Reliability analysis of waste clean-up manipulator using genetic algorithms and fuzzy methodology

In this paper, the reliability analysis of waste clean-up manipulator has been performed using Real Coded Genetic Algorithms and Fuzzy Lambda Tau Methodology. The optimal values of mean time between failures and mean time to repair are obtained using genetic algorithms. Petri Net tool is applied to represent the interactions among the working components of the system. To enhance the relevance of the reliability study, triangular fuzzy numbers are developed from the computed data, using possibility theory. The use of fuzzy arithmetic in the Petri Net model increases the flexibility for application to various systems and conditions. Various reliability parameters (failure rate, repair time, mean time between failures, expected no. of failures, reliability and availability) are computed using Fuzzy Lambda Tau Methodology. Sensitivity analysis has also been performed and the effects on system mean time between failures are addressed. The adopted methodology improves the shortcomings/drawbacks of the existing probabilistic approaches and gives a better understanding of the system behavior through its graphical representation.