Title :
DOE-Based Hybrid Automatic Process Control for Variation Reduction
Author :
Ye, Liang ; Pan, Ershun ; Xi, Lifeng
Author_Institution :
Shanghai Jiao Tong Univ., Shanghai
Abstract :
The quality improvement of industrial processes is achieved by maintaining their mean continuously close to the target value while reducing process variability. When there are strong noise factors including observable noises and unobservable ones in the process, use of parameter design, feedforward control or feedback control alone may not be effective. In this paper, an integrated online control strategy which is able to compensate all sources of noise factors is developed. The framework of the proposed hybrid control scheme is given and a two-step approach for the integrated design of feedforward and feedback controllers is also presented.
Keywords :
design of experiments; feedback; feedforward; process control; quality control; DOE-based hybrid automatic process control; design of experiment; feedback control; feedforward control; industrial process; integrated online control; noise factor; quality improvement; variation reduction; Engineering management; Feedback control; Industrial engineering; Manufacturing processes; Noise measurement; Noise reduction; Optimal control; Process control; Production; Quality management;
Conference_Titel :
Innovative Computing, Information and Control, 2007. ICICIC '07. Second International Conference on
Conference_Location :
Kumamoto
Print_ISBN :
0-7695-2882-1
DOI :
10.1109/ICICIC.2007.271