Why Is Industry 4.0 Taking So Long?

As is the case with most historical progress, it’s hard to pinpoint when Industry 4.0 first started. We generally define the start of the third industrial revolution as roughly 1969, when programmable logic control systems emerged as a usable resource in production. Arguably, we are in the midst of the beginning of the fourth industrial revolution.

The four industrial revolutions: (1) Mechanization through water and steam power. (2) Mass production and assembly lines powered by electricity. (3) Computerization and automation. (4) Smart factories and cyber-physical systems.

Let’s Start with the Basics

We’ve all heard or have seen the term Industry 4.0 touted by marketers when they are describing emerging OEM features, but what exactly does this term mean?

According to Spencer Cramer, president and CEO of ei3 Corporation, “People seem to be constantly misinterpreting Industry 4.0.  Even worse, they think Industry 4.0 is synonymous with the Industrial Internet of Things (IIoT). A strict definition of Industry 4.0 is that it describes digitalization as the Fourth Industrial Revolution.

“For me, Industry 4.0 conveys many digital topics like batch size 1, made to order, digital twins, and my favorite one, the Industrial Internet of Things, and artificial intelligence (AI). I like the last two the best because that’s what ei3 has been concentrating on for the past several years.”

Essentially, Industry 4.0 is taking the world of industry and manufacturing, and creating the ability to work in the digital space. Doing production more efficiently and leveraging concepts like digital twins for preventative maintenance using a growing plethora of data are just the tip of the iceberg here.

Has the Fourth Industrial Revolution Already Arrived?

The concept of Industry 4.0 has been around for some time already. Some might blame marketers for touting the term before it was a viable concept, but really, digitizing a world that is based on making physical things is no simple task.

Roughly seven years ago, we were on the cusp of a viable IIoT, but there is more needed to realize Industry 4.0. Cramer said, “We were combining three simple concepts: secure communications, cheap data storage and supercomputer processing power into a whole new way to think about the elements of production, machines, uptime, quality and reliability.”

Even back then, one of the biggest challenges wasn’t necessarily collecting data, but rather, doing something useful with that data. “It’s true that we have more data than ever, and the sad reality is that more than 95% of the data that’s recorded and stored never gets used,” Cramer explained. “This has been my mission and it’s led ei3 into some exciting new avenues—particularly in the areas of machine learning and artificial intelligence with our team of data scientists.”

According to Cramer, manufacturer analysis is still in its infancy today. Many shops and OEMs alike understand the value of gathering data from their machines, inventory, and more, but much of that data is still underused. And herein lies the industry’s shortfall in digitization.

While manufacturers are beginning to understand the value of digitization, it can be argued that Industry 4.0 is still coming. “In my view, we’re only seeing the tip of the iceberg,” Cramer said. “Yes, huge technical changes are being put in place in the background to enable the Industrial Internet of Things. Most importantly, companies are steadily investing into the secure communication links and devices needed to capture and transmit the large amounts of data needed for analytics to work. But, since we’re early in this revolution it is safe to say that impact is still very much in the future.”

While we’re all familiar with data being gathered and have an idea of how it is being leveraged, manufacturing is only just starting to get a handle on the best way to use the data that we are gathering.

How Do We Leverage All That Data?

There is no black-and-white method to get ROI from IIoT or the broader idea of Industry 4.0. It’s much more complicated—mostly because it relies on what data is gathered, how it is monitored, and, most importantly, what an organization does with it.

Preventative maintenance and using data to root out causes of machine failure are two of the most prominent ways this data can be used to avoid unplanned downtimes and make operations more efficient. Cramer noted, “The most value is captured by using data to learn from the past to predict the future.”

He went on to share an anecdote about Milacron, a plastics company that ei3 has worked with on a number of Industry 4.0 projects. “Milacron has a premium reputation for delivering high-performance injection molding machines. Together we came up with the idea of putting predictive analytics to work to monitor some of the most critical parts of their machines.”  

ei3 works with Milacron to monitor and analyze machine data to make better predictions and decisions. (Image courtesy of Milacron and ei3.)

“Today we are monitoring thousands of Milacron machines operating at injection molding facilities around the world. From these facilities we have captured enormous sums of data and the ei3 data science team, based in Zurich, Switzerland, has worked closely with Milacron engineers to develop algorithms that model machine behavior—if the machine does not perform to its model—then something’s wrong.

“Algorithms need data, and with the data we are collecting on Milacron machines, we run algorithms to compute machine health. The goal is to provide warnings to drive parts replenishment programs for their customers. It’s a great service because the machine owners can have Milacron monitor and send them the parts they need and so there are less parts needed by the machine side in inventory. This creates a virtuous double bottom line where both Milacron and their customers benefit.”

