Abstract
Company Z had an inventory of fast moving spare parts where the demand pattern for these spare parts fluctuated every month and there were several months in which the demand was zero. In addition, company Z did not have a safety stock for these spare parts, so the risk of shortage for these spare parts was quite high. This study aimed to reduce fast moving spare part inventory costs and prevent the risk of shortage by determining the optimal order quantity and re-ordering time. The inventory control model used to determine the optimal order quantity was the Probabilistic Economic Order Quantity (Probabilistic EOQ). This model is appropriate to use in conditions of unstable demand and it requires the calculation of safety stock to prevent shortage. Research data in the form of data on demand, lead time, purchasing cost, ordering cost, carrying cost, and shortage cost were collected through company documents. The data that had been collected was then processed using an excel spreadsheet. Demand forecasting for the next 12 months was carried out using the Croston method. Forecasting results were used as input in calculating the optimal order quantity on Probabilistic EOQ. Furthermore, data processing was run by calculating the safety stock and reorder point. The total inventory cost with Probabilistic EOQ was calculated and compared with the company’s total inventory cost to determine whether Probabilistic EOQ is able to create inventory cost reduction. The results showed that Probabilistic EOQ enabled the company to reduce its inventory cost up to 57.85%.
Highlights
Energy holds a key role for companies in running their business because energy is the driving force of operations
Probabilistic Economic Order Quantity (EOQ) is one of the inventory controls models that is appropriate for the companies whose demand and or lead time are not certainly determined
The study provides the evidence that Probabilistic EOQ allows the company to reduce its inventory cost by 57.85%
Summary
Energy holds a key role for companies in running their business because energy is the driving force of operations. Energy-producing companies are demanded to be an energy provider that operates efficiently and effectively so that they can be used as an underpinning in ensuring fast and precise service for energy needs. Energy-producing companies are responsible for ensuring the availability of energy by minimizing troubles and instabilities during the energy production process. The engine is one of the important aspects for energy-producing companies so that the reliability and availability of machines must be maintained well and the machine will be in ideal conditions (Budiningsih and Jauhari, 2017). Maintenance of machines needs to be carried out by energy-producing companies for predictive maintenance as well as corrective maintenance. The availability of spare parts plays an important role for energy-producing companies in carrying out machine maintenance and has a substantial impact on the inventory costs borne by the company (Syntetos and Boylan, 2005). A large number of spare part inventories causes high storage costs, while a small number of spare part inventories causes a shortage that has implications for interference of energy production (Porras and Dekker, 2008)
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