When thinking about how to best address the problem of plant downtime, one must first identify the causes. The first thing that comes to mind is machine failure; something on the line breaks, bringing production to a shuddering, unceremonious and potentially expensive halt. Despite being the most significant issue, however, machine failure is only one of many.

For Raleigh, N.C.-based Pepsi Bottling Ventures LLC (PBV), the primary problem was product changeover . PBV, North America’s third largest manufacturer and distributor of Pepsi-Cola products, makes and ships more than 100 different soft drink products from 27 bottling and distribution facilities in six states. With such a wide variety of products being produced, smooth switchover from one to another is vital to each plant’s productivity.

The PBV facility in Nampa, Idaho, was a particular sore spot. Built in 2005 and acquired by PBV earlier this year, the plant employed a mix of legacy and new systems, leading to waste and downtime problems. A home-grown data-collection system designed to accommodate the legacy equipment didn’t play well with the newer gear, while operators relied on manual methods to track downtime, recording it on clipboards during their shifts.

Without real intelligence about the process, engineers estimated that the changeover process took about an hour, which wasn’t bad, but could be better. To tighten things up, the company rolled out a performance-management-and-downtime- tracking system from Lake Forest, Calif.-based Wonderware, a unit of Invensys Operations Management. The first thing engineers learned was that their changeover process didn’t take them 60 minutes...
it took them 90! And that was unacceptable.

According to Scott Jamison, PBV’s vice president of engineering, the plant used the Wonderware system to identify the primary constraints and their root causes, and found that the most critical bottleneck was in the filler process. Correcting this issue reduced changeover time by up to 45 minutes and had a cascade effect, with additional savings realized in raw materials and packaging. Efficiency on the filler line increased by 10 percent.

Accurate data

“The main thing we are trying to do is get data that is very accurate,” says Jamison. “What is the downtime and what is the cause? By taking information directly from the machines, we are now getting [this rich, reliable information].” For example, he adds, they now get a view of all the micro stops—interruptions of less than a minute that nobody had time to write up in the past and were therefore invisible—that occur every day and take action to correct them.

“Now that we have taken care of  most of the low hanging fruit, we are able to dial in on the most minute things and make informed decisions to improve things. It is helping us evaluate not only the machinery but the people who are running it. We can now see very quickly if an operator is in the wrong position. Can we reassign him or give him more training to make him more effective? All of that ultimately leads to less downtime,” concludes Jamison.

Schwäbische Maschinenwerkzeuge GmbH (SW) in Schramberg-Waldmössingen, Germany, is doing something similar, but with a much closer tie to the maintenance process. The machine-tool maker has rolled out ePS Network Services, a solution from Siemens’ Motion Control Systems group, which provides an Internet-based remote condition monitoring service. Each of the roughly 160 high-performance, multi-spindle machining centers the company makes for the automotive industry each year comes with the service as a combined offering.

ePS constantly mines operational data directly from the equipment and analyzes it to provide useful insight and decision support for not only the maintenance group, but also production and management. Should a specific condition be met—an indicator of an impending failure, for example—an alarm can be issued and corrective action taken to prevent the problem from escalating into an incident that interrupts production.

According to Peter Siegel, the champion for online services at SW, ePS simplifies and accelerates maintenance, eliminating downtime in the process. “The maintenance staff no longer needs to wait for alerts and updates, because they can also work with the data themselves.”

While the initial value to the maintenance function is obvious, Siegel stresses that once you have the information, you can subject it to numerous analyses to get a clearer picture of the business and generate important value for production and management teams.

For example, the production team may want to know how often a given operation is selected; or how long set-up takes; or how long the machine is stopped without ...