Reliability analysis of complex multi-robotic system using GA and fuzzy methodology
The objective of the study is to compute various reliability parameters for multi-robotic system, using Real Coded Genetic Algorithms (RCGAs) and Fuzzy Lambda-Tau Methodology (FLTM). The paper contains a new idea about the reliability analysis of robotic system. The optimal values of mean time between failures (MTBF) and mean time to repair (MTTR) are obtained using GAs. Petri Net (PN) tool is applied to represent the interactions among the working components of multi-robotic system. To enhance the relevance of the reliability study, triangular fuzzy numbers (TFNs) are developed from the computed data, using possibility theory. The use of fuzzy arithmetic in the PN model increases the flexibility for application to various systems and conditions. Various reliability parameters, namely failure rate, repair time, MTBF, expected number of failures (ENOF), reliability and availability, are computed using FLTM. Sensitivity analysis has also been performed and the effects on system MTBF 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. The analysis presented, may be helpful for the system analyst to analyze and predict the system behavior and to reallocate the required resources.
reliability genetic algorithms optimization mtbf petri nets linguistic variables