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首页> 外文期刊>Journal of Intelligent Manufacturing >Scalability and performance of computational structures for real-time order promising
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Scalability and performance of computational structures for real-time order promising

机译:实时订单前景广阔的计算结构的可伸缩性和性能

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摘要

This paper analyzes the scalability and performance of computational structures used in an order promising method designed for discrete build-to-order environments facing dynamic order arrivals. Main-memory database technology and supporting index structures are exploited to improve scalability of this data-intensive procedure so that orders can be promised in real time for industrial-sized systems. Two index structures, a linear structure and a tree structure, are compared. The tree structure improves response times and also has higher scalability at the expense of larger memory requirements compared to the linear structure. Performance of the method is evaluated under two manufacturing scenarios: a tandem line and an assembly shop. Computational results obtained from large-scale simulation studies of realistic systems with 60 resources show the method to be robust. Accuracy of the method in terms of median absolute lateness surpasses that of due date assignment methods previously examined in the literature.
机译:本文分析了针对面向动态订单到达的离散按单构建环境设计的有前途方法中使用的计算结构的可伸缩性和性能。利用主内存数据库技术和支持的索引结构来改善此数据密集型过程的可伸缩性,以便可以对工业规模的系统实时承诺订单。比较了两个索引结构,线性结构和树形结构。与线性结构相比,树形结构改善了响应时间,并且还具有更高的可伸缩性,但以更大的内存需求为代价。该方法的性能在两种制造场景下进行评估:串联生产线和装配车间。从具有60种资源的现实系统的大规模仿真研究中获得的计算结果表明,该方法是可靠的。就中值绝对延迟而言,该方法的准确性超过了先前在文献中检验的到期日分配方法的准确性。

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