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Legacy equipment learns new tricks

Internet of Things

For years, production managers at Mueller Inc. would stay late in the day or arrive in the wee hours of the morning to sketch out plans on paper for cutting parts out of giant rolls of steel.
Since everything was done by hand — from making pattern plans to inputting that information into the cutting machines — getting a head start was essential.

“Few pieces of their equipment communicated with their software,” said Andrew Dugenske, principal engineer and director of the Factory Information Systems Center at Georgia Tech. “People had to enter data by hand, which was very labor intensive and error prone.”

Managers at the Texas-based manufacturer of metal buildings knew there must be a better way and enlisted factory technology researchers at Georgia Tech to help. The team built a system to link those cutting machines to computers across a network in the factory so production managers could automate the process and monitor the system with more confidence.

The project reduced Mueller’s scrap metal, increased production, and saved significant labor costs.

“This is a great example of how the Internet of Things for manufacturing can provide significant value to manufacturers,” Dugenske said.

Much like internet connections are enhancing a growing range of consumer products, from slow cookers to thermostats, Internet of Things technologies hold great promise for manufacturers looking to automate and monitor their factory machines and systems.

At the basic level, Internet of Things devices simply allow machines to talk to other machines using internet protocols. Sometimes that data is transmitted over the internet and sometimes over just a local network.

“Very few machines on the factory floor currently collect data, and from the ones that do, very little of it is acted upon,” Dugenske said. “So there’s this huge opportunity for applying software systems to these legacy pieces of equipment.”

For some manufacturers, connected devices can help them collect data about their production processes, which lays the groundwork for optimization efforts.

“Collecting data is important,” Dugenske said. “It’s the first step. But data is not useful by itself — it just fills databases. Data needs to be processed into meaningful information so informed decisions can be made. And we find ways to help manufacturers do just that.”

Josh Brown is a senior science writer at Georgia Tech. A journalist by training, he’s spent the past decade writing about economic development, medical research, and scientific innovation.

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