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All Journal International Journal of Environmental, Sustainability, and Social Science
Iwan Vanany
Sepuluh Nopember Institute of Technology, Surabaya, Indonesia
Economics, Econometrics & Finance Environmental Science Social Sciences

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Determining Demand Forecasting and Inventory Policy For Management of Raw Materials With Engineering To Order Characteristics in The Electricity Maintenance Industry Rosa Shinta Rosyadi; Iwan Vanany
International Journal of Environmental, Sustainability, and Social Science Vol. 7 No. 2 (2026): International Journal of Environmental, Sustainability, and Social Science (Mar
Publisher : PT Keberlanjutan Strategis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38142/ijesss.v7i2.1463

Abstract

This study examines the optimization of critical raw material inventory control policies in an Engineering-to-Order (ETO) manufacturing unit operating under a “no inventory” policy. The main challenges in the ETO system are demand uncertainty and unique product specifications, which are exacerbated by the prohibition on stocking. Through ABC analysis and CV-ADI classification, three critical materials (Materials 1, 4, and 7) are identified with lumpy and erratic demand patterns. The Syntetos-Boylan Approximation (SBA) forecasting method proves to be the most accurate for these demand patterns. Furthermore, three inventory policy scenarios (existing, continuous review (s, Q), and periodic review (R, S)) are evaluated based on total cost and service level. The results show that the existing policy has a low service level. For Materials 1 and 7, the continuous review (s, Q) system offers the most optimal cost with high service levels (77.14% and 95.30%). Meanwhile, for Material 4, the periodic review (R, S) system proves to be the most efficient with a service level of 95%. This study provides data-driven inventory policy recommendations that can improve operational efficiency, minimize stockout risks, and support production sustainability in an ETO environment with inventory constraints.
Co-Authors Rosa Shinta Rosyadi