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Performance evaluation of re-entrant manufacturing system with production loss using mean value analysis

机译:基于均值分析的具有生产损失的可重入制造系统的性能评估

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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.
机译:本文提出了一种基于均值分析(MVA)技术的近似方法,用于评估具有生产损失的可重入制造系统的性能指标。该模型是Park等人提出的模型的扩展。 (计算机操作研究,29(2002)1009)。扩展模型的独特之处在于可以考虑由于机器故障和良率导致的随机生产损失。考虑到此类损失对于性能评估至关重要,因为如果分析未明确考虑这些损失,则与实际值相比,可能经常导致结果出现重大错误。但是,由于即使通过仿真,它不仅需要额外的建模工作,而且还需要大量复制,因此这种随机损失会大大增加分析的复杂性。结果,它需要更大的工作量和数据,并且需要更长的计算时间。对于分析方法,这种随机损失也妨碍了系统的精确分析。因此,提出了一种基于MVA和一些启发式调整的迭代过程,用于近似分析系统的方法。感兴趣的性能度量是每个作业类的周期时间的稳态平均值,每个缓冲区的队列长度以及系统的吞吐量。数值测试表明了该方法对仿真结果的性能。此外,与早期测试结果的比较总结了迄今为止的整体研究的见解。

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