A study of workforce assignment problem in lean factory on machine tool industry

Jrjung Lyu, Ching Hsiang Tung, Chia Wen Chen

研究成果: Conference article同行評審

摘要

For a company in the traditional manufacturing environment, such as a machine tool industry, how to adjust the workforce assignment during adopting lean production is a key issue. Consiering the complexity in manufacutirng various machine types, each requires a combination of the expertise in multiple techniques for one specific technician, arrange appropriate workforce is therefore not an easy job for the shop floor manager. This work proposes a systematic method, based on the mathematical programming, to resolve the issue of workforce assignment when receiving small-volume, large-variety orders in the machine tool industry. A case company is used to demonstrate the feasibility and effectiveness of this method. The proposed method starts with the drawing of Value Stream Mapping (VSM) and applies the seven principles of lean to design the to-be production system. An interger programming (IP) model is formed to find the optimal workforce assignment in re-designing the manufacturing process when various orders are received for the future VSM. Simulation results illustrate the potential performance of the model. A typical company which was quite representive in the machine tool industry was selected and its shop floor information was collected. For the case company, it was found out that the makespan could be reduced from 28.03 days to 12.5 days without additional manpower for a series of five orders with four machine types. The emprical results clearly demonstate that the proposed method is feasible and could be extended to other companies.

原文English
頁(從 - 到)1950-1955
頁數6
期刊Proceedings of the International Conference on Industrial Engineering and Operations Management
2019
發行號MAR
出版狀態Published - 2019 一月 1
事件9th International Conference on Industrial Engineering and Operations Management, IEOM 2019 - Bangkok, Thailand
持續時間: 2019 三月 52019 三月 7

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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