Smart Manufacturing in the Mid-Size Company

How big do you need to be to make intelligent machinery and processes work for your company?

At GE, massive physical machines like wind turbines are embedded with highly sophisticated sensors to determine their internal health. The sensors produce real-time data on water temperature, oil pressure, vibration and microscopic metal fragments in the ambient environment. Predictive data analytics systems model this wide-ranging data to determine the machine’s operational efficiency. “Obviously, knowing weeks, if not months, in advance that a wind turbine will need to be out of commission for a repair is a lot better than finding out today,” says Don Busiek, general manager of manufacturing operations management software at GE Intelligent Platforms.

Sensors also drive quality enhancements and waste reduction. Shelley cites the use of sensors in the injection injection-molding business, where the porosity of plastic can cause a product failure. “By using sensors and algorithms to optimize pressures, temperatures and other parameters in the injection-molding machine, you can ensure that enough plastic is injected at the right pressure to eliminate the risk of cavities,” he explains. “This improves the quality of the molded product and reduces waste, and it all happens in real time.”

“Sensors improve the quality of the molded product and reduce waste, and it all happens in real time.”

Staying Dumb
All this sounds too good to be true; and in a way, it is. Companies don’t simply flip a switch and become “smarter.” Challenges abound, chief among them is a dearth of “skilled workers or ‘smart’ people who know how to use all these IT-driven machines,” Bernaden says.

Swink cites another impediment. “One of the most daunting tasks in any manufacturing operation is to really know and understand the data you already have, use it effectively to make more informed decisions, and then determine what else you should collect and know about,” she says. “The compartmentalization organizationally and process-wise is a huge obstacle in doing this.”

Some organizations are holding back for the time being on intelligent machines until their workforce and organizational structures are ready. “Talking with a CEO of a $60 million metal-parts fabricator recently, I asked him why he didn’t buy one of the new, automated welders that could increase his output with higher-quality products,” Bernaden says. “He said he couldn’t find someone with the combined programming skills and welding skills necessary to operate it.”

He adds, “Not many welders have IT skills, too. But that’s what it’s going to take to program, operate and maintain these smart machines in smart factories.”

Nevertheless, there are plenty of reasons for companies to make the leap now, despite the hurdles. According to a December 2013 survey of manufacturers by the American Society for Quality, only 13 percent have implemented smart manufacturing within their organizations. However, of the ones that did, 82 percent gained greater efficiency, 49 percent reported fewer product defects and 45 percent increased customer satisfaction.

The payoff may be well worth it.


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