FORCAM is leading a research project at the Digital Manufacturing and Design Innovation Institute (DMDII) in Chicago to learn how analysis of machine health information can lead to dynamically scheduled maintenance in the plant floor.
The project at DMDII is being conducted along with Predictronics, Lockheed Martin and Boston-based Northeastern University to look at how to combine real time overall equipment effectiveness (OEE) data with machine health data to improve the understanding of actual equipment health. Partner Advantech Corporation provides IoT intelligent hardware such as industrial PCs to enhance project success and visualization of metrics across the shop floor of Lockheed Martin’s operations.
“Current dynamic scheduling software systems effectively assume that the machines are 100% healthy and that similar machines do not degrade at different rates,” said Mohamed Abuali, chief executive officer of FORCAM Americas. “The value of the proposed technology is changing today’s factory operations from a reactive environment centered around preventive maintenance to an agile, just-in-time maintenance environment.”
FORCAM team members and other researchers are looking at how this data analysis can significantly improve the availability metric of OEE, as well as reduce mean-time-to-repair (MTTR) and mean-time-between-failures (MTBF). Successful improvement in these metrics also could reduce spare inventory levels and cost impacts of machine downtime for an organization.
The Digital Manufacturing and Design Innovation Institute is where innovative manufacturers go to forge their futures. In partnership with UI LABS and the Department of Defense, DMDII equips U.S. factories with the digital tools and expertise they need to begin building every part better than the last. As a result, its more than 300 partners increase their productivity and win more business.
This work is sponsored in part by the Department of the Army through the Digital Manufacturing and Design Innovation Institute. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Department of the Army.
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