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

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. Significance for defence and security Under peaceful conditions, operating mangers in the Canadian Armed Forces (CAF) are encouraged to dynamically find out best decisions for maintenance systems, where the word of "best" refers to the balance between operating costs and fleet reliabilities. As one of the fastest operations to recover a weapon system, especially for critical parts, cannibalization is widely used by operating managers. For example, according to the Canadian Army Divestment Plan, the CAF National Procurement reductions will constrain the CAF to prematurely divest up to half of its Heavy Logistics Vehicle Wheeled, Light Support Vehicles Wheeled, and BandVangn to maintain operational readiness to meet CAF missions. This report developed an optimization model to find the best maintenance decisions with cannibalization and presented solution approaches to the model. Operating managers would use the model to make repair decisions at the operational level over a finite number of time periods. DRDC-RDDC-2014-R165 i