A Financial Analysis To Identify Constraint Tools And Its Operational Impacts

• Auteur principal: Lim, Poh Siong
• Format: Thèse
• Langue: anglais; anglais
• Publié: 2016
• Sujets: T Technology (General); TS Manufactures
• Accès en ligne: http://eprints.utem.edu.my/id/eprint/20783/; https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=104907

Basic downtime analysis refers to the effort of understanding overall downtime rates which is related to production issues leading to the efficiency improvement of the whole production. However, in a large production system, there are a lot of different types of machines and processes with their individual capacities despite being linear in manner. The specification is referred as the parameters of the downtime cost related factors which have different impact on the downtime analysis. As a result, common study is unable to justify which process or machine requires focus and priority in any downtime improvement program. The justification needs to be supported with a financial analysis which requires the costing method on the downtime issues since the improvement program requires possible financial budget and the potential cost saving activities should be well planned and managed. The main objectives of this project are to link up actual downtime issues to the cost followed by a further analysis on the impact of the downtime cost. The project will be a future tool for the top management to make decision and changes in their operations to move their companies towards better practices and most importantly reducing the operational costs. A period of ten consecutive weeks of downtime monitoring has been conducted in a chosen company by selecting two of its bottleneck processes. During this study, two major downtime cost categories from each process is calculated by using the introduced costing method and an overall potential cost saving improvement program is established. Findings from this study will provide linkages of downtime to financial losses followed by a detailed Pareto breakdown of key drivers. Therefore, this clear determination enables necessary recommendations of downtime improvement effort to be provided within the factory.