Abstract: Currently, inventory and logistics performance play a significant role for the efficiency augmentation and competitiveness of the manufacturing industry. The objective of this research study focuses on inventory management and measurement of logistics performance metrics of on-time in full and vehicle capacity utilization. The problem of maintaining inventory due to the dynamic fluctuating schedule of the customer results in stock-outs due to fluctuating demand and poor performance of on-time in full. Primarily, annual sales data were collected and classified based on ABC-FSN analysis. Then, the outcome of the analysis was used to classify about 123 parts into three classes such as fast, slow, and non-moving categories. Demand forecasting was carried out using various forecasting techniques, followed by ordering policy by economic order quantity. Reorder point model and safety stock were also analyzed. Logistics performance metrics, on-time in full, and vehicle capacity utilization were studied and measured. From the final observed results, it was found that vehicle capacity utilization was poor and all vehicles had an average utilization of 52.61%. Further suggestions were made to demand and adopt the maintaining inventory safety stock and proper packaging of goods to improve the overall performance.

Key words: performance, inventory, ABC-FSN analysis, ordering policy, on-time-in full, logistics, VCU