Where 4.0 Might Go

What will Industry 4.0 ultimately mean? That is, what will it mean not only to the likes of you and me, but also to the way that industry itself operates and performs? That is a valid question, because the possibilities contained in Industry 4.0 are transformative. Those possibilities will also take time to realize—enough time that we might not experience the answer to this question until well after we have ceased to use the term.

That term, “Industry 4.0,” is challenging. The term is an umbrella, and not everyone agrees on what it covers. The number in that term refers to a fourth disruptive change in manufacturing. The previous change (Industry 3.0 by this reckoning) involved the coming of hardware automation such as computerized machine tools and robots. Industry 4.0 refers to information automation, in which the overall production process is digitally united into a system able to capture meaningful data and respond to it in useful ways. Of the two types of automation—hardware and information—the latter type is ultimately more powerful.

This month’s cover story actually provides a glimpse of this. Tech Manufacturing is capturing meaningful data about the perfomance of its machines. Important improvements to the process have resulted from what these data reveal.

However, all of the responses to the data are human-driven. In this shop (or in any shop pursuing this kind of improvement right now), the managers examine the data, find the problems the numbers suggest and drive all of the responses to those problems. Now, what if—and this is a very big “what if” at this point—but what if the system in this shop could not only detect utilization shortfalls, but also to some extent respond to those shortfalls on its own?

Going further, what if that same system could also allocate its own resources effectively, because of the way its connections to customers’ systems (connections those customers welcomed) enabled this system to gather the data to anticipate future demand?

These hypothetical possibilities suggest manufacturing systems that would have to be far more complex than any industrial system today. And yet: Every single detail of achieving such a system is a straightforward engineering challenge that today we now know how to solve, or know how to go about solving. The challenges relate to sensing, networking, process characterization, predictive diagnostics, adaptive programming, high-level algorithms, system resilience, security and other known challenges. To be sure, the challenges are numerous. But engineering researchers and innovators who are addressing challenges in these areas are gradually advancing us toward Industry 4.0. In “The Martian,” the astronaut hero had a line that captures this. (It appears in the movie, not the book.) After surviving being stranded on Mars and achieving rescue through his resourcefulness, the astronaut says, “Solve enough problems and you get to go home.” In manufacturing, once we solve enough problems, we will get to have a vastly different manufacturing ecosystem.

How will this affect us? One of the impacts is liable to be dramatically lower costs for manufactured goods. I suspect we do not yet have any inkling how much of the cost of manufacturing today is the result of human beings processing limited information at human capacity and speed. Placing orders, entering orders, scheduling jobs, programming jobs, overseeing standalone pieces of equipment, puzzling out the reasons why these pieces fail—all of these functions are steps that we might one day trust the system to perform instantaneously and at no incremental cost. At that point, manufactured products might become so much less expensive that we will think about these material goods far less than we do today. Certainly we will think about manufacturing less, because—in the future I am describing—fewer people will work in manufacturing.

Another impact will be strangeness. It is a characteristic of ecosystems that seemingly small changes propagate into significant, unexpected effects. Indeed, in any adaptive system that is performing the way we hope, this system ought to detect important signals that our human capacities don’t discern, and initiate responses our human foresight wasn’t expecting. In manufacturing, it will become our job to govern these systems that are doing the right thing, even though we don’t know precisely what they ought to be doing at any given instant. The job of a manufacturing engineer will be much less like that of a mechanic and much more like that of a farmer or livestock herder.

These are far-off ideas. Yet they are not so far off as one might imagine. Again, the many engineering challenges inherent to this puzzle will be solved, and as those solutions come, they will start to sum together and synergize. At some point, maybe far sooner than we think, the impact will start to reshape what manufacturers consider to be commonplace. Part of the reason we will eventually cease to talk about Industry 4.0 is because, to some extent, these ideas are destined to become simply industry.