Pass Schedule Optimization for a Tandem Cold Mill Using Chance-constrained Programming Method

Abstract

Pass schedules for a tandem cold mill have been optimized using the chance constrained programming method. Variations of variables are evaluated from past data without assuming probability distributions. Discrete constraints are smoothed with the sigmoid functions, and the sequential quadratic programming method is applied. Furthermore, the constraints are relaxed individually on a priority basis so that a feasible and practical solution is obtained. Experimental results with high tensile strength steel strips showed 13 to 35% decreases in off-gage length.