Abstract
Maintenance planning is a subject of concern to many industrial sectors as plant safety and business depend on it, and can be formulated in terms of a multi-objective optimization problem where reliability, availability, maintainability and cost act as decision criteria and surveillance test and maintenance strategies act as decision variables. Usually, the frequency of performing a maintenance task is considered, in the optimization process, as a constant value but a certain range of variation from such value is observed in real practice. Thus, to obtain a more realistic approach, a certain degree of uncertainty should be considered in the decision variables. This paper presents two examples of maintenance optimization using Particle Swarm as optimization technique and a tolerance interval based approach to address uncertainty, one is focused on a safety component and the other considers a nuclear power plant safety system. © 2012 Civil-Comp Ltd and Elsevier Ltd. All rights reserved.
