Optimising preventive maintenance strategy for production Lines

Sun, Yong, Ma, Lin, & Mathew, Joseph (2012) Optimising preventive maintenance strategy for production Lines. In Amadi-Echendu, Joe, Brown, Kerry A., Willett, Roger, & Mathew, Joseph (Eds.) Asset condition, information systems and decision models [Engineering Asset Management Review, Volume 2]. Springer, United Kingdom, pp. 133-147.

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Preventive Maintenance (PM) is often applied to improve the reliability of production lines. A Split System Approach (SSA) based methodology is presented to assist in making optimal PM decisions for serial production lines. The methodology treats a production line as a complex series system with multiple (imperfect) PM actions over multiple intervals. The conditional and overall reliability of the entire production line over these multiple PM intervals are hierarchically calculated using SSA, and provide a foundation for cost analysis. Both risk-related cost and maintenance-related cost are factored into the methodology as either deterministic or random variables. This SSA based methodology enables Asset Management (AM) decisions to be optimised considering a variety of factors including failure probability, failure cost, maintenance cost, PM performance, and the type of PM strategy. The application of this new methodology and an evaluation of the effects of these factors on PM decisions are demonstrated using an example. The results of this work show that the performance of a PM strategy can be measured by its Total Expected Cost Index (TECI). The optimal PM interval is dependent on TECI, PM performance and types of PM strategies. These factors are interrelated. Generally, it was found that a trade-off between reliability and the number of PM actions needs to be made so that one can minimise Total Expected Cost (TEC) for asset maintenance.

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ID Code: 56661
Item Type: Book Chapter
DOI: 10.1007/978-1-4471-2924-0_7
ISBN: 978-1-4471-2923-3
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 Springer
Deposited On: 24 Jan 2013 02:19
Last Modified: 21 Oct 2015 16:12

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