Accession Number : AD1003618


Title :   Detailed Maintenance Planning for Military Systems with Random Lead Times and Cannibalization


Descriptive Note : Technical Report


Corporate Author : DRDC - Centre for Operational Research and Analysis Ottawa ON Canada


Personal Author(s) : Zhang,R ; Ghanmi,A


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/1003618.pdf


Report Date : 01 Dec 2014


Pagination or Media Count : 52


Abstract : 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 ofthe 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 tosolve the maximization problem. The obtained solutions were proved to be controllable in such away that solutions with designated approximation ratios were achievable by running the algorithmin predictable run times.


Descriptors :   approximation , cannibalization , production , dynamic programming , planning , reliability , scenarios , budgets , maintenance , uncertainty , decision making , repair


Distribution Statement : APPROVED FOR PUBLIC RELEASE