An Investigation of Stochastic Analysis of Flexible Manufacturing Systems Simulation
An Investigation of Stochastic Analysis of Flexible Manufacturing Systems Simulation
复制标题
柔性制造系统仿真随机分析的研究
DOI：
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发表时间：
1999
期刊：
影响因子：
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通讯作者：
K. W. Keung
中科院分区：
文献类型：
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作者：
W. Ip;R. Fung;K. W. Keung
本文介绍了如何使用 ARIMA（自回归积分移动平均）模型及其等效的状态空间模型来为柔性制造系统 (FMS) 生成基于规则的知识，该知识可用于研究各种问题，包括机器故障、材料短缺和调度规则更改。使用所提出的模型的一大优点是可以轻松地总结、分析和捕获模拟结果，以及可以将知识的数学表示形式保存在知识数据库中，以便在实时环境中评估和选择替代 FMS 策略。使用各种案例研究来说明ARIMA和状态空间模型的方法和发展，分析包括系统成本和变化或干预的稳定性、模拟输入和输出之间的关系以及FMS调度器的生产规则库的制定。管理层可以使用这种集成方法来描述和预测复杂 FMS 的动态行为。
This paper describes the use of an ARIMA (autoregressive-integrated- moving-average) model and its equivalent state space models to produce rule-based knowledge for flexible manufacturing systems (FMS) that can be used to investigate a wide variety of problems including machine breakdown, material shortage, and changes of scheduling rules. One great advantage of using the proposed models is the ease with which the simulation results can be summarised, analysed and captured, as well as the availability of the mathematical representation of the knowledge that can be kept in a knowledge database for evaluation and selection of alternative FMS strategies in a real-time environment. Various case studies are used to illustrate the methodology and the development of ARIMA and state space models, the analysis includes the system cost and stability of changes or interventions, the relationships among the simulation inputs and outputs, and the formulation of the production rule-base for the FMS scheduler. Management can use this integrated approach to describe and predict the dynamic behaviour of a complex FMS.