Generation Of A Decision Support System To Enhance The Efficiency Of Lean Manufacturing

Mohamad, Effendi and A Rahman, Muhamad Arfauz and Salleh, Mohd Rizal and Ibrahim, Mohd Amran and Sulaiman, Mohd Amri (2019) Generation Of A Decision Support System To Enhance The Efficiency Of Lean Manufacturing. Industrial Engineering & Management Systems, 18 (2). pp. 173-181. ISSN 1598-7248

Text GENERATION OF A DECISION SUPPORT SYSTEM TO ENHANCE THE EFFICIENCY OF LEAN MANUFACTURING.PDF Download (1MB)

Abstract

Lean manufacturing (LM) is an established process that employs an array of instruments to eradicate waste. A variety of methods have been applied (some more successfully than others) to enhance the effectiveness of this process. This study delves into the introduction of the Intelligent Lean Tools Simulation (iLeTS) to overcome the deficiencies in the LM process and reduce the failure ratio. Fabricated with the use of modelling software, the performance of iLeTS was enhanced by way of an amalgamation involving the visual basic application (VBA) and the multi agent system (MAS). This merging served to enhance the user friendliness of iLeTS, which in turn reduced the required period of usage. Face validity and a usability study were harnessed to evaluate the performance of iLeTS. While face validity was used to authenticate the multi-agent system flow in iLeTS; the usability study was engaged to determine the proficiency of iLeTS when it comes to managing a number of arbitrarily occurring incidents. Subsequent to a thorough examination of a wide range of simulation results (deriving from authentic data), we arrived at the conclusion that (a) the iLeTS is suitable for the automation of the manufacturing process, and (b) the iLeTS can be relied upon for making prompt and appropriate choices.

Item Type:	Article
Uncontrolled Keywords:	Waste, Lean Manufacturing, Modeling, Simulation, Lean Practitioner, Intelligent Agent, Multi-Agent System, Decision Support System, Decision Support System
Divisions:	Faculty of Manufacturing Engineering
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	09 Dec 2020 12:05
Last Modified:	09 Dec 2020 12:06
URI:	http://eprints.utem.edu.my/id/eprint/24639
Statistic Details:	View Download Statistic

Actions (login required)

View Item