Multi-objective optimization of a sequentially inspected system prone to revealing and non-revealing failures via particle swarm optimization and a fuzzy method

Abstract

ABSTRACT Maintenance models rely heavily on the failure characteristics and inspection or maintenance actions. This paper introduced a sequentially inspected system whose failure alternated between revealing and non-revealing failures. The distinctive characteristic of the proposed model is that inspections are imperfect, inspection and maintenance time are non-negligible, and corrective maintenance is perfect. The proposed study contributed on the multi-objective availability and cost optimization issue of the aforementioned system, which was lacking in the prior studies. This paper focused on evaluating the general expressions for limiting availability and long-run average cost of the sequentially inspected system and addressed the multi-objective optimization issue using particle swarm optimization to generate the Pareto optimal solutions followed by a fuzzy method to select the best compromise solution. Moreover, reasonable results were achieved using a numerical case study and the findings of the existing studies were found to be the special case of this model.