Performance modeling of automated manufacturing systems
Performance modeling of automated manufacturing systems
Performance analysis of scheduling policies in re-entrant manufacturing systems
Computers and Operations Research
Stability and instability of fluid models for reentrant lines
Mathematics of Operations Research
Mean-Value Analysis of Closed Multichain Queuing Networks
Journal of the ACM (JACM)
Experiments with improved approximate mean value analysis algorithms
Performance Evaluation - Special issue on modelling techniques and tools for performance evaluation
Mean value analysis of re-entrant line with batch machines and multi-class jobs
Computers and Operations Research
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This paper proposes an approximation method based on mean value analysis (MVA) technique for estimating the performance measures of re-entrant manufacturing system with production loss. The model is an extension of the one proposed by Park et al. (Comput. Oper. Res. 29 (2002) 1009). A unique feature in the extended model is that random production losses due to machine failures and yields are considered. Considering such losses is critical in performance evaluation, because it may often cause significant errors in the results compared to the real values if the analysis does not explicitly consider them. However, such random losses substantially increase the complexity of the analysis, due to the fact that even through simulation it requires not only extra modeling efforts, but also a number of replications. As a result, it requires bigger efforts and data, and significantly longer computational times. For an analytical approach, such random losses also prohibit exact analysis of the system. Therefore, a methodology for analyzing the system approximately is proposed using the iterative procedures based upon the MVA and some heuristic adjustments. The performance measures of interest are the steady-state average of the cycle time of each job class, the queue length of each buffer, and the throughput of the system. Numerical tests are presented to show the performance of the proposed approach against the simulation results. Also, the comparisons with the earlier test results summarize the insights from the overall research thus far.