ANALYSIS OF PT SEMEN INDONESIA'S SUPPLY CHAIN USING PRODUCTION ORDER QUANTITY AND FORECASTING MODELS FOR ORDER OPTIMIZATION.

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Bibliographic Details
Title:	ANALYSIS OF PT SEMEN INDONESIA'S SUPPLY CHAIN USING PRODUCTION ORDER QUANTITY AND FORECASTING MODELS FOR ORDER OPTIMIZATION.
Authors:	MAULANA, Yudi^1,2, MANSHOOR, Bukhari¹ bukhari@uthm.edu.my, ZAINUDDIN, Mairizal², NURMUTIA, Syahreen²
Source:	Academic Journal of Manufacturing Engineering. 2026, Vol. 24 Issue 1, p32-39. 8p.
Subjects:	Production quantity, Forecasting, Cement industries, Industrial efficiency, Supply chain management, Cost functions, Inventory control, Inventories
Geographic Terms:	Indonesia
Abstract:	This study investigates the integration of quantitative inventory management techniques--Mean Absolute Deviation (MAD), Economic Order Quantity (EOQ), and Production Order Quantity (POQ)--within the production operations of PT Semen Merah Putih Indonesia, a major cement manufacturer. Analysis of clinker production data from 2021 to 2023 identified a substantial decline in output in 2023, attributed to an increase in kiln stoppage days (82 days), which adversely affected production continuity and efficiency. The MAD method quantified significant deviations between forecasted and actual demand, indicating inadequate forecasting accuracy. EOQ modelling yielded an optimal order quantity of 740,548.45 tons, effectively minimizing total inventory costs through a balance of ordering and holding costs. The POQ model recommended a 24-day production cycle, providing a more consistent and cost-effective scheduling approach aligned with production capacity and demand variability. The results highlight the operational benefits of integrating statistical forecasting with inventory control models in large-scale manufacturing environments. The combined application of EOQ and POQ supports both cost reduction and production stability, enhancing the responsiveness of the supply chain. Future research should focus on dynamic EOQ adaptations under fluctuating demand, integration with Just-In-Time (JIT) methodologies, and the inclusion of sustainability parameters--such as energy consumption and waste reduction--into inventory optimization frameworks. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	This study investigates the integration of quantitative inventory management techniques--Mean Absolute Deviation (MAD), Economic Order Quantity (EOQ), and Production Order Quantity (POQ)--within the production operations of PT Semen Merah Putih Indonesia, a major cement manufacturer. Analysis of clinker production data from 2021 to 2023 identified a substantial decline in output in 2023, attributed to an increase in kiln stoppage days (82 days), which adversely affected production continuity and efficiency. The MAD method quantified significant deviations between forecasted and actual demand, indicating inadequate forecasting accuracy. EOQ modelling yielded an optimal order quantity of 740,548.45 tons, effectively minimizing total inventory costs through a balance of ordering and holding costs. The POQ model recommended a 24-day production cycle, providing a more consistent and cost-effective scheduling approach aligned with production capacity and demand variability. The results highlight the operational benefits of integrating statistical forecasting with inventory control models in large-scale manufacturing environments. The combined application of EOQ and POQ supports both cost reduction and production stability, enhancing the responsiveness of the supply chain. Future research should focus on dynamic EOQ adaptations under fluctuating demand, integration with Just-In-Time (JIT) methodologies, and the inclusion of sustainability parameters--such as energy consumption and waste reduction--into inventory optimization frameworks. [ABSTRACT FROM AUTHOR]
ISSN:	15837904
DOI:	10.5281/zenodo.19217310