The Center for Intelligent Maintenance Systems, a National Science Foundation consortium including the University of Cincinnati, the University of Michigan and the Missouri University of Science and Technology, held its latest meeting at the Chrysler Education Center in suburban Detroit May 16-18, 2012.

Manufacturing companies join the Center and contract with engineering Ph.D. and post-doctoral researchers to conduct research into various engineering problems. Some of the companies I’ve seen in the past included GE Aviation, P&G and Toyota. This year at the Industry Forum Spirit Aerosystems, a spin off from Boeing, presented its experience moving its maintenance experience from reactive to condition-based. A presentation from Applied Materials explained something of semiconductor manufacturing and how it’s looking for more sensing and automated data collection into an event-based database in order to improve its machine uptime.

Jay Lee, Director of the Center and a Professor of Engineering at the University of Cincinnati, challenged the audience to expand thinking by considering a cloud-based predictive analytics. The idea would be to perform the analytics in the cloud, not to store data there. There are potentially many people who would be interested in the analytics, but most would prefer to store data locally. While he mentioned to the audience the efficacy of Amazon’s S3 cloud service and other similar ones, he really was advocating what’s known as a “private cloud.” Being from an Ohio-based university, he mentioned another benefit of the cloud idea–Only Handle Information Once (OHIO).

As I examined the poster board corridor containing information about some of the research students had conducted recently, two especially caught my eye: Estimation of Maintenance Opportunity Windows in a Manufacturing System; and Importance Measure-based Reliability Improvement for Multi-State Systems. With any luck, I’ll get a paper from each to publish in Automation World.

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