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Reliability Optimization by Considering Time‐Dependent Reliability for Components
Author(s) -
Abouei Ardakan Mostafa,
Mirzaei Zahra,
Zeinal Hamadani Ali,
Elsayed Elsayed A.
Publication year - 2017
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2132
Subject(s) - redundancy (engineering) , reliability (semiconductor) , reliability engineering , benchmark (surveying) , computer science , function (biology) , optimization problem , mathematical optimization , engineering , mathematics , algorithm , power (physics) , physics , geodesy , quantum mechanics , geography , evolutionary biology , biology
Reliability optimization is an important and challenging topic both in engineering and industrial situations as its objective is to design a highly reliable system that operates more safely and efficiently under constraints. Redundancy allocation problem (RAP), as one of the most well‐known problems in reliability optimization, has been the subject of many studies over the past few decades. RAP aims to find the best structure and the optimal redundancy level for each subsystem. The main goal in RAP is to maximize the overall system reliability considering some constraints. In all the previous RAP studies, the reliability of the components is considered constant during the system's mission time. However, reliability is time‐dependent and needs to be considered and monitored during the system's lifetime. In this paper, the reliability of components is considered as a function of time, and the RAP is reformulated by introducing a new criterion called ‘mission design life’ defined as the integration of the system reliability function during the mission time. We propose an efficient algorithm for this problem and demonstrate its performance using two examples. Furthermore, we demonstrate the importance of the new approach using a benchmark problem in RAP. Copyright © 2017 John Wiley & Sons, Ltd.