Modeling of reconfigurable manufacturing system architecture with geometric machines and in-stage gantries

Reconfigurable Manufacturing Systems (RMSs) are well recognized by their capability to achieve high responsiveness and flexibility and are receiving increasing interest in today's versatile manufacturing environment. This paper aims to develop methods to study the performance of RMS architecture consisting of machines and in-stage gantries whose time to failure and time to repair follow geometric distributions. A discrete-time Markov chain model is built to perform an exact analysis for two-stage-one-buffer systems. A decomposition method is developed to analyze multi-stage systems. Moreover, both time-dependent failure and operation-dependent failure modes are considered. Numerical studies that compare the calculated production rate and work-inprocess to the simulation results demonstrate that the proposed methods can provide accurate results, especially for balanced systems and for systems with a small number of stages. The impact of different parameters (e. g., buffer capacity, machine/gantry reliability) on the production rate of the two models is also studied. Finally, examples on the applications of the models in the manufacturing systems design and operations are presented.

Automated summary

This paper focuses on the study of Reconfigurable Manufacturing Systems (RMSs) and develops methods to analyze their performance, using models such as discrete-time Markov chains and decomposition methods to provide accurate results in production rate calculations.