According to Rodney Rusk, Industry 4.0 leader at Bosch Rexroth Corp., companies start IIoT projects in one of three ways: from the top down, from the bottom up, or somewhere in the middle.

“The top-down approach is usually driven by someone from the C-suite—the chief digital officer or the chief technical officer,” says Rusk. “Management has a clear vision of the connected factory as a core strategy of the organization. They will assess where the company is today and then craft a plan for five years down the line.”

The bottom-up approach typically stems from a specific production problem. “It starts with a manufacturing engineer, a maintenance technician or even a line worker who is trying to solve a problem,” explains Rusk. “Maybe it’s an issue with quality or uptime. So, they implement an IIoT solution. If it works, maybe they can make a business case to apply it to the rest of the organization.”

The middle approach usually starts with the IT department. “IT is looking at the company’s software stack and trying to streamline it,” says Rusk. “They are trying to find ways to make things interoperable and reduce the number of systems they’re running.”

Dan McKiernan, president of software supplier eFlex Systems, observes that few manufacturers have the wherewithal to dive headlong into Industry 4.0. Most start by dipping their toes in the water.

“The first step in Industry 4.0 or the smart factory is getting rid of paper work instructions and enforcing your assembly process,” he says. “From there, it moves on to error-proofing and capturing data. Simple steps. Maybe it’s something as simple as having an operator scan a bar code on a parts bin when you used to take for granted that the right parts were going into the right products. Or, maybe it’s greater control over the fastening process, when before it was just an open-loop process. From our experience, it’s surprising how little control we see on assembly lines, even today.”

Once assemblers have mastered digital work instructions, error proofing and data collection, they can take the next step to greater integration of their “software stack.” This is the alphabet soup of hardware and software—PLCs, SCADA, MES and ERP systems—that govern modern assembly plants.

“Manufacturers can use our product as is, but when they’re ready and if they need it, we can take them all the way up to the back end of their ERP system,” says McKiernan.

“Typically, each one of those layers represents a different vendor and a different skill set,” he continues. “So integrating them can be daunting. Our software covers that full spectrum, from the bottom of the ERP to the assembly tools.”

Whether the Industry 4.0 mandate comes from the top down or the bottom up, neither approach is better than another. Ultimately, what matters most is the corporate culture. “A lot depends on the digital maturity level of the organization,” Rusk concedes. “But, it’s also important for the company to have a lean, agile culture that is embraced from the C-suite to the line worker. When an organization is generating quite a few continuous improvement projects, those often lead to larger solutions. There is no silver-bullet solution for creating a digital factory; it’s a series of agile sprints. You test theories and you learn from your best solutions.”

Rusk knows firsthand how that works. For the past five years, he has been helping apply IIoT technologies at Industry 4.0 test facilities within the Bosch group. “We’ve learned a lot through trial and error,” he admits. “Now, we are sharing much of that knowledge with our manufacturing customers.”

Common Issues

Outfitting an assembly line, a multistation automated assembly system, or an entire factory for IIoT can be a challenge, particularly if some of the equipment is older. This is what Bosch Rexroth encountered when equipping its assembly plant in Anderson, SC.

“Some lines have been running since 1992, and other lines were installed as recently as 2018,” recalls Rusk. “The equipment was running different control systems and different networks. Some machines were Ethernet; others were Profibus. Originally, we thought all we had to do was install a software layer to make everything work together and feed all the data into one database. But that did not necessarily work.”

Another lesson Bosch learned was the importance of being on the same page when trying to link up multiple factories. “A facility in Germany went in one direction; a facility in the U.S. went with another; and a facility in Mexico went with yet another,” says Rusk. “Now, we had three solutions, and none of them resolved the problems we thought they were going to resolve. The plants couldn’t help each other because their systems were talking different languages.”

Another issue was at the device level. “Because we had so many lines over the years—some built internally, some built by integrators—we hadn’t considered their digital capabilities. Instead, we focused on network standards, like Ethernet or Profibus. However, we realized that many technology suppliers had their own little ‘twist’ on, say, an Ethernet solution. Instead of having a generic Ethernet solution that could plug and play, many had unique ways to interface with their technology. Our engineers were burdened with knowing the idiosyncrasies of each of those devices.

“Today, we have a different approach. When we look at technology that will go into our production lines, we ask: Is the protocol truly open? Is it scalable? And is it flexible? Can they be intermarried with other technologies? Has the manufacturer painted us into a proprietary corner?”

Indeed, this is the philosophy behind Bosch Rexroth’s own line of automation and motion control products, and it’s the thinking behind the company’s Open Core Engineering programming software.

Frank Latino, product manager for electric automation at Festo Corp., counsels manufacturers to consider what they want to learn about their production lines before they start collecting data. “The first thing you need to do is figure out what you want to achieve,” he says. “The three most common targets [for IIoT initiatives] are energy efficiency, preventive maintenance and machine optimization.”

