A proposal of Muda Indicator agent to estimate Lean Manufacturing verification

Lean Manufacturing (LM) is the philosophy to improve productivity of manufacturing system by eliminating wastes. LM tools have been implemented as software tools in order to implement this philosophy. However, implementing LM in factories does not always succeed because of several reasons; insuffic...

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Main Authors: Mohamad, Effendi, Ito, Teruaki, Yuniawan, Dani, Ibrahim, M. A., Saptari, Adi, Kasim, Mohd Shahir, Raja Abdullah, Raja Izamshah, Shibghatullah, Abdul Samad, Md Ali, Mohd Amran
Format: Article
Language:English
Published: Penerbit Universiti Teknikal Malaysia Melaka 2014
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Online Access:http://eprints.utem.edu.my/id/eprint/19385/2/paperEffendi.pdf
http://eprints.utem.edu.my/id/eprint/19385/
https://jamt.utem.edu.my/jamt/article/view/116/82
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Summary:Lean Manufacturing (LM) is the philosophy to improve productivity of manufacturing system by eliminating wastes. LM tools have been implemented as software tools in order to implement this philosophy. However, implementing LM in factories does not always succeed because of several reasons; insufficient expertise and knowledge on LM practitioners, dynamic feature of complicated manufacturing processes, difficulty in quantifying the benefits of LM implementation, and etc. Simulation-based approaches have been proposed to support LM implementation, and their effectiveness has been reported in several papers. However, they are not suitable for LM practitioners who are not familiar with simulation software. Therefore, some appropriate niche techniques to bridge the gap between LM practitioners and simulation-based approaches are expected to achieve successful LM implementation. This research proposes an agent-based approach to LM implementation using Muda Indicator (MI) agent to narrow the gap. This paper presents the overview of MI agent, defines quartile calculation to determine Muda level, explains MI indication by MI agent, and shows the feasibility of MI agent using a manufacturing process model. The feasibility study showed how MI agent presents transition of quantifying wastes during simulation in a dynamic manner.