APPROXIMATE ANALYTICAL PERFORMANCE MODELS FOR AUTOMATIC ASSEMBLY SYSTEMS WITH STATISTICAL PROCESS-CONTROL AND AUTOMATED INSPECTION

Analytical methods for modeling manufacturing systems have emerged as promising performance evaluation techniques. Some analytical tools have been developed for the performance evaluation of automatic assembly systems (AASs), which form an important class of manufacturing systems. In some AASs there is a strong interaction between statistical process control of the assembly process and the dynamics of the assembly system. This paper presents an analytical performance evaluation model where this interaction has been integrated with the system dynamics. The analytical tool models the splitting and merging of the flow of the assemblies among the main and repair loops of the assembly system in addition to the dynamics of the main system. The model is a general one that can be used to model AASs with several automatic inspection stations and counter-flow repair loops. For the statistical process control, Dodge CSP-1 plans, which have wide application for continuous production, are chosen. AASs with a single automatic inspection station and counter-flow repair loop with various system parameters are discussed as examples. The ability of the proposed analytical model to accurately predict the performance of the AASs is demonstrated. The system throughput as a function of process quality is analyzed.