Enrico De Carolis, vice president of global technology at Emerson Fluid and Motion Control, agrees.

“Everyone is focusing on data today,” he says. “The problem is, data is not necessarily useful information. …You need to understand the process of the machine to give relevance to the data. If you’re just generating massive amounts of data and hoping somebody will analyze it and come up with a bunch of wonderful insights, you need to rethink that.”

Having clear information goals will ensure that engineers are collecting the right data and analyzing it the right way. It will also keep costs down.

“Many people think of IIoT as being similar to IoT, where everything is connected to everything,” says De Carolis. “However, in an industrial setting, that would be very difficult and very expensive.”

Engineers also need to think about future needs. When making capital equipment decisions in the era of Industry 4.0, Rusk advises manufacturers to ask more than just “what is this line going to do?” and ask instead, “how is this line going to fit into my entire ecosystem?”

“You don’t want to be reinventing the wheel all the time,” he points out.

Most of all, when making the leap to Industry 4.0, manufacturers should not be afraid to fail. “You’re not going to get it right 100 percent of the time,” Rusk says.

IIoT and Automation Components

As the IIoT increases in popularity, automation component suppliers are responding with new products that make it easier to collect and analyze performance data.

For example, the CPX Motion Terminal from Festo combines mechanics, electronics and software in the form of a “cyberphysical system.” Pneumatic functions are no longer automatically connected to mechanical hardware, but can be assigned using apps. As a result, just one valve type can handle a wide range of pneumatic movements and functions.

The terminal makes it possible to have the same hardware for a multitude of functions. With the matching motion app, engineers can change functions at the press of a button. Apps are available for directional control valve functions; proportional directional control valve functions; proportional pressure regulation; model-based proportional pressure control; leakage diagnostics; supply and exhaust air flow control; and selectable pressure levels for high loads. A soft-stop app is a self-adapting algorithm for time-optimized positioning without vibration. Another app allows presetting of travel time, enabling the pneumatic system to learn and adapt for consistent advancing and retracting.

The terminal can be connected to host environments for Industry 4.0 and also to the cloud via an IoT gateway.

“We have preconfigured dashboards through our IoT gateway for some of our components,” says Latino. “For example, our energy savings module displays data on air consumption, supply-to-flow rate, and pressure supply values. It will also trend that data over a period of time, so you can look for anomalies. You can set thresholds, so you can get warnings if the machine is running out of spec. It also tracks leakage data and provides basic maintenance data. That takes the guesswork out.”

Emerson Fluid and Motion Control offers engineers different levels of control. Products such as the ASCO G3 platform extend the intelligence of pneumatic fieldbus manifolds to perform various IIoT data analytics locally—at the device level. The G3 gives engineers the ability to collect relevant and useful information on smart pneumatic devices regardless of plant infrastructure—and to do it without changing the PLC program. Diagnostic and prognostic information takes place at the device level. The technology is also future-proof. Device information will remain relevant as the plant’s infrastructure matures.

Another option is a device called a Smart Pneumatic Monitor. “It connects to the manifold, and because it has more computing horsepower, it can collect and analyze a lot more information, such as temperature, pressure and flow, and send to the cloud,” says De Carolis. “Bear in mind, however, that you will have to add extra sensors to collect that additional data, and that increases cost.”

In the near future, AI and machine learning will provide engineers with predictive maintenance information, so equipment can be repaired or replaced before breakdowns occur.

“We’re doing tests right now of our ability to confidently predict when certain pneumatic components might fail a week or two before it happens,” says Latino. “Today, you simply replace a component after so many cycles. With IIoT, artificial intelligence can determine when a part will fail. The machine might even order its own spare parts. The part will just show up on the loading dock with instructions on when and where to install it.”

Software Advances

Just as the IIoT will require new types of automation components, so, too, will it require new types of software. “For IIOT to work, a lot of things needed to happen so that plug-and-play interconnectivity between all these different systems was easy,” explains McKiernan. “Today, you don’t have to do a lot work to make data flow from one level to any layer above it. That standardization has opened up more capabilities on a wider array of hardware.”

New publish-subscribe messaging protocols, such as MQTT (message queuing telemetry transport), and flow-based software development tools, such as Node-Red, are making it easier to integrate manufacturing hardware and software and to send data to and from a production line.

“Manufacturers that had been lagging in adopting technologies to improve quality and efficiency can now take advantage of them in ways that they couldn’t before because it was cost-prohibitive,” says McKiernan.

“It’s a given what manufacturers will do with all the data they can collect from a production line,” he continues. “It was just getting the data that was a problem. Now, for a minimal fee, you can subscribe to analytics in the cloud that weren’t even available five years ago—things like IBM Watson and Microsoft Azure.”