PURPOSE: To provide an inexpensive blender optimization control system which is easily handled and can perform quality estimation and control rationally in an optimum state at the highest speed.
CONSTITUTION: In this blender optimization control system 100, property quality and a mixing ratio for respective kind of base materials A, B, and C are inputted by a mixing quality estimation part 1, so that the temporary quality of a specific product is estimated by a neural network to search the cheapest mixing ratio by a cheapest mixing ratio search part 2 through genetic algorithm according to specific predetermined restriction items. A product quality estimation part 3 estimates the actual quality regarding the specific product by the neural network according to analytic data from an analysis part 6, and a quality control part 4 performs correction control over the difference between the estimation result of the actual quality and the cheapest mixing ratio. A quality estimation system structuring part 5 inputs the property quality and mixing ratio regarding the base materials A, B, and C and the estimation result of the actual quality, learns the estimation result of the actual quality as tutor data, and controls the mixing quality estimation part on the basis of the result.
MATSUO GOSUKE
FURUICHI HIDETSUGU
