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Multi-objective optimisation of dynamic scheduling in robotic flexible assembly cells via fuzzy-based Taguchi approach

机译:基于模糊Taguchi方法的机器人柔性装配单元动态调度多目标优化

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摘要

This paper presents Taguchi method coupled with fuzzy logic for dealing with multi-objective optimisation problems for dynamic scheduling in robotic flexible assembly cells (RFACs). This is the first study to address these particular problems. In this study, Taguchi optimisation method has been applied to reduce the number of experiments required for scheduling RFACs. The experiments are implemented with four different scheduling factors, namely sequencing rule, dispatching rule, cell utilisation and due date tightness. These factors are difficult to optimise considering the objectives of multiple functions instead of a single objective. Therefore, a multiple performance characteristics index (MPCI) based fuzzy logic approach has been developed to derive the optimal solution. The predicted results of MPCIs have been verified via a confirmation test. Results of the confirmation test show significant improvement in MPCI using the optimal levels of the scheduling factors.
机译:本文提出了Taguchi方法与模糊逻辑相结合的方法来解决机器人柔性装配单元(RFAC)中动态调度的多目标优化问题。这是解决这些特殊问题的第一项研究。在这项研究中,田口优化方法已被用于减少调度RFAC所需的实验数量。实验通过四个不同的调度因素来实现,即排序规则,调度规则,单元利用率和到期日紧度。考虑到多个功能的目标而不是单个目标,很难优化这些因素。因此,已经开发了一种基于多性能特征指标(MPCI)的模糊逻辑方法来得出最佳解决方案。 MPCI的预测结果已通过确认测试得到验证。确认测试的结果表明,使用最佳水平的调度因子可以显着改善MPCI。

著录项

  • 来源
    《Computers & Industrial Engineering》 |2016年第9期|250-259|共10页
  • 作者单位

    School of Industrial Engineering, University of Technology, Baghdad, Iraq,School of Engineering, University of South Australia, Adelaide 5095, South Australia, Australia;

    School of Engineering, University of South Australia, Adelaide 5095, South Australia, Australia;

    School of Engineering, University of South Australia, Adelaide 5095, South Australia, Australia;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Taguchi's method; Fuzzy logic; Scheduling; Robotics; Assembly cells;

    机译:田口的方法;模糊逻辑;排程;机器人技术组装单元;

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