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A rule-based harmony search simulation-optimization approach for intelligent control of a robotic assembly cell

机译:基于规则的和声搜索仿真优化方法,用于机器人组装单元的智能控制

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This paper proposes to use a rule-based simulation-optimization approach for the dynamic scheduling and control of a robotic assembly cell. The approach is useful in both hierarchic control structure and hybrid control structure where the decision is distributed among the robotic cell entities that are products and resources (robots). Particularly, the approach make use of scheduling/dispatching rules and a harmony search optimization process coupled to a discreet event model of the studied manufacturing system, modeled in the FlexSim simulation software. Target system consists of the Valenciennes's AIP PRIMECA robotic assembly cell (France) that represents a hard declination of the flexible job shop scheduling problem. Obtained results validate the simulation model and the methodology but highlights a lack of efficiency of the adopted optimization process witch have to be addressed in future works.
机译:本文建议使用基于规则的仿真优化方法来进行机器人组装单元的动态调度和控制。该方法在层次控制结构和混合控制结构中是有用的,其中决定分布在作为产品和资源(机器人)的机器人单元实体中。特别地,该方法利用调度/调度规则和和声搜索优化过程,耦合到研究的制造系统的谨慎事件模型,在FlexSIM仿真软件中建模。目标系统由Valenciennes的AIP Primeca机器人组装单元(法国)组成,该组装单元(法国)表示灵活的作业商店调度问题的艰难偏差。获得的结果验证了仿真模型和方法,但突出了未来工作中所采用优化过程缺乏效率的效率。

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