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Robot reliability has become an increasingly important issue in the last fewyears due to increased application of robots in many industries (likeautomobile industry) under hazardous and unstructured environment. As thecomponent failure behavior is dependent on configuration and environment, theavailable information about the constituent component of robots is most of thetime imprecise, incomplete, vague and conflicting and so it is very difficultto analyze their behavior and to predict their failure pattern. The reliabilityanalysis of any system provides an understanding about the likelihood offailures occurring in the system/component and the increased insight about itsinherent weakness. The objective of this paper is to quantify the uncertaintiesthat makes the decision more realistic, generic and extendable to applicationdomain. In this paper various reliability parameters (such as mean time betweenfailures, expected number of failures, reliability, availability etc.) arecomputed using Fuzzy Lambda-Tau methodology. Triangular fuzzy numbers are usedto represent failure rates and repair times as they allow expert opinion,linguistic variables, operating conditions, uncertainty and imprecision inreliability information, to be incorporated into system model. Petri Nets areused because unlike the fault tree methodology, the use of Petri Nets allowsefficient simultaneous generation of minimal cut and path sets.

Robot Reliability Using Petri Nets and Fuzzy Lambda-Tau Methodology