Enhancement of lean manufacturing implementation based on decision support system using simulation and intelligent agent

• Auteur principal: Ibrahim, Mohamad Amran
• Format: Thèse
• Langue: anglais; anglais
• Publié: 2017
• Sujets: T Technology (General); TS Manufactures
• Accès en ligne: http://eprints.utem.edu.my/id/eprint/21011/; https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=106161

Lean Manufacturing (LM) is a powerful means employed to improve efficacy in the manufacturing field and get rid of waste by utilising a set of tools. Different approaches have been employed to execute LM. This involves improving the knowledge of the Lean Practitioner (LP) and supporting the offline/online decision making in evaluating the existing production system. Going by the technological growth, some researchers concur that online methods enjoy more popularity in comparison to offline ones as the former can be employed without disorder and can effectually simulate the behaviour of the manufacturing system. This study has been taken up to scrutinise the existing practice of LM execution through an online approach. Many efforts have been made to improve the efficacy of LM execution; however, not all companies have succeeded in this. The author has investigated and recommended iLeTS (Intelligent Lean Tools Simulation) as a solution to bridge the existing gap and simultaneously lower the failure percentage of the LM execution through a new simulation approach. iLeTS had been formulated using the modelling software and improved through the Visual Basic application and multi agent system (MAS). MAS is deemed approp1iate for supporting this production process as agents can dynamically adjust their conduct to fluctuating environments and they can determine solutions speedily through negotiations and mutual cooperation. iLeTS is an alternative approach which can aid the LP to make swift decisions by automating the production process. This combination helps improve the user friendliness and simultaneously lower the usage time. To assess the iLeTS application, two approaches are employed: face validation and usability study. The former is utilised to substantiate the multi agent system flow in iLeTS which impacts the production process; the usability study helps gauge the competence of iLeTS in tackling several randomly occurring events. An extensive array of simulation outcomes, based on actual data, is reported and scrutinised. In concluded, based on the usability study; iLeTS is appropriate for automating the production process and competent enough for being used to make quick decisions.