基于数据SCADA的压铸工艺冷却系统预测性维护价值分析

Engelbert Harsandi Erik Suryadarma, T. J. Ai, P. Anggoro
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引用次数: 0

摘要

冷却系统在压铸过程中是至关重要的。有问题的冷却系统将使凝固过程失控。因此,需要维护(特别是预测性维护)以保持冷却系统处于良好状态。然而,预测性维护的应用需要复杂的资源。本研究将通过减少传感器和计算的数量,简化铸造过程中冷却系统的预测性维护程序。本研究使用SCADA技术和机器学习来不断获得准确的预测。根据测试结果,提出的预测性维护系统的复杂程度比进行价值分析之前更直接,但具有与应用价值分析之前相当的精度水平。
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Value Analysis of Predictive Maintenance in Cooling System of a Die Casting Process by Data SCADA
The cooling system is vital for the die casting process. The problematic cooling system will make the process of solidification uncontrolled. So that maintenance (especially predictive maintenance) is needed to keep the cooling system in good condition. However, the application of predictive maintenance requires complex resources. This research will simplify the predictive maintenance procedure on the cooling system in the casting process by reducing the number of sensors and calculations. This research uses SCADA technology and Machine Learning to keep getting accurate predictions. Based on the test results, the level of complexity of the proposed predictive maintenance system is more straightforward than before the value analysis was carried out, but has an accuracy level equivalent to before the value analysis applied.
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