QUALITY PREDICTION AND CONTROL OF INJECTION MOLDING PROCESS USING MULTISTAGE MWGRNN METHOD
A multistage moving window generalized regression neural network (GRNN) was demonstrated to injection molding batch process. Firstly analyzing the changes of process correlation can lead to effective division of a process into several operation stages, in good agreement with process knowledge. Then the nonlinearly and dynamic relationship between process variables and final qualities was made at different stages, and a multistage on-line quality prediction model was built. In addition, a closed-loop quality control system is proposed. Application has demonstrated that this method can not only give a valid quality prediction, but also effectively carry on quality closed-loop control.
Multistage batch process quality prediction generalized regression neural network (GRNN) Injection molding
XIAO-PING GUO FU-LI WANG SHU WANG
School of Information Engineering, Shenyang Institute of Chemical Technology, Shenyang 110142, China School of Information Science and Engineering, Northeastern University, Shenyang 110004, China
国际会议
2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)
大连
英文
3095-3100
2006-08-13（万方平台首次上网日期，不代表论文的发表时间）