Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 1950-1955 |
| Number of pages | 6 |
| Journal | Proceedings of the International Conference on Industrial Engineering and Operations Management |
| Volume | 2019 |
| Issue number | MAR |
| Publication status | Published - 2019 Jan 1 |
| Event | 9th International Conference on Industrial Engineering and Operations Management, IEOM 2019 - Bangkok, Thailand Duration: 2019 Mar 5 → 2019 Mar 7 |
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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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A study of workforce assignment problem in lean factory on machine tool industry. / Lyu, Jrjung; Tung, Ching Hsiang; Chen, Chia Wen.
In: Proceedings of the International Conference on Industrial Engineering and Operations Management, Vol. 2019, No. MAR, 01.01.2019, p. 1950-1955.Research output: Contribution to journal › Conference article
TY - JOUR
T1 - A study of workforce assignment problem in lean factory on machine tool industry
AU - Lyu, Jrjung
AU - Tung, Ching Hsiang
AU - Chen, Chia Wen
PY - 2019/1/1
Y1 - 2019/1/1
N2 - 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.
AB - 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.
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M3 - Conference article
AN - SCOPUS:85067250673
VL - 2019
SP - 1950
EP - 1955
JO - Proceedings of the International Conference on Industrial Engineering and Operations Management
JF - Proceedings of the International Conference on Industrial Engineering and Operations Management
SN - 2169-8767
IS - MAR
ER -