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Stochastic Maintenance Opportunity Windows for Serial Production Line

[+] Author Affiliations
Jing Zou, Qing Chang

Stony Brook University, Stony Brook, NY

Yong Lei

Zhejiang University, Hangzhou, Zhejiang, China

Guoxian Xiao, Jorge Arinez

General Motors R&D, Warren, MI

Paper No. MSEC2015-9307, pp. V002T04A007; 8 pages
  • ASME 2015 International Manufacturing Science and Engineering Conference
  • Volume 2: Materials; Biomanufacturing; Properties, Applications and Systems; Sustainable Manufacturing
  • Charlotte, North Carolina, USA, June 8–12, 2015
  • Conference Sponsors: Manufacturing Engineering Division
  • ISBN: 978-0-7918-5683-3
  • Copyright © 2015 by ASME and General Motors


Timely performance of preventive maintenance (PM) tasks is a critical element of manufacturing systems. The current PM at most manufacturing plants is to conduct maintenance tasks during non-production shifts, breaks, or other scheduled downtime. This practice may introduce unnecessary extra labor and overhead costs. Therefore, there is need to look for hidden maintenance opportunities to perform PM tasks during normal production time without impacting throughput. Additional benefit of the hidden opportunity window is that it can be translated to hidden energy saving opportunity during which machines can be strategically shut down or turned to energy saving mode while PM can be performed. Since production schedules are always made beforehand, the development of opportunity window and the downtime schedule need future prediction about the production system. In this paper, a stochastic model of the downtime opportunity on serial production systems is developed. Based on the stochastic model, revised opportunity window and recovery time is defined, which can help on production control on deciding when and where to insert the downtime events and the duration of the downtime events for the incoming process.

Copyright © 2015 by ASME and General Motors



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