Abstract:
One of the most important factors in business operations is inventory, especially Raw Material, as it protects against fluctuation in supply and realizes economy of scale for a company. Nevertheless, inventory is a costly asset. Reducing inventory levels allows a company to increase liquidity and to be more responsive to customer’s demands. This case study proposes the use of ABC Classification to classify high-impact raw-material in an electronic industry company and the use of lot-sizing to improve the procurement process. The inventory performance measure of the case study company is in Inventory Turnover Days where a target of no more than 10 days is set. ABC Classification and other prerequisites results in 12 items from 3 different refrigerator models on which further study is conducted. Comparing results from lot sizing heuristics showed that the Part-Period balancing heuristic performs best, resulting in a total cost difference of 12.09% from the optimum values obtained from Wagner-Whitin algorithm. The Part-Period Balancing heuristic also came as close to within 3% of the optimum values for two parts. Implementing the Part-Period Balancing heuristic to just the 12 selected items, out of 1,008 possible items resulted in a considerable Inventory Turnover Days reduction of 0.5 days. As Lot Sizing heuristics and algorithms leave little or no inventory at the end of each period, Safety Stock levels for the aforementioned items are established to guard against stock-outs.
