Joint Optimization of System Design and Maintenance Planning for Systems under Uncertain Environment

In this talk, we present a new approach to optimally and simultaneously design the configuration of a multi-component system and determine a maintenance plan with uncertain future stress exposure. Traditionally, analytical models for system design and maintenance planning have been applied sequentially and thus potentially inefficient. We consider the lifecycle cost of the system under the uncertain future usage stresses on component and system reliability, and develop a two-stage stochastic programming model with recourse to integrate the redundancy allocation and maintenance planning problems. The first stage decision variables determine the selection of component types and the number of components to be used in the system, and these decisions must be made before the uncertainty is revealed. The second-stage variables, involving a recourse function, are the preventive maintenance plan, which defines optimal maintenance times for planned replacement of components under distinct usage scenarios. The model is then extended to a four-stage optimization model to accommodate sequences of decisions over time with random future usage scenarios. The comparisons of the proposed integrated approach to traditional sequential method show advantages of the proposed model in cost saving.