Abstract:
This study aims to improve the efficiency of parts storage positions in a warehouse by using Entry-Item-Quantity (EIQ) analysis, ABC analysis, and a Linear Programming Model. The research focuses on the final assembly shop (Trim and Final Shop, TCF) in an automotive manufacturing company, where delays in parts delivery from the Material Handling (MH) department often cause production stoppages. Data from production plans between August 2022 and February 2023 were used, with specific analysis on parts orders from November 2022, comprising 11,231 orders. The results from EIQ and ABC analyses identified 88 items (23% of total SKUs) as category A with 71% usage frequency, 84 items (22% of total SKUs) as category B with 20% usage, and 205 items (54% of total SKUs) as category C with 9% usage. The implementation of a Linear Programming Model reduced the total walking distance for four employees from 4,276,183 meters per month to 2,845,882 meters per month, a 33% reduction. Additionally, the average cycle time of picking per order decreased from 2.12 minutes to 1.69 minutes, a 20% improvement. In conclusion, this research significantly enhances the efficiency of the MH department by optimizing storage layouts, thereby minimizing walking distances and reducing cycle times, which positively impacts work performance of picking process.