Maintenance scheduling for modular systems-models and algorithms
Author(s)Zarybnisky, Eric J. (Eric Jack), 1979-
Massachusetts Institute of Technology. Operations Research Center.
Retsef Levi and Thomas L. Magnanti.
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Maintenance scheduling is an integral part of many complex systems. For instance, without effective maintenance scheduling, the combined effects of preventative and corrective maintenance can have severe impacts on the availability of those systems. Based on current Air Force trends including maintenance manpower, dispersed aircraft basing, and increased complexity, there has been a renewed focus on preventative maintenance. To address these concerns, this thesis develops two models for preventative maintenance scheduling for complex systems, the first of interest in the system concept development and design phase, and the second of interest during operations. Both models are highly complex and intractable to solve in their original forms. For the first model, we develop approximation algorithms that yield high quality and easily implementable solutions. To address the second model, we propose a decomposition strategy that produces submodels that can be solved via existing algorithms or via specialized algorithms we develop. While much of the literature has examined stochastically failing systems, preventative maintenance of usage limited systems has received less attention. Of particular interest is the design of modular systems whose components must be repaired/replaced to prevent a failure. By making cost tradeoffs early in development, program managers, designers, engineers, and test conductors can better balance the up front costs associated with system design and testing with the long term cost of maintenance. To facilitate such a tradeoff, the Modular Maintenance Scheduling Problem provides a framework for design teams to evaluate different design and operations concepts and then evaluate the long term costs. While the general Modular Maintenance Scheduling Problem does not require maintenance schedules with specific structure, operational considerations push us to consider cyclic schedules in which components are maintained at a fixed frequency. In order to efficiently find cyclic schedules, we propose the Cycle Rounding algorithm, which has an approximation guarantee of 2, and a family of Shifted Power-of-Two algorithms, which have an approximation guarantee of 1/ ln(2) ~ 1.4427. Computational results indicate that both algorithms perform much better than their associated performance guarantees providing solutions within 15%-25% of a lower bound. Once a modular system has moved into operations, manpower and transportation scheduling become important considerations when developing maintenance schedules. To address the operations phase, we develop the Modular Maintenance and System Assembly Model to balance the tradeoffs between inventory, maintenance capacity, and transportation resources. This model explicitly captures the risk-pooling effects of a central repair facility while also modeling the interaction between repair actions at such a facility. The full model is intractable for all but the smallest instances. Accordingly, we decompose the problem into two parts, the system assembly portion and module repair portion. Finally, we tie together the Modular Maintenance and System Assembly Model with key concepts from the Modular Maintenance Scheduling Problem to propose an integrated methodology for design and operation.
Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 185-188).
DepartmentMassachusetts Institute of Technology. Operations Research Center.
Massachusetts Institute of Technology
Operations Research Center.