LAPSE:2023.1896
Published Article
LAPSE:2023.1896
Productivity Improvement Using Simulated Value Stream Mapping: A Case Study of the Truck Manufacturing Industry
February 21, 2023
Abstract
The accumulation of process waste in the production line causes fluctuations, bottlenecks, and increased inventory in workstations disrupting process flow. In this paper, the optimal process flow that will improve productivity using simulated value stream mapping (SVSM) for decision-making to provide consistency, minimise errors and non-value adding times in the implementation phase of VSM in the truck manufacturing industry. The proposed methodology applied a discrete event simulation for production process operations improvement to eliminate non-value adding times and provide good quality products at the lowest cost and highest efficiency. The results are the analysis of the current state of the production system in a South African truck manufacturing industry as a potential solution for the production system’s future state. The identified non-value adding times in the six most critical workstations were eliminated by SVSM resulting in a productivity improvement of 4%, most importantly bringing the productivity to 95% and total cycle time improvement to 451 for small units and 466 for large units. The results proposed combined VSM and simulation techniques based on empirical data from the observation during time measurement. The Yamazumi confirms the issues observed and the NVA recorded by showing how close the process cycle times are to the TAKT time, which enhance the LEAN application by DES to increase productivity and performance improvement to remain competitive in the global economy.
Keywords
cyber-physical systems, lean enterprise, productivity improvement, simulated value stream mapping, spaghetti/yamazumi diagram
Suggested Citation
Poswa F, Adenuga OT, Mpofu K. Productivity Improvement Using Simulated Value Stream Mapping: A Case Study of the Truck Manufacturing Industry. (2023). LAPSE:2023.1896
Author Affiliations
Poswa F: Department of Industrial Engineering, Tshwane University of Technology, Pretoria-Campus, Pretoria 0183, South Africa [ORCID]
Adenuga OT: Department of Industrial Engineering, Tshwane University of Technology, Pretoria-Campus, Pretoria 0183, South Africa [ORCID]
Mpofu K: Department of Industrial Engineering, Tshwane University of Technology, Pretoria-Campus, Pretoria 0183, South Africa [ORCID]
Journal Name
Processes
Volume
10
Issue
9
First Page
1884
Year
2022
Publication Date
2022-09-17
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr10091884, Publication Type: Journal Article
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LAPSE:2023.1896
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https://doi.org/10.3390/pr10091884
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Feb 21, 2023
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