Analisis Perencanaan Produksi dan Age Replacement untuk Meminimalkan Overstock, Stockout, serta Downtime di PT Hanil Jaya Steel. (Analysis of Production Planning and Age Replacement to Minimize Overstock, Stockout, and Downtime at PT Hanil Jaya Steel).

Salvana, Vanka Cathrinne (2026) Analisis Perencanaan Produksi dan Age Replacement untuk Meminimalkan Overstock, Stockout, serta Downtime di PT Hanil Jaya Steel. (Analysis of Production Planning and Age Replacement to Minimize Overstock, Stockout, and Downtime at PT Hanil Jaya Steel). Undergraduate thesis, Universitas 17 Agustus 1945 Surabaya.

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Abstract

PT Hanil Jaya Steel is a manufacturing company engaged in the production of reinforcing steel bars, namely Deformed Bars and Plain Bars. The company faces challenges related to the high frequency of component failures in the Roughing Mill machine, resulting in significant downtime, as well as suboptimal production planning in meeting customer demand. This study aims to improve the maintenance system of the Roughing Mill machine to reduce downtime so that the production process can operate according to plan, and to develop an optimal production plan capable of meeting demand while minimizing the risks of overstock and stockout. The methods employed in this study are the Age Replacement method for maintenance system improvement and the Master Production Schedule (MPS) for production planning. The MPS was developed based on demand forecasting results using the Linear Trend Model for Plain Bars and the Moving Average method for Deformed Bars.The results indicate that the maintenance system improvement generated an optimal inspection schedule for the roll component with an inspection frequency of 2.71 times per month and an inspection interval of 77.74 operating hours. The proposed production plan resulted in Plain Bars production ranging from 294-321 tons with available effective capacity of 111.15-125.19 hours, and Deformed Bars production ranging from 202-216 tons with available effective capacity of 78.9-88.8 hours. These results demonstrate that demand requirements for the period from February to July 2026 can be fulfilled optimally.

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