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Journal International Conference on Engineering, Applied Sciences and TechnologyInternational Conference on Engineering, Applied Sciences and Technology Abstract

The andesite mining industry in Cilegon needs help in meeting the increasing market demand, especially in the Split 1-2 product, which has an annual production capacity of 349,418 tons compared to the demand of 454,238 tons. This research aims to increase production capacity through the application of the cut-and-try method. This method identifies the optimal solution through repeated experiments on various operational strategies. The analysis uses the Simple Moving Average, Exponential Moving Average, and Mean Absolute Percentage Error (MAPE) approaches for demand forecasting, as well as aggregate planning evaluation, to align capacity with market demand. The results show that the cut-and-try method provides flexibility in adjusting production strategies in real-time, allowing for increased productivity, reduced downtime, and more efficient inventory management. Two production planning scenarios were tested, namely Production Plan 1, with variations in inventory and stock depletion, and Production Plan 2, which uses constant labour and overtime. Of these two scenarios, Production Plan 2 proved to be more cost-effective, with a total expenditure of IDR 1,413,258,340 compared to IDR 2,357,596,694 in Production Plan 1.

Conclusion

The cut-and-try method offers a flexible approach to identifying effective production strategies in andesite mining through experimentation and real-time adjustments.This method allows for optimization of mining operations by testing various factors like labor, equipment, and inventory management, ultimately increasing efficiency and productivity.However, balancing flexibility with cost control is crucial, and a systematic approach using collected data can improve decision-making for sustainable growth.

Future Research

Penelitian lebih lanjut dapat dilakukan untuk menguji efektivitas metode cut-and-try dalam berbagai kondisi geologis dan operasional tambang andesit, dengan mempertimbangkan faktor-faktor seperti karakteristik batuan, kedalaman tambang, dan kondisi cuaca. Selain itu, studi komparatif dapat dilakukan untuk membandingkan metode cut-and-try dengan metode optimasi produksi lainnya, seperti simulasi Monte Carlo atau algoritma genetika, untuk mengidentifikasi pendekatan yang paling efisien dan efektif dalam meningkatkan kapasitas produksi. Terakhir, penelitian dapat difokuskan pada pengembangan model prediktif yang lebih akurat untuk memperkirakan permintaan pasar dan mengoptimalkan perencanaan produksi, dengan memanfaatkan teknik machine learning dan analisis data besar untuk mengidentifikasi pola dan tren yang relevan.

References

1. FORECASTING THE NUMBER OF AIRPLANE PASSENGERS USING HOLT WINTER'S EXPONENTIAL SMOOTHING METHOD AND... ojs3.unpatti.ac.id/index.php/barekeng/article/view/10503FORECASTING THE NUMBER OF AIRPLANE PASSENGERS USING HOLT WINTERS EXPONENTIAL SMOOTHING METHOD AND ojs3 unpatti ac index php barekeng article view 10503

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