Maintenance Opportunity Planning System

[+] Author and Article Information
Qing Chang

Manufacturing Systems Research Lab, General Motors Research and Development Center, 30500 Mound Road, Warren, MI 48090-9055cindy.chang@gm.com

Jun Ni

Department of Mechanical Engineering, University of Michigan—Ann Arbor, 1023 H. H. Dow, 2300 Hayward St., Ann Arbor, MI 48109-2136junni@umich.edu

Pulak Bandyopadhyay, Stephan Biller, Guoxian Xiao

 Manufacturing Systems Research Lab, GM R&D Center, 30500 Mound Road, Warren, MI 48090

J. Manuf. Sci. Eng 129(3), 661-668 (Feb 07, 2007) (8 pages) doi:10.1115/1.2716713 History: Received May 10, 2006; Revised February 07, 2007

Timely performance of preventive maintenance (PM) tasks is a critical element of manufacturing systems. Since the majority of PM tasks requires that equipment be stopped, these tasks can generally only be performed during nonproduction shifts, breaks, or other scheduled downtime. Thus, there is a trade-off between time dedicated to production and time available for preventive maintenance. One approach to mitigate this trade-off is to perform maintenance during scheduled production time by strategically shutting down equipment for short time periods. This research developed a systematic method on when to shut down equipment to do maintenance in an automotive assembly environment. It is called maintenance opportunity. The method incorporated real-time information about production and machine failure conditions. A simulation-based algorithm is developed by utilizing the buffer contents as well as machine starvation and congestion to obtain maintenance opportunities during production time.

Copyright © 2007 by American Society of Mechanical Engineers
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Figure 1

Maintenance opportunity

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Figure 10

Throughput impact of 50% capacity criterion applied over time

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Figure 2

Two-machine one-buffer line

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Figure 3

Maintenance opportunity versus critical time

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Figure 4

Tangent change when ṁ1 close to ṁ2

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Figure 5

Serial line with k machines k−1 buffers

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Figure 6

Flowchart of the algorithm to find the maintenance opportunity for each station

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Figure 7

Sample line configuration and parameters

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Figure 8

Throughput impact caused by S2 maintenance opportunity window

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Figure 9

Throughput impact caused by the S4 maintenance opportunity window



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