Stochastic analysis of potato chips plant model under classical and bayesian set UPS

This paper presents the stochastic analysis of a real existing industrial system model of potato chips under Classical and Bayesian set ups. The system consists of four different subsystems viz. Destoning and Peeling (D), Slicing (S), Coloring (C) and Frying & Salting (F). Out of four subsystems, one subsystem (Destoning and Peeling) has its cold standby unit. All these subsystems are connected in series configuration. Life time distributions and repair time distributions of each sub system are assumed to be independent Weibull with different scale parameters but common shape parameter. A single repairman is always available with the system. The repair discipline is first come first served (FCFS). Maximum Likelihood Estimation of the parameters representing the reliability characteristics is also done. A Bayesian approach is also adopted to evaluate the reliability characteristics. Finally, a Monte Carlo simulation study is carried out to judge the performances of the ML and Bayes estimator.