• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>International Journal of Production Research >Re-entrant lines with unreliable asynchronous machines and finite buffers: performance approximation and bottleneck identification
【24h】

Re-entrant lines with unreliable asynchronous machines and finite buffers: performance approximation and bottleneck identification

机译：具有不可靠的异步机器和有限缓冲区的可重入行：性能近似和瓶颈识别

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this paper we study a re-entrant line with unreliable asynchronous exponential machines and finite buffers. First, an approximation method is presented to estimate the throughput of the re-entrant line. The idea of the approximation is to transform an M-machine re-entrant line into a 2M-machine serial line. Then, a system approach to identify a c-bottleneck based on blockage and starvation information is proposed, where a c-bottleneck machine is the machine whose improvement in machine capacity leads to the largest improvement in system throughput compared with improving all other machines. It is shown that the approximation method results in acceptable accuracy, and the bottleneck identification method can correctly detect the bottlenecks in most cases.
机译：在本文中，我们研究了具有不可靠的异步指数机和有限缓冲区的重入行。首先，提出一种近似方法来估计折返线的吞吐量。近似的想法是将M机折返线转换为2M机串行线。然后，提出了一种基于阻塞和饥饿信息来识别c瓶颈的系统方法，其中c瓶颈机器是一种机器能力的提高，与改善所有其他机器相比，其机器吞吐量的提高最大。结果表明，该近似方法可以达到可接受的精度，并且瓶颈识别方法可以在大多数情况下正确检测瓶颈。

著录项

  • 来源
    《International Journal of Production Research》 |2012年第4期|p.977-990|共14页
  • 作者

    Yang Liu; Jingshan Li; Shu-Yin Chiang;

  • 作者单位

    Department of Industrial Engineering, University of Louisville, Louisville, KY 40292, USA;

    Department of Industrial and Systems Engineering, University of Wisconsin - Madison, Madison, WI53706, USA;

    Department of Information and Telecommunication Engineering, Ming Chuan University, Taoyuan 333, Taiwan, ROC;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    flow lines; continuous improvement; stochastic models;

    机译：流线;连续的提高;随机模型;

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