期刊论文详细信息
Estonian Academy of Sciences. Proceedings | |
Production monitoring system design and implementation | |
Tanel Eiskop1  | |
关键词: production monitoring system; tool life modelling; ANN.; | |
DOI : 10.3176/proc.2017.4.02 | |
学科分类:化学(综合) | |
来源: Teaduste Akadeemia Kirjastus | |
【 摘 要 】
The aim of the current study was to develop a highly flexible and scalable modular real-time monitoring system withpredictive capabilities. The main focus was on forecasting tool/component life-span. A two-stage model is proposed for predictingtool life-span. Based on real-time monitoring data a back-propagation artificial neural network model was developed andvalidated. The obtained response surfaces for vibrations, current, and temperature are utilized in an analytical tool wearforecast model.
【 授权许可】
CC BY-NC
【 预 览 】
Files | Size | Format | View |
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RO201910284287449ZK.pdf | 700KB | download |