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Research Papers

Reliability-Based Dynamic Maintenance Threshold for Failure Prevention of Continuously Monitored Degrading Systems

[+] Author and Article Information
Lin Li1

Department of Mechanical Engineering, University of Michigan–Ann Arbor, 1035 H. H. Dow, 2350 Hayward Street, Ann Arbor, MI 48109-2136lilz@umich.edu

Mingyi You

State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, P. R. Chinayoumingyi@sjtu.edu.cn

Jun Ni

Department of Mechanical Engineering, University of Michigan–Ann Arbor, 1023 H. H. Dow, 2350 Hayward Street, Ann Arbor, MI 48109-2136junni@umich.edu

1

Corresponding author.

J. Manuf. Sci. Eng 131(3), 031010 (May 19, 2009) (9 pages) doi:10.1115/1.3123340 History: Received September 07, 2008; Revised March 13, 2009; Published May 19, 2009

Machine failures in manufacturing systems interrupt production operations and cause production loss. The conventional methods for failure prevention are to perform preventive maintenance before failure occurs. In these methods, a fixed maintenance threshold (FMT) is obtained using the lifetime distribution of each machine. This threshold can then be used to trigger maintenance work-orders. A problem with the conventional technique is that it does not consider the updated state of the system, which continues to change before and after maintenance. Therefore, unnecessarily high costs can be incurred due to unexpected equipment failure (lack of maintenance) or excessive maintenance. In this paper, a reliability-based dynamic maintenance threshold (DMT) is calculated based on the updated equipment status. The benefits of the DMT are demonstrated in a numerical case study on a drilling process. The results illustrate that the maintenance policy using the DMT can reduce unscheduled downtime, increase equipment availability, and utilize the equipment remaining useful life more effectively than a conventional FMT-based maintenance policy.

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Copyright © 2009 by American Society of Mechanical Engineers
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Figures

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Figure 1

Timing in the URLM model

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Figure 2

Optimization algorithm

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Figure 3

Degradation processes of drill bits

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Figure 4

Condition-based cdf of system failure of drill bit 2

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