<![CDATA[In the increasingly competitive automotive industry, effective raw material control is essential to achieve cost efficiency, maintain production continuity, and ensure accurate distribution. PT XYZ, an automotive manufacturing company located in Karawang, faces several challenges, including high demand fluctuations, dependence on imported raw materials, and the absence of safety stock calculations, which increase the risk of inventory shortages. This study aims to determine the optimal raw material planning method by integrating demand forecasting and Material Requirement Planning (MRP) using the Lot for Lot (LFL) technique in the production of the KWU-type Timing Chain Cover (TCC). This research employs a quantitative case study approach, with data collected through observation, interviews, documentation, and literature review. Demand forecasting is conducted using Double Exponential Smoothing, Moving Average, and Linear Regression methods. The most accurate forecasting method is then used as an input for preparing the Master Production Schedule (MPS) and MRP. The results indicate that the Linear Regression method provides the highest forecasting accuracy, as indicated by the lowest Mean Squared Error (MSE) value of 2,075,786,061. Furthermore, the implementation of MRP using the Lot for Lot technique combined with safety stock calculations proves effective in reducing the risk of stockouts. This improvement is reflected in the stabilization of inventory levels, such as the water pump bearing component, which previously experienced zero stock conditions and is now maintained at a safety stock level of 37,770 units. In conclusion, the integration of Linear Regression forecasting and Lot for Lot-based MRP enhances planning accuracy, ensures raw material availability, and supports long-term operational efficiency at PT XYZ.]]>
Copyrights © 2026
