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A Novel Reliability Evaluation Technique for Stochastic-Flow Manufacturing Networks With Multiple Production Lines

机译：多生产线随机流制造网络的可靠性评估新技术

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摘要

This paper presents a novel technique to measure the performance of a stochastic-flow manufacturing network (SMN) which violates the so-called flow conservation law due to the failure rates of stations. We address the mission reliability, the probability of demand satisfaction, as a performance indicator for the SMN while considering both the stochastic capacities and the multiple production lines. First, we construct a manufacturing system as an SMN through a graphical transformation, and decompose the transformed SMN into several paths for further analysis. Subsequently, two algorithms for different scenarios are designed to generate all minimal capacity vectors that stations should provide to satisfy the given demand. The first scenario is for the SMN with identical production lines in parallel. The second scenario is for distinct production lines with common stations in the SMN. We derive the mission reliability in terms of minimal capacity vectors by applying the recursive sum of disjoint products (RSDP) algorithm. A decision making issue is also discussed to decide a reliable production strategy.
机译：本文提出了一种测量随机流制造网络（SMN）性能的新技术，该技术由于站的故障率而违反了所谓的流量守恒定律。我们将任务可靠性，需求满足的概率作为SMN的性能指标，同时考虑了随机产能和多条生产线。首先，我们通过图形转换将制造系统构建为SMN，然后将转换后的SMN分解为若干路径以进行进一步分析。随后，针对不同场景设计了两种算法，以生成站点应提供以满足给定需求的所有最小容量向量。第一种情况是针对具有相同并行生产线的SMN。第二种情况是针对SMN中具有公用工作站的不同生产线。我们通过应用不相乘积的递归和（RSDP）算法，以最小容量向量推导任务可靠性。还讨论了决策问题，以决定可靠的生产策略。

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