A simulation-based approach to decision support for lean practitioners

• Main Authors: Mohamad, Effendi, Ito, Teruaki, Yuniawan, Dani
• Format: Conference or Workshop Item
• Language: English; English
• Published: 2013
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.utem.edu.my/id/eprint/11054/1/Mohamad%2C_E.pdf; http://eprints.utem.edu.my/id/eprint/11054/2/Mohamad%2C_E.pdf; http://eprints.utem.edu.my/id/eprint/11054/; http://www.ebooks.iospress.nl/publication/34815

In today’s global competition, having a lean production system is a must for companies to remain competitive. By identifying and eliminating waste throughout a product’s entire value stream by means of a set of LM tools, companies are able to produce and assemble any product range in any order or quantity. In order to do these, personnel needs to have the expertise in deciding which LM tool to implement at the right time and on the right place. However, this expertise is not always available. Therefore, this paper proposes a simulation-based decision support (SDS) tool to assist the decision making in LM tool implementation. The SDS tool provides five functions through an interactive use of process simulation. The functions are layout, zoom-in/zoom-out, task status, Key Performance Indicators (KPI) status and R.A.G (Red, Amber and Green) status (quantifying waste). These functions are incorporated into a process model of coolant hose manufacturing (CHM) factory which was developed in this study. Layout function provides a bird’s eye view of the whole process model and shows how the manufacturing process runs with the flow of materials and products. Zoom-in/zoom-out function provides a detail view of manufacturing processes of the factory. For KPI and RAG status functions, examples of LM tool implementations are used to show how different parameters affect the outcome of manufacturing process. Bar charts of KPIs are also available during simulation. Feasibility study showed how SDS tool enhance the visual perception and analysis capabilities of lean practitioners through availability of specific functions in the simulation model. Hence, decisions in LM implementation could be made correctly and with increased confidence by lean practitioners.