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Developing methods to solve the workforce assignment problem considering worker heterogeneity and learning and forgetting.

机译：考虑到工人的异质性和学习与遗忘，开发解决劳动力分配问题的方法。

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摘要

In this research we studied how the assignment of a fully cross-trained workforce organized on a serial production line affects throughput. We focused on two serial production environments: dynamic worksharing on a production line, similar to bucket brigade systems and a fixed assignment serial-production line where workers work on a specific task during a given time period.;For the dynamic assignment environment we concentrated on the impact of different assignment approaches and policies on the overall system performance. First, we studied two worker two station lines when incomplete dominance is possible as well as the effects of duplicating tooling at these lines. One focus of this research was to optimally solve the dynamic worksharing assignment problem and determine exact percentages of work performed by each worker under the assumptions presented. We developed a mixed integer programming formulation for n workers and m stations that models one-cycle balanced line behavior where workers exchange parts at exactly one position. This formulation is extended to incorporate multiple production lines. We also developed a two-cycle formulation that models a condition when workers exchange parts at exactly two positions in a periodic manner. We also determined throughput levels when workers productivity changes over time due to workers' learning and forgetting characteristics.;A fixed worker assignment system considers a serial production setting in which work is passed from station to station with intermediate buffers between stations. We considered two models. The first model assumed that workers perform tasks based on their steady-state productivity rate. The second model assumed that workers' productivity rates vary based on their learning and forgetting characteristics. Heuristic methods were developed and implemented to solve these two models and to determine optimal throughput levels and optimal worker assignments. We were also able to demonstrate the importance of introducing learning and forgetting into these types of worker assignment problems. A final focus of this research was the comparison of the dynamic worksharing and fixed worker assignment environments.
机译：在这项研究中，我们研究了在串行生产线上组织的经过全面交叉培训的劳动力如何影响生产率。我们专注于两个串行生产环境：类似于桶式大队系统的生产线上的动态工作共享，以及在给定时间段内工人从事特定任务的固定分配的串行生产线;对于动态分配环境，我们专注于不同分配方法和策略对整体系统性能的影响。首先，我们研究了两个工人两条工位的生产线，这些生产线可能存在不完全的支配地位以及在这些生产线上重复工装的影响。这项研究的重点是最优地解决动态工作共享分配问题，并根据提出的假设确定每个工人完成的工作的准确百分比。我们为n个工人和m个工位开发了一个混合整数编程公式，该模型对一个周期的平衡线行为进行建模，其中工人在一个位置上交换零件。该配方扩展为包含多条生产线。我们还开发了两个周期的公式，该模型为工人周期性地在两个位置精确地更换零件时的情况建模。我们还确定了由于工人的学习和遗忘特性而导致工人生产率随时间变化时的生产率水平。固定的工人分配系统考虑了串行生产设置，其中工作从一个工位传递到另一个工位，并在工位之间设置中间缓冲区。我们考虑了两种模型。第一个模型假设工人根据其稳态生产率执行任务。第二种模型假设工人的生产率根据他们的学习和遗忘特征而变化。开发并实施了启发式方法来解决这两个模型，并确定最佳吞吐量水平和最佳工人分配。我们还能够证明在这些类型的工人分配问题中引入学习和遗忘的重要性。这项研究的最后重点是动态工作共享和固定工人分配环境的比较。

著录项

  • 作者

    Vidic, Natasa S.;

  • 作者单位

    University of Pittsburgh.;

  • 授予单位 University of Pittsburgh.;
  • 学科 Engineering Industrial.;Operations Research.
  • 学位 Ph.D.
  • 年度 2008
  • 页码 176 p.
  • 总页数 176
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 一般工业技术;运筹学;
  • 关键词

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