Researchers Unite to Search for Zero Breakdown Performance
For years, maintenance has been treated as a dirty, boring and ad hoc job. Its critical for productivity but isnt yet recognized as a key component of revenue generation, says UCs Jay Lee, professor of engineering and director of the NSF Industry/University Cooperative Research Center on Intelligent Maintenance Systems (IMS) and an Ohio Eminent Scholar. The simple question is often, Why do we need to maintain things regularly? The answer is, To keep things as reliable as possible. But the real question is, How much change or degradation has occurred since the last round of maintenance? The answer is, I dont know.
The
Center for Intelligent Maintenance Systems
was established to enable products and systems to achieve and sustain near-zero breakdown performance, and ultimately transform the traditional maintenance practices from "fail and fix" to "predict and prevent" methodology. The center focuses on frontier technologies in embedded and remote monitoring, prognostics technologies and intelligent decision-support tools.
The challenge for reliability is dealing with data from the past. Failure is modeled, analyzed and to some extent predicted. Unfortunately, the prediction doesnt take into account users or working environment-related constraints, and often the results arent that useful, says Lee. Condition-based maintenance (CBM) deals with online data. Machine conditions are constantly monitored and their signatures evaluated. However, this is done at the machine level one machine at a time. This is what we call the fail-and-fix approach.
Today, CBM focuses on sensors and communications. All products and machines are networked by some means. Lee says that its difficult to know, though, what to do with all these data.
We need to turn data into information by using computational tools to process data locally, he says.
Get your own information about intelligent maintenance systems at the industry forum on May 16 with a focus on advanced prognostics and smart predictive maintenance benchmarking. Presenters include the University of Cincinnati, the University of Michigan, the University of Missouri-Rolla, GE Aviation, Caterpillar, Toyota, P&G, GM, Nissan, Omron and National Instruments.
Following the industry forum, the NSF IMS Center 13th Industry Advisory Board (IAB) meeting will be held at P&G in Cincinnati on May 1718, 2007.
"The maintenance world of tomorrow is an information world for feature-based monitoring," says Lee. "Information should represent a trend, not just a status. It should offer priorities, not just show how much. If we do that, then our productivity can be focused on asset-level utilization, not just production rates."
About the NSF Industry/University Cooperative Research Center on Intelligent Maintenance Systems (IMS)
IMS is a multi-campus NSF Industry/University Cooperative Research Center with a focus on advanced prognostics and predictive maintenance technologies to achieve zero-breakdown productivity. The Center consists of research sites at the University of Cincinnati, the University of Michigan and the University of Missouri-Rolla, as well as two international sites (Singapore and Brazil), in partnerships with over 40 global companies.
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