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Two-level manufacturing system performance analyser

机译：两级制造系统性能分析仪

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摘要

Open queuing network is a commonly used analytical tool for modelling manufacturing systems. Parametric decomposition is a proven solution method for analysing open queuing networks and can estimate key performance measures such as work-in-process inventory, cycle time, and machine utilisation, fairly accurately. This paper presents a two-level hierarchical open queuing network model, which considers numerous features seen in a real manufacturing system including, machine set-up, material handling device setup (for example, loading and unloading operations), process as well as transfer batching, empty travel of the material handling device and machine or material handling device failures. The model first analyses a higher level open queuing network whose nodes are aggregations of a set of machines. The higher level network is solved via the parametric decomposition method and the results are then disaggregated to get lower level, e.g. machine specific, results. The motivation, algorithm and its relationship with the one-level model are discussed. Experimental results are provided to show that the two-level model provides comparable results with the one-level model in addition to its computational and managerial advantages. In addition, both are shown to provide better results than a recent method available in the literature that is based on the well-known queuing network analyser.
机译：开放式排队网络是用于建模制造系统的常用分析工具。参数分解是一种用于分析开放式排队网络的行之有效的解决方案，可以相当准确地估算关键性能指标，例如在制品库存，周期时间和机器利用率。本文提出了一个两级分层开放排队网络模型，该模型考虑了在实际制造系统中看到的众多功能，包括机器设置，物料搬运设备设置（例如，装卸操作），过程以及转移批处理。 ，物料搬运设备空行程以及机器或物料搬运设备故障。该模型首先分析其节点是一组计算机的集合的更高级别的开放排队网络。较高级别的网络可通过参数分解方法求解，然后分解结果以获取较低级别的网络，例如特定于机器的结果。讨论了动机，算法及其与一级模型的关系。提供的实验结果表明，除了具有计算和管理优势外，两层模型还提供了与一层模型相当的结果。此外，与基于已知排队网络分析器的文献中提供的最新方法相比，两者均显示出更好的结果。

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