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A Study of Knowledge-Based Scheduling of Flexible Manufacturing System

柔性制造系统知识调度研究

基本信息

批准号：
01550208
负责人：
TAMURA Hiroyuki
金额：
$ 1.28万
依托单位：
Osaka Univ.
依托单位国家：
日本
项目类别：
Grant-in-Aid for General Scientific Research (C)
财政年份：
1989
资助国家：
日本
起止时间：
1989 至 1990
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-01550208/
关键词：
Flexible Manufacturing System Scheduling Rule Base Simulation Fuzzy Inference Stochastic Petri Nets ファジィペトリネット

项目摘要

This study deals with on-line and off-line scheduling of a Flexible Manufacturing System (FMS) based on a knowledge engineering approach. To cope with the computational complexity of scheduling problems, we apply a simulation method. When some part types can be processed in a machine, a priority rule is applied to select one part type to be processed. For obtaining an efficient schedule of FMS, we construct a rule base to generate an appropriate priority rule in simulation process. To evaluate the method proposed in our study, we construct three rule-bases whose scheduling objectives are 'Minimizing production leed time', 'Minimizing tardiness time', and 'Just-in-time', respectively. As the result, we confirmed that these three rule bases achieved good performance of each scheduling object.To cope with the difficulty of correcting a knowledge base of scheduling, First, we develop a self-tuning mechanism to adjust some heuristic parameters in the rule-base automatically analyzing the scheduling results obtained previously. Second, we divide the knowledge base into 3 modules ; schedule evaluation, scheduling policy, and dispatching module, which are represented by fuzzy rules. When the scheduling objective is changed, user can easily correct the knowledge base by revising the membership functions of the fuzzy rules in the schedule evaluation module, because the knowledges of sched-ule evaluation module might be realized intuitively.To construct a rule base for obtaining an efficient schedule of FMS with on-line, we develop an FMS simulation system that represent uncertain events, such as failure of machine tools, repair time, and processing time. The rule base of on-line scheduling developed in our study, achieved good performance of scheduling objects.Further research might be developed the method of automated generation of rule bases of off-line and on-line scheduling.

本研究涉及基于知识工程方法的柔性制造系统（FMS）的在线和离线调度。为了解决调度问题的计算复杂性，我们采用了模拟方法。当某些零件类型可以在机器中加工时，将应用优先级规则来选择要加工的一种零件类型。为了获得有效的FMS调度，我们构建了一个规则库以在模拟过程中生成适当的优先级规则。为了评估我们研究中提出的方法，我们构建了三个规则库，其调度目标分别是“最小化生产准备时间”、“最小化延迟时间”和“准时制”。结果，我们确认这三个规则库对每个调度对象都取得了良好的性能。为了应对调度知识库修正的困难，首先，我们开发了一种自调整机制，自动分析先前获得的调度结果来调整规则库中的一些启发式参数。其次，我们将知识库分为3个模块；调度评价、调度策略、调度模块，用模糊规则表示。当调度目标发生变化时，用户可以通过修改调度评估模块中模糊规则的隶属函数来轻松修正知识库，因为调度评估模块的知识可以直观地实现。为了构建一个在线获得高效FMS调度的规则库，我们开发了一个表示不确定事件的FMS仿真系统，例如机床故障、维修时间和加工时间。本研究开发的在线调度规则库，取得了良好的调度对象性能。离线和在线调度规则库的自动生成方法还有待进一步研究。