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Flexible modelling of correlated operation times with application in product-reuse facilities

机译:关联操作时间的灵活建模及其在产品回用设施中的应用

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摘要

For each job (product instance) to be serviced in a product-reuse production system, multiple operations are often scheduled. Typically, there is high variability in the same operation times required by different jobs; and for each individual job, there is often significant probabilistic dependence (correlation) between many of the job's required operation times. Well-conditioned jobs require fewer operations with shorter durations. Poorly conditioned jobs require more operations with longer durations. Accurate and rapid methods for representing the uncertainty of operation necessity and duration are required to use simulation effectively as a schedule evaluation tool. This paper develops such methods using an alternative to the conventional multivariate extension of the Johnson system of univariate probability distributions. The alternative methods match the first three, and often four, marginal moments of the random vector of operation times for a given job as well as all pairwise correlations between those operation times. A logistic regression model is used to estimate the distribution of the binary random variable indicating the necessity of an operation conditioned on the indicators for the job's preceding operations. The proposed overall mixed-distribution modelling technique is computationally efficient, useful in product-reuse system practice, and easily integrated into existing simulation software platforms.
机译:对于要在产品重用生产系统中提供服务的每个作业(产品实例),通常会计划多个操作。通常,不同作业所需的相同操作时间差异很大。对于每个单独的工作,许多工作所需的操作时间之间通常存在很大的概率依赖性(相关性)。状况良好的工作需要较少的操作且持续时间较短。条件差的工作需要更长的时间进行更多的操作。需要使用准确,快速的方法来表示操作必要性和持续时间的不确定性,才能有效地将模拟用作计划评估工具。本文使用单变量概率分布的Johnson系统的常规多元扩展的替代方法来开发此类方法。替代方法匹配给定作业的操作时间随机向量的前三个(通常是四个)边际矩,以及这些操作时间之间的所有成对相关性。使用逻辑回归模型来估计二进制随机变量的分布,该二进制随机变量指示以作业的先前操作的指标为条件的操作的必要性。所提出的总体混合分布建模技术具有高效的计算能力,可用于产品重用系统实践,并且易于集成到现有的仿真软件平台中。

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