...
首页> 外文期刊>Technical Gazette >Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach
【24h】

Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach

机译:使用模拟优化方法确定混合流动店中的最小等待时间

获取原文
   

获取外文期刊封面封底 >>

       

摘要

Planning the order and size of batches is an extremely complex task especially if these tasks are related to production companies in a real environment. This research deals with the problem of determining the entry order and size of product batches in order to optimize inter-operational waits, in the form of waiting in queues for processing and waiting due to the setting-up of the workplace. In real environment, these waits represent a large share of the time spent in the production of a unit of product in a hybrid flow shop. This problem is almost impossible to be solved with analytical models because they may require many simplifying assumptions. Therefore, a simulation-optimization approach is used to solve this problem. Discrete event simulation allows greater flexibility in the representation of the real production system, while the integrated optimization tool, a genetic algorithm, serves to find the optimal solution relatively quickly. To ensure simpler production management, batch size is defined as a fixed value with the exception of a different first or last batch which represents the difference to the required production volume. Therefore, two optimization cases are presented in the paper. Although both cases show improvements, the case when a different batch is the first batch shows better results. In that case, the share of setup time in the total production time of the product unit was reduced from 4% to 3%, and the share of waiting time in the queue for processing was reduced from 76% to 32%.
机译:规划批次的顺序和大小是一个非常复杂的任务,特别是如果这些任务与实际环境中的生产公司有关。该研究涉及确定产品批次的进入顺序和大小的问题,以便优化操作间等待,以等待队列的形式进行处理和等待的工作场所。在实际环境中,这些等待代表了在混合流动店生产产品单位的大量时间。此问题几乎不可能通过分析模型来解决,因为它们可能需要许多简化的假设。因此,使用仿真优化方法来解决这个问题。离散事件仿真在实际生产系统的表示中允许更大的灵活性,而综合优化工具,遗传算法,用于相对快速地找到最佳解决方案。为确保更简单的生产管理,批量大小被定义为固定值,除了不同的第一或最后批处理,表示与所需的生产量的差异。因此,本文提出了两种优化案例。虽然这两种情况都显示出改进,但不同批处理是第一个批量的情况显示更好的结果。在这种情况下,产品单元总生产时间中的设置时间的份额从4%降至3%,并且加工队列中的等待时间的份额从76%降至32%。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号