Precise control system for moisture content in strips out of loosening and conditioning process step based on statistical regression analysis

In order to promote the control precision of moisture content in strips out of loosening and conditioning process step, a precise control model was developed following the statistical regression analysis of historical data of the said process step, and further revised for self-adaptive optimization with self-learning algorithm. The control system was validated with the data of on-line monitoring samples of "Hongqiqu (Tianxingjian) "cigarette brand in Nanyang Cigarette Factory. The results showed that:the control precision of moisture content in output strips was significantly improved, process deviation, standard deviation and extreme difference decreased by 0.24%, 0.078% and 0.34%, respectively; process capability index increased by 0.54. It indicated that the level of process control was effectively improved. This method provides a support for the promotion of intra-batch quality consistency in tobacco primary processing.