Optimization of annealing cycle parameters of dual phase and interstitial free steels by multiobjective genetic algorithms

ABSTRACT

Data-driven models have been constructed for Dual Phase (DP) and Interstitials Free (IF) steels using an evolutionary approach. DP steel data are utilized from an existing database, while for the IF steels, data generated at an integrated steel plant have been used. The objective function for Ultimate Tensile Strength (UTS) and % elongation, created as data-driven models, is simultaneously optimized for an optimum strength-ductility balance and the results indicate the possibilities of developing steels with better mechanical properties than what are known to have been existing so far.

KEYWORDS:

• Annealing
• cold rolling
• data-driven modeling
• DP steel
• genetic algorithms
• IF steel
• multi-objective optimization
• pareto-optimality
• strength-ductility balance