Title :
A study of semiconductor industry accidents: Making predictions based on BP artificial neural networks
Author :
Liu Chao ; Hsuan Peichen ; Wu Jianping
Author_Institution :
ESH Dept., Semicond. Manuf. Int. Corp., Shanghai, China
Abstract :
This paper puts forward using BP artificial neural network to forecast semiconductor industry accidents, using optimized and quantifiable impact factors of accidents as input nodes and accident quantity as the output node. The established predictive model has 7 input parameters and 1 output parameter. This paper uses this model to predict and validate the accident occurrence circumstances of a semiconductor company and gets accurate results.
Keywords :
accidents; backpropagation; neural nets; production engineering computing; semiconductor industry; BP artificial neural networks; accident occurrence; semiconductor company; semiconductor industry accidents; semiconductor industry accidents forecasting; Accidents; Neural networks; Personnel; Predictive models; Safety; Semiconductor device modeling; Training; BP Artificial Neural Network; Impact Factors; Prediction; Semiconductor;
Conference_Titel :
Industrial Engineering and Engineering Management (IEEM), 2013 IEEE International Conference on
Conference_Location :
Bangkok
DOI :
10.1109/IEEM.2013.6962460
