Testing strategies for k-out-of-n systems under forest type precedence constraints

Abstract

This thesis investigates diagnosis strategies for k-out-of–n systems under precedence constraints. A k-out-of-n system consists of n independent components whose working probabilities of are known in advance. The system itself functions if at least k components function. The true state of the system is determined by the sequentially inspection of these components. This inspection is costly and the cost of inspection for each component is also known. This study aims to minimize expected cost of determining true state of such a system when there are forest type precedence constraints. Optimal inspection strategies are already known for series and parallel systems. In this study, modifications of these strategies are proposed for k-out-of-n systems. Numerical results are presented to evaluate and compare the proposed strategies.