Application of Monte Carlo Simulation in Modeling the Lifetime of Industrial Components

This paper explores the application of Monte Carlo Simulation (MCS) to model the lifetime of industrial components, specifically focusing on a contactor commonly used in automation systems. The study emphasizes the challenges posed by the variability in system performance and the need to incorporate expert knowledge for accurate modeling. Using expert data, MCS is employed to simulate different scenarios and determine a probabilistic distribution that reflects the uncertainties in component lifespan. The analysis reveals that factors such as temperature, environmental conditions, and switching frequency have significant impacts on the failure rate of the component, thereby influencing its reliability. The results demonstrate the effectiveness of MCS in providing a more precise estimation of component lifetime, offering valuable insights for maintenance planning and operational decision-making. The study concludes that incorporating Monte Carlo methods into reliability assessments enhances the ability to manage risk and optimize system performance, ensuring safer and more efficient operation of industrial systems.

Keywords: Monte carlo simulation, Industrial reliability, Component lifetime, Expert knowledge, Probabilistic modeling, Failure rate.