An integrated approach for fuzzy reliability analysis and resource allocation of a repairable industrial system

In this paper, an integrated approach for fuzzy reliability analysis and resource allocation has been presented for a paper machine of a paper mill comprises forming, press and dryer units. In the presented approach, imprecise and vague failure/repair data of system components is fuzzified using triangular fuzzy numbers (TFNs). Using fuzzified data, genetic algorithms-based lambda-tau (GABLT) technique is used to obtain system main subsystems (stages) fuzzy reliabilities which are then defuzzified. A resource allocation problem (RAP) has been formulated as a multistage decision-making problem. Formulated RAP considers system reliability as the objective function while maintenance and manpower costs as constraints. The approach makes use of defuzzified values of subsystems' reliability along with relevant system information (number of components, manpower, cost ranges). Resulting single objective optimisation problem is then solved by using dynamic programming based on recursive Lagrange multiplier technique. To show the merits of the approach, computed results have been compared with existing results.system reliability; resource allocation problem; RAP; triangular fuzzy number; TFN; genetic algorithms-based lambda-tau; GABLT; Lagrange multiplier technique