Performability Analysis and Optimization of a Rice Sheller System Using Stochastic Petri Nets Approach

This paper presents a performability analysis of a rice sheller system using Stochastic Petri Nets to evaluate the impact of subsystem failure and repair behaviours on overall system availability. The modelling framework captures the up, down, and repair states of four key machines—sieve, ruler, paddy separator, and polisher—along with system-level capacity variations. Simulation results show that performance is highly sensitive to changes in failure and repair rates, with the polisher machine identified as the most critical subsystem, contributing to the largest performance decline. Maintenance prioritization and optimization using parameter adjustments and PSO-based modification further enhance system’s availability. Further experiments assess the influence of iteration size and population size on optimization outcomes. The research paper demonstrates that an integrated and optimization approach effectively supports decision-making for improving reliability and operational efficiency in rice milling plants.