Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/11994
Title: A Conceptual Model of Inventory Management System using an EOQ Technique – A Case Study in Automotive Service Industry
Authors: Eida Nadirah Roslin
Siti Norhafiza Abdul Razak
Mohd Zaki Bahrom
Muhammad Aizat Abd Rahman
(UniKL MFI)
Keywords: Inventory Management System
Forecasting
Economic Order Quantity
Automotive Service Industry
Issue Date: Dec-2015
Publisher: Universiti Kuala Lumpur Publishing
Citation: Journal of Science & Engineering Technology JSET Vol: 02 No: 02
Abstract: The successful implementation of inventory management system (IMS) in an organization will give the high impact to their business growth and sustainability. Due to the rapid growth in the automotive industry, the need of having this system in this industry is increase especially in the automotive maintenance business. Although there are varieties of choices of the IMS software available in the market, however, financial constraints become the most important barriers to an organization to implement the system. In this paper, the level of implementation of the IMS in Malaysian automotive service industry is identified. A model of IMS by using the Economic Order Quantity is proposed to be implemented in the independence automotive services workshop as an alternative to the high cost investment of the system in the selected industry. Four products that have the highest usage in the workshop are selected. Three different techniques of forecasting are compared in order to predict the demand of the selected products and to develop the economic order quantity. Based on the results, the data that forecasted by Simple Moving Average technique gives the most accurate data and this technique is selected in the development of IMS model.
Description: Full text also available at http://jset.mfi.edu.my/index.php/view-journal-2. JSET is open access journal published by Universiti Kuala Lumpur Publishing
URI: http://ir.unikl.edu.my/jspui/handle/123456789/11994
ISSN: 24621374
Appears in Collections:Journal Articles

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