Enhancing Demand Forecasting Accuracy for Electronic Components: A Case Study of PT Omron Indonesia

Abstract

In the dynamic realm of manufacturing, precise demand forecasting is crucial for optimizing supply chains and production processes. This study addresses PT Omron Indonesia's challenge of inaccurate demand forecasts leading to production disruptions. Utilizing the Plan-Do-Study-Act (PDSA) cycle, alongside Multiplicative Decomposition methods, the research aims to improve forecasting accuracy. Results indicate that the Multiplicative Decomposition - Centered Moving Average method yields a lower Mean Absolute Percentage Error (MAPE), though refinement is needed to meet set standards. The estimated demand for the next period is 1308 units, with a MAPE of 140%. The study concludes that iterative refinement of the selected method is essential for achieving higher forecasting accuracy. This research contributes to enhancing production efficiency and mitigating the impact of part shortages in the electronics industry.