Generation of a Decision Support System to Enhance the Efficiency of Lean Manufacturing

Effendi Mohamad*, Mohd Amran Ibrahim, Muhamad Arfauz A. Rahman, Mohd Rizal Salleh, Mohd Amri Sulaiman

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)173-181
Number of pages9
JournalIndustrial Engineering and Management Systems
Volume18
Issue number2
DOIs
Publication statusPublished - 01 Jun 2019
Externally publishedYes

Bibliographical note

Funding Information:
The authors are grateful to the Malaysian government and Universiti Teknikal Malaysia Melaka (UTeM) for funding the research via grant FRGS/1/2017/TK03/ FKP-SMC/F00342 and providing materials support as well as other useful information.

Publisher Copyright:
© 2019 KIIE.

Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.

Keywords

  • Decision support system
  • Intelligent agent
  • Lean manufacturing
  • Lean practitioner
  • Modeling
  • Multi-agent system
  • Simulation
  • Waste

ASJC Scopus subject areas

  • Social Sciences(all)
  • Economics, Econometrics and Finance(all)

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