Reliability assessment of multistate flexible manufacturing cells considering equipment failures

Abstract

The reliability evaluation of a flexible manufacturing cell (FMC) is valuable for engineers in comprehending the system's reliability level and making well-informed decisions. Nevertheless, the inherent randomness and heterogeneity in the FMC production process present challenges in assessment, making traditional reliability evaluation metrics designed for single machines partially inadequate. This study conducts a comprehensive analysis of various FMC states, encompassing normal operation, failure downtime, and non-failure idle time. Additionally, variables such as part processing time, part transportation time, and equipment maintenance time are treated as stochastic variables conforming to an exponential distribution. Markov processes are employed to model the production processes of both FMC types, with closed solutions for steady-state conditions derived. This analytical approach facilitates a more streamlined and precise computation of reliability metrics as compared to simulation analysis. As a result, reliability evaluation metrics including equipment utilization, manufacturing capacity, and productivity are utilized to assess FMC reliability. Calculation methods for these metrics are established based on the derived analytical solutions. Furthermore, a practical case study is presented to illustrate and validate the proposed model. The primary contribution of this paper is the provision of a stochastic process modeling approach for FMCs, along with system-level reliability assessment indicators and their corresponding calculation methods. This empowers engineers to efficiently and effectively evaluate FMC reliability within the context of their production processes, facilitating informed decision-making.