights-out and human-centric simultaneously, as humans generally do not like to work in the dark.
Now what? From its vision as complete system automation, Industry 4.0 has fizzled into point solutions of a wide selection of automation and augmentation technologies and triggered the proposal of a competing human-centered vision.
A framework to make sense of Industry 4.0
A framework spanning out automation versus augmentation on a horizontal axis and point solutions versus system solutions on a vertical axis, as shown in Figure 1, can help explain Industry 4.0. As illustrated in its upper left corner, Industry 4.0 is—in its original form—a vision for full system automation. However, in reality, all quadrants are represented in the Industry 4.0 discourse and business practice.
Studies include a wide variety of different technologies under the Industry 4.0 label. Consider, for example, the World Economic Forum’s Global Lighthouse Network, which looks for companies implementing Industry 4.0 technologies at scale. In these lighthouse companies, an extensive range of technologies are reported in use. Hence, in industrial practice, Industry 4.0 is often seen as a mixed bag of technologies in search of use cases.
A technology use case describes the practical application of a technology in a real-world context. The latest Global Lighthouse Network report mentions the mapping of more than 1,000 different use cases.
Industry 4.0 technologies
The presented framework can be used to sort Industry 4.0-related technologies into five technology clusters, as shown in Figure 2. Note that the framework should be helpful when discussing and navigating the opportunities of Industry 4.0—not taken as an ultimate technology typology.
At the foundation, there is a layer of enabling digital technologies that collect, transmit, store, and protect data. These technologies have no use case on their own but enable the potential of other technologies. The more enabling technologies a company implements, the larger the potential of integrating other technologies—but at the cost of installation and maintenance and risk of obsolescence.
The four other technology clusters fall into the quadrants of the framework: point automation, point augmentation, system automation, and system augmentation (see the paper for a detailed presentation and discussion).
A peril with the use-case-building approach could be that it misses the revolutionary opportunities of Industry 4.0—hence, risking to improve the horse rather than inventing the car. But it does not have to be that way. At a closer look, most technologies listed above are potentially cumulative and synergetic. For example, when a company implements robots and wearables, it can improve its digital twinning through increased and improved data capture. However, such synergetic effects can only be reaped when contextualized data can be connected and used at scale by a range of applications. Therefore, it is critical to build and maintain the enabling digital infrastructure with a view to the long-term vision.
Putting the framework to use
When it comes to Industry 4.0, after all is said and done, a lot more has been said… than done. Manufacturers are often lost in digital transformation—overwhelmed by technological opportunities in search of problems to solve. But there’s a better way, and the simple framework proposed here can offer some guidance. It can serve as a mapping tool for tracking what types of technologies have been tested and which ones to prioritize next.
While a reasonable business vision may be Industry 4.0-like system automation, it is not the best place to invest all efforts. Companies that pursue a strategically selected and well-balanced portfolio of use cases from all four quadrants are best positioned to reap exponential business benefits. Companies that get ahead prioritize use cases that offer clear business value, which nurtures support and encourages further transformation.
A good place to start is to point augmentation. Why? Because using new technologies to help people succeed at their job tasks rather than making them obsolete is good for morale and frees up human ingenuity for the next improvement. Besides, the amount of enabling digital infrastructure to support point augmentation is often limited and affordable. Getting the people involved and supportive is the key.
Read the full paper including references to further work: Netland, T. (2025) “Demystifying Industry 4.0: Navigating Automation and Augmentation,” in IEEE Engineering Management Review, doi: 10.1109/EMR.2025.3550594.
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