Inventory management for high voltage equipment using statistical distribution techniques

To minimize maintenance cost, the optimum number of items kept in stock needs primary concern, especially high voltage equipment in electrical system. This paper proposes the method to optimize number of spare parts for effective inventory control. By using Pareto analysis, components of power transformer in the stock are classified into ABC classes. Class A means the few most expensive ones that need special care. Class B means ordinary ones that need standard care. Class C means the large number of cheap items that need little care. Since class A items occupy most of the total inventory cost, the optimum number of class A items, which are bushing and arrester, is of prime interest and can be determined from the failure records of power transformer's components by applying statistical distribution techniques. Therefore, the proposed method can effectively reduce the total inventory cost and can also apply with the other high voltage equipment in the system.