Design of a multistage serial production system utilizing multitasking workers

Aya Ishigaki, Shuhei Inada, Yasuhiro Hirakawa

Research output: Contribution to journalArticlepeer-review


This paper discusses the design of a multistage serial production system utilizing multitasking workers, who have the capability of processing two or more kinds of operation. In designing a production system, it is important to raise productivity by using workers and production facilities effectively. However, the variation in operation time and unbalanced workloads generally reduce the performance of the system. They increase the work in the process level and decrease the process throughput in the line. To cope with this problem, methods for levelling workloads at each workstation have been studied by many researchers as the line balancing problem. Methods for determining the optimal or near-optimal combination of operations at each workstation have been proposed. Following on from previous researches, this paper discusses the effectiveness of utilizing multitasking workers to raise the performance of the production system. The usefulness of multitasking workers is verified through numerical simulation. Simulation experiments show that the production system including multitasking workers can achieve high-performance under a low WIP level for each worker. Through these results, this paper shows that a high-performance flexible manufacturing system can be constructed by using multitasking workers. Furthermore, the design method of the multistage serial production system, which raises the production rate of each worker, is clarified.

Original languageEnglish
Pages (from-to)376-382
Number of pages7
JournalJournal of Japan Industrial Management Association
Issue number5
Publication statusPublished - 2008 Dec 1


  • CONWEP system
  • KANBAN, Line Balancing Problem
  • Multistage serial production system
  • Multitasking worker

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Applied Mathematics


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