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Analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing.

机译:分析近似值可预测具有工作故障和并行处理的制造系统的性能指标。

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摘要

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.
机译:并行处理在许多制造和服务系统中很普遍。许多制造的产品都是由平行生产的几个组件制造和组装的。在配备用于组装和测试Web服务器的制造工厂中观察到此制造系统配置的示例。典型的Web服务器组装线的特征是:多种产品,工作循环和并行处理。这项研究的主要目的是开发分析近似值,以预测具有工作失败和并行处理的制造系统的性能指标。这些分析公式扩展了装配制造系统中使用的先前排队模型,因为它们可以处理具有多个产品类别的并行处理的串行和不同配置,以及由于零件随机故障而导致的工作循环。另外,通过回归分析将适当的校正项添加到近似值中,以最大程度地减少分析近似值和模拟模型之间的误差。研究了具有多个产品类别,由于故障而导致的工作循环以及模型化并行处理的fork和join系统的Markovian和常规类型的制造系统。在马尔可夫和一般情况下,没有校正项的逼近对于一个和两个乘积问题实例表现得很好。但是,观察到流动时间误差随产品数量和净流量强度的增加而增加。因此,通过回归分析开发了单站和分叉站的校正项,以处理两种以上的产品。数值比较表明,当在近似中使用校正因子时,近似的性能非常好。通常,在马尔可夫情况下,平均流动时间误差从38.19%降低到5.59%,在一般情况下,从26.​​39%降低到7.23%。分析公式中陈述的所有方程式都是作为一组Matlab脚本实现的。通过使用此集合,具有类似特征的Web服务器装配线,制造或其他服务系统的运营经理可以估算不同的系统性能指标,并做出明智的决定-特别是设置交付到期日,容量计划和缓解瓶颈等。

著录项

  • 作者

    Hulett, Maria de Lourdes.;

  • 作者单位

    Florida International University.;

  • 授予单位 Florida International University.;
  • 学科 Engineering, Industrial.;Operations Research.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 258 p.
  • 总页数 258
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 ;
  • 原文服务方 国家工程技术数字图书馆
  • 关键词

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