Fakhriyah, Siti Diaz Rifa
School of Business and Management, Institut Teknologi Bandung

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Improving Inventory Management by Using Material Requirement Planning (MRP): Case in Soigne Adornment Company Fakhriyah, Siti Diaz Rifa; Farmaciawaty, Desy Anisya
Journal of Innovation, Business and Entrepreneurship Vol 4, No 2 (2019)
Publisher : Journal of Innovation, Business and Entrepreneurship

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Abstract

Soigne Adornment is a fashion company that focuses on accessories. High market demand in the fashion industry is very dependent on the supply and productivity of companies in making products. Therefore, the operating system must be prepared carefully. As one of the companies in the fashion industry, Soigne Adornment is needed to maintain the operating system. Soigne Adornment itself has experienced several operational problems in production because it does not have the right schedule and estimated demand, resulting in losses. Losses experienced due to several aspects, namely from the excess of raw materials and delays in ordering. These problems affect the company's performance and have an impact on sales. This study aims to make an estimate of demand and find the most efficient method to minimize production costs. Therefore, using Material Requirement Planning (MRP) can overcome the problems that have occurred. In this study, what must be done first is to determine the number of forecasting requests by interviewing through the Jury of Executive Opinion method by interviewing the owner of Soigne Adornment and interviewing the owner of the Velour Jewels Company. After the estimated data is collected, researchers conduct production scheduling using the Master Production Schedule (MPS), Bill of Materials (BOM), and Lead Time. After the scheduling process is completed, an analysis is conducted to find the lowest production costs using the Lot-Sizing technique through three methods, namely Lot-For-Lot (L4L), Economic Order Quantity (EOQ), and Order Quantity Period (POQ). Based on the results of the analysis, it shows that Economic Order Quantity (EOQ) is the most efficient method for minimizing production costs. Keywords: Soigne Adornment, Fashion Company, Material Requirements Planning, Demand Forecasting, Production SchedulingSoigne Adornment is a fashion company that focuses on accessories. High market demand in the fashion industry is very dependent on the supply and productivity of companies in making products. Therefore, the operating system must be prepared carefully. As one of the companies in the fashion industry, Soigne Adornment is needed to maintain the operating system. Soigne Adornment itself has experienced several operational problems in production because it does not have the right schedule and estimated demand, resulting in losses. Losses experienced due to several aspects, namely from the excess of raw materials and delays in ordering. These problems affect the company's performance and have an impact on sales. This study aims to make an estimate of demand and find the most efficient method to minimize production costs. Therefore, using Material Requirement Planning (MRP) can overcome the problems that have occurred. In this study, what must be done first is to determine the number of forecasting requests by interviewing through the Jury of Executive Opinion method by interviewing the owner of Soigne Adornment and interviewing the owner of the Velour Jewels Company. After the estimated data is collected, researchers conduct production scheduling using the Master Production Schedule (MPS), Bill of Materials (BOM), and Lead Time. After the scheduling process is completed, an analysis is conducted to find the lowest production costs using the Lot-Sizing technique through three methods, namely Lot-For-Lot (L4L), Economic Order Quantity (EOQ), and Order Quantity Period (POQ). Based on the results of the analysis, it shows that Economic Order Quantity (EOQ) is the most efficient method for minimizing production costs. Keywords: Soigne Adornment, Fashion Company, Material Requirements Planning, Demand Forecasting, Production Scheduling