Leveraging lean manufacturing through computer modeling and simulation for production process improvement
Intensified competition, rapid technological advancements, and shifting customer demands are key catalysts for the global manufacturing landscape. Manufacturing companies that aim to remain competitive have re-evaluated and transformed their business models via sophisticated technologies to enhance...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Book Chapter |
| Language: | English |
| Published: |
IntechOpen
2025
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/44785/ http://umpir.ump.edu.my/id/eprint/44785/1/Published%20Chapter.pdf |
| Summary: | Intensified competition, rapid technological advancements, and shifting customer demands are key catalysts for the global manufacturing landscape. Manufacturing companies that aim to remain competitive have re-evaluated and transformed their business models via sophisticated technologies to enhance production efficiency and customer focus. Nevertheless, implementing such innovations often requires substantial investments in infrastructure, training, and system upgrades, which can be challenging for small and medium enterprises (SMEs). The current work examined an SME specializing in aluminum casting products that struggled to reduce the extended production time for high-volume products to meet production planning targets. Discrete-event simulation (DES) modeling served to replicate the current production processes and analyze the system behavior under various production process improvement strategies. A notable 71% reduction in the total production time was required to achieve the monthly planned quantity based on the DES analysis outcomes. Moreover, system dynamics (SD) modeling was employed to evaluate actionable improvement strategies aimed at expanding production capacity and assessing their potential to receive more orders and meet upcoming demand. The SME could meet a demand of 8000 units per month and increase its production capacity by combining overtime and outsourcing strategies. The findings from both simulation techniques offered real-time insights into the impact of proposed improvement strategies on operational and strategic performance measures to understand process optimization and improve production efficiency and capacity with minimal investment. |
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