Determination of Demand Forecasting and Inventory Policies for Managing Raw Materials with Engineering to Order Characteristics in the Electricity Maintenance Industry

Abstract

Abstract - Manufacturing industry with Engineering to Order (ETO) characteristics faces challenges in the production process in the form of the availability of raw materials needed. This research was conducted at a manufacturing unit owned by the electricity industry with the main task of producing spare parts for the generation, transmission, and distribution of electricity, this unit carries out the production process with regulations no inventory policy, these regulations make the raw material planning process more difficult and result in material shortages, production delays, and inability to meet delivery time targets, thus threatening customer satisfaction and operational efficiency of the unit. A critical raw material needs planning strategy will be developed using the demand forecasting method. The forecasting methods used include linear regression, double exponential smoothing, Winter's Model and Syntetos-Boylan Approximation. The results of this demand forecasting will be used as a basis for designing a more optimal inventory policy. Three inventory policy scenarios to be evaluated include existing review, continuous review (s,Q), and periodic review and order-up-to-level (R,S) and the method with the smallest stockout risk, the most optimal cost, and the method with the best raw material supply flexibility will be selected.

Keywords - Demand Forecasting, Inventory Policy, Engineering to Order, Reverse Engineering