Real-Time Production Monitoring Approach for Smart Manufacturing with Artificial Intelligence Techniques  
Author Q. T. Nguyen

 
Co-Author(s) H. D. Nguyen; K. P. Tran; P. Castagliola; E. Frénod

 
Abstract Production monitoring in real-time is a very important problem in smart manufacturing. It helps enterprises to timely detect abnormalities in the production process and then guarantee the product quality and reduce waste. In this paper, we develop a novel method to monitor the real-time production based on the Convolution Neural Network and the Support Vector Data Description algorithm. The numerical result shows that our proposed method leads to high efficient on the testing data.

 
Keywords Real-time monitoring, SVDD, CNN, One-class classification, Anomaly detection, transfer learning
   
    Article #:  DSBFI19-92
 
Proceedings of ISSAT International Conference on Data Science in Business, Finance and Industry
July 3-5, 2019 - Da Nang, Vietnam