by LESLIE LANGNAU, Managing Editor
Medical, automation, automotive, food and beverage, material handling—so many industries plan to take advantage of IIoT. Experts explain why.
Connecting various devices, systems and equipment together through an Ethernet platform has been going on for years in various manufacturing industries. Data about manufacturing machine performance and operation used to be loaded up to “dashboards” monitored by upper management. An overwhelming amount of data, though, shifted this effort from recording every single device operation to “management by exception,” where only certain bits of data were analyzed for importance.
Why are manufacturing industries returning to massive data gathering? And which industries are doing so?
The answer to which industries is easy:
“We have seen the IoT applications in dozens of industries from oil and gas, paper products, recycling, plastics, vending, food and beverage, medical machinery, automotive and wastewater,” said Gary Marchuk, director of business development, AutomationDirect. “The demand seems to exist just about everywhere.”
“We see greater interest in a variety of industries, from consumer product manufacturing, to packaging, to material handling, heavy industry, and more,” said Daymon Thompson, TwinCAT product specialist, Beckhoff Automation.
“Don’t forget agriculture,” added Jeremy King, product marketing manager, Bimba Manufacturing.
Answers for why include:
- The promise of getting almost any type of information in digital format, which experts claim makes this information free as well as “fluid.”
- The predictive potential of such data, especially its ability to improve uptime. “Everyone wants to avoid having an actuator wear out in the middle of a product run,” said King. “This is an area most IIoT products are targeting.”
- Marketers, managers and product developers expect to learn what customers want practically before they know themselves.
- Managers and manufacturing directors expect to know in plenty of time when a machine component will break or need maintenance.
- “Access to device-level data and the ability to more reliably operate and diagnose problems are factors in deploying Ethernet automation networks, thus allowing the capability to connect more devices to the Internet,” said Randy Durick, VP, Network and Interface Div., TURCK.
“Making domestic manufacturing more affordable is a key theme of Industry 4.0,” added Thompson. “This requires the optimization of processes to accommodate made-to-order manufacturing (lot size one), highly flexible manufacturing lines (such as object-oriented manufacturing), quality improvements, and production throughput despite requirements for more frequent product changeovers.”
“The ability of management to get instant access to manufacturing throughput or yields while traveling around the world creates instant value,” added Marchuk.
But the IIoT will need to offer more than the possibility of helping manufacturing reach these here-to-fore unreachable goals. The next step may be to predict changes in equipment and processes. Some customers are looking at different ways to use the data to improve how machines work together; they have broadened their perspective to more than just uptime.
According to some experts, these are the customers that are at the forefront of IIoT.
“Although commercial tools have long been available to provide Overall Equipment Effectiveness (OEE) information to factory management,” said Anthony Varga, president, Canada, SVP, North America Strategic Sales, Rittal, “they tend to be focused on finding root causes for problems that have already happened rather than providing predictions that managers can use to prevent problems.”
Added Bob Gates, global marketing director, GE Intelligent Platforms, “It’s not only beneficial to use the Industrial Internet to build a better product, you can also use applications within those products to run and manage them better. That’s critical when you are talking about gaining better fuel capacity with certain weather patterns or altitudes. Or, when you are sending a turbine out for maintenance, you can now assess how parts wear and see how to use the turbine in the best way possible. Maximizing asset potential—that is what it is all about.”
Many managers of manufacturing operations have experience with data gathering on their processes. As was mentioned earlier, it’s been done before. The data that’s been collected for nearly 30 years was primarily for making operations more efficient and reducing downtime—the same goals mentioned today.
“Some of the large end users have been collecting all kinds of machine data for a long time,” said John Kowal, director, business development, B&R Automation. “But they will tell you: it’s tough to get their arms around, to analyze and use. Meanwhile, machine builders know their machines and they are in a perfect position to offer IIoT functionality as a service, one they can turn on or off using the existing control hardware. And being able to access their machines’ performance data helps them optimize their designs.”
This time vendors can put more sensors on more industrial components. This time, manufacturers know a bit more about their production processes and can factor that in to their analyses. But there will be challenges.
The goals of better, faster, more cost efficient, and more flexible operations will deliver terabytes (1 TB is roughly 1,000 GB) of data to users, per day. Manufacturers must have a new generation of IT infrastructure to handle the data between the plant floor and the enterprise.
“Currently only bits and pieces of the true potential of the IoT are being implemented in industry,” said Nuzha Yakoob, product manager, Festo. “Manufacturers of automation hardware, such as PLCs and motion control devices, are able to incorporate the electronics and Ethernet protocols into their hardware and some go as far as saying that their hardware is IoT ready. However, the standardized open Ethernet protocol is yet to be defined and the required IT infrastructure is yet to be implemented.”
GE Intelligent Platforms