Detailed maintenance planning for military systems with random lead times and cannibalization


  1. Zhang, R.
  2. Ghanmi, A.
Corporate Authors
Defence Research and Development Canada, Centre for Operational Research and Analysis, Ottawa ON (CAN)
Detailed maintenance planning under uncertainty is one of the most important topics in military research and practice. As one of the fastest ways to recover failed weapon systems, cannibalization operations are commonly applied by maintenance personnel. Due to additional complexities introduced by these operations, detailed maintenance decision making with cannibalization was rarely studied in the literature. This report proposed an analytic model for making repair decisions in a multi-stage uncertain environment at the operational level, where cannibalization operations are allowed and repair lead times are random. The study addresses the problem of maintenance planning for military systems with random lead times and independent failures. The objective of the problem is to maximize fleet reliabilities under operating costs constraints. A complementary problem that minimizes total operating costs under fleet reliabilities constraints was also examined. A polynomial algorithm was proposed to solve the minimization problem and determine optimal decision strategies. This algorithm could be used as a subroutine in a binary-search algorithm to solve the maximization problem. The obtained solutions were proved to be controllable in such a way that solutions with designated approximation ratios were achievable by running the algorithm in predictable run times.

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Report Number
DRDC-RDDC-2014-R165 — Scientific Report
Date of publication
01 Dec 2014
Number of Pages
Electronic Document(PDF)

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