This chart demonstrates how Milacron leverages Industry 4.0 technology to help both its customers and its internal data systems. (Image courtesy of Milacron and ei3.)

The concept of an OEM providing data is the first step in the full implementation of Industry 4.0. But developing ecosystems of machines and networks is going to be the basis of this new world of digitized manufacturing. Without an ecosystem, manufacturers would be forced to navigate varying sets of data from different providers and find themselves without a centralized means of making educated decisions.

“There are simply too many technological advancements that need to be done for any single organization to be responsible for it all,” said Cramer. “Collaborations can create benefits for all players involved, truly making better where one plus one equals way more than three.

“To ensure that we have interoperability in the future, industry participants must build solutions using standards. The standards need to apply to different layers of the Industry 4.0 stack.  There are already the standards needed for the transport and exchange of data. But other parts of Industry 4.0 need to be defined, for example, standards that define machine states or modes of operation. This is one of the reasons why The Organization for Machine Automation and Control (OMAC) has an important and upcoming role. By curating a set of standards for machine operations, modes and states, OMAC provides a vital context to allow machine data to play nice together.”

Who Really Benefits from Industry 4.0?

Manufacturing has always had a broad mix of major business entities, small 10- to 15-person shops, and cottage industry machinists working in home shops. While major software buys like ERP systems and annual capital equipment line items are often relegated to major manufacturing outlets, all facets of the industry stand to benefit from Industry 4.0.

In fact, as the prices of capable equipment and industrial software become more affordable, more small manufacturers are emerging than ever. Cramer even noted, “Smaller companies stand to benefit disproportionately more from Industry 4.0—and significantly benefit from the Industrial Internet of Things. Industry 4.0 levels the playing field—may be even tipping it towards smaller manufacturers.”

Smaller manufacturing businesses often can be more agile and react faster to new technology, and this situation is no different. “Smaller companies are able to react fast and put Industry 4.0 to work quickly, while larger companies take longer to evaluate and deploy,” Cramer explained. “This difference in adoption speed really helps the small company. The ability of Industry 4.0 to reduce overhead and get maximum production from expensive machines has a larger impact on smaller companies.”

That doesn’t mean that large manufacturers have nothing to gain. Increasing shop efficiency—even marginally—can create real dollar value on the shop floor and in a business’s bottom line. While smaller businesses stand to gain a lot right away, Industry 4.0 could change the way every manufacturer does work.

Full-on Industry 4.0 Is Still Coming

If there is anything that we want in the world of manufacturing and engineering, it is data. Let’s be honest … data allows for the sweet justification of decisions and, in the end, provides a path to help us be as efficient as possible. When there are so many benefits to gathering all this data, why hasn’t Industry 4.0 already been overwhelmingly adopted?

Cramer explained, “One of the reasons is that a good deployment of Industry 4.0 doesn’t appear automatically. Getting one that works and delivers on the promise requires careful selection of the company providing the solution. And in this case, experience matters. Put it another way, right now there are not enough suppliers that have the product and expertise to meet the needs of the manufacturing industry. Yes, there are many companies who have smart web pages saying all the right words, but it’s not certain if they have the experience to get the job done.

“From my point of view, it’s clear that manufacturing companies are notoriously slow to adopt new technologies and processes, and when it comes to the Industrial Internet of Things, that's no exception. With that said, the past twelve months [with the COVID-19 pandemic] have been full of change.”

This is an understandable bottleneck. Even garage-shop manufacturers have tens of thousands of dollars invested in machines and programming—they aren’t quick to put their business and investments at risk. That’s not to mention the major manufacturers and OEMs that have millions or tens of millions of dollars in both production and capital equipment that could be at risk.

Even so, there is little to deny the value that true Industry 4.0 can provide a business of any size. The challenge of developing a workable ecosystem of machines and digital assets and learning to root out actionable decisions from all that data, isn’t small, but when applied correctly, businesses are already seeing major returns.

We’ve all known about Industry 4.0 for some time. And while the actual fourth industrial revolution is still in the making, the opportunities to take advantage of it are already revealing themselves. According to Cramer, the natural evolution as costs for sensors, communications, data storage and processing power continue “their relentless drop” is that IIoT will become more prevalent. With IIoT growing, there will be even more data, and using that data, engineers and shop managers can develop better practices, more efficient processes, and even more AI for the shop floor. Machine learning and data gathering are sure to continue, driving us further into Industry 4.0.