Spare Parts Inventory Management :Al Sarrawi Automobile Spare Parts Industry
Aya Abu Zant
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Effective inventory management of spare parts is essential to many companies, from capital-intensive manufacturers to service organizations, such as car manufacturers, chemical plants, telecom companies and airlines. In this Project we present a case study in inventory management of spare parts in a local car company in Palestine called Al Sarrawi Company for Mercedes Spare parts. The companys core business is selling spare parts for Mercedes Cars to consumers. The company does not give adequate importance to inventory management due to various reasons including the disorganization of spare parts and the non availability of any inventory modeling system or ordering policy combined with inexperienced manpower. As a result, there is an inefficient deployment of inventory. This study focuses on the inventory management of spare parts for a specific model of Mercedes Cars called 416. So this project aims to improve the efficiency of Al Sarrawi Company, through improving and implementing new inventory management systems. We start our study by classifying the spare part items by using ABC analysis, then we focus on the analysis of the demand data provided by the company, then building a model for each type of the spare parts, then evaluate the previous conditions and compare them empirically with the new results based on our inventory models. One major difficulty of the study was the limited demand history available, and no real inventory model systems were applied. By describing the case, we make general observations about the practical aspects of inventory control. Moreover, our aim is to compare various policies with real demand data from the case to see which one is best under what circumstances. Common methods presented in the literature rather use given statistical demand distributions to assess the performance of inventory models. Consequently, with our methodology we can better identify the real limitations of industrial data sets. The stages of our project are: stage 1 is ABC analysis and the classification of the items: The classification in our case study as follow: Description Total number of parts Percentage of items in the inventory Cumulative usage value Percentage of annual sales value Cumulative of annual sales value A 17 20% 20% 70% 70% B 21 26% 46% 20% 90% C 45 54% 100% 10% 100% Total 100% 100% We divided the spare parts into three classes A, B, and C. Class A should contain 17 parts of high cost, class B parts of medium cost and C parts of low cost. Closely monitor those items with a high price value. Class A: represents 70% of total inventory cost Class B: represents 20% of total inventory cost Class C: represents 10% of total inventory cost Stage 2 is Demand Forecasting: We covers demand forecasting for 416 Mercedes spare parts in Al - Sarrawi Company, and we use Time Series Models which is based only on past values and assumes that factors that influence the past, then we measure the forecast errors shown in the tables in Appendixes on the report. Stage 3 is inventory cost: For this case study, the non capital costs: - Logistics costs - Tax and utility human resource for the warehouse. - Administrative and human resource for the warehouse The costs of logistics were obtained by the cost of every shipments contains 6-10 pallets every order (200 N.I.S per pallet), so we conclude in average the total cost of logistics is 1600 N.I.S every order. Taxes and rental of human resource for warehouse are equal 18,000-19,000 N.I.S Administrative and human resources were 15,000-20,000 N.I.S in total. The overall holding cost percentage for non capital cost is presented in the tables. Stage 3 is Inventory Management Model: Finally we develop EOQ model which seems that the implementing of the model on items class A, B and C there is cost saving varies between 3-15 %.