Estimation and Optimization for System Availability Under Preventive Maintenance

• Published in: IEEE access Vol. 10; pp. 94337 - 94353
• Main Authors: Raghav, Yashpal Singh, Mradula, Varshney, Rahul, Modibbo, Umar Muhammad, Ahmadini, Abdullah Ali H., Ali, Irfan
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Availability; Availability constraints; Continuity (mathematics); Cost function; Decision making; exponential distribution; Genetic algorithms; Goal programming; Maintenance engineering; Markov processes; Optimization; Particle swarm optimization; Preventive maintenance; preventive maintenance policy; Reliability; Robustness (mathematics); series-parallel system; Statistical tests; System failures
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2022.3204394

Engineers design systems to be reliable and work to fulfil their missions without failure for a specific period. However, the system components deteriorate with time and lead to its failures. A frequent system failure increases the management costs, hence posing a challenge to decision-makers. Therefore, for the avoidance of frequent system failures, preventive maintenance is necessary. The objective of any manufacturing firm is to maximize profit and minimize costs. The interval for preventive maintenance can be optimized if the system's availability is maximized and its cost function minimized. This study evaluates the availability and cost function for a continuous operating series-parallel system under a fixed time environment. A multiobjective model is formulated to maximize the availability and minimize the cost function of the system. The study illustrated a numerical example and solved using goal programming (GP), fuzzy goal programming (FGP), genetic algorithm (GA), and particle swarm optimization (PSO) techniques. The results are compared using a robust statistical test and, the PSO proves to be better. A simulation study was carried out further to evaluate the availability and cost function using R and MATLAB packages.