Production Anomaly Analysis of Discrete Manufacturing Process Based on Attention SRU
In order to judge the impact of production anomalies on production process,a prediction model for the remaining completion time of production tasks based on attention SRU neural network was designed after detailed analysis of the Internet of Things data generated in discrete manufacturing process.Through the parallel feature extraction process and by combination with the attention mechanism,different weights of information at different moments were given to predict the delayed delivery time of production tasks,which achieves the purpose of quantifying the impact of production anomalies on production process,and effectively improves the efficiency and accuracy of the algorithm,so as to help the workshop staff carry out subsequent decision-making control work.
discrete manufacturing processInternet of Manufacturing Things dataproduction anomaly analysisattention mechanismSRU neural network
国家科技期刊平台
NSTL
万方数据
