Modeling and Optimization of Heat Treatment Process in Steel Wire Used in the Manufacture of Automotive Springs

The aim of this work was the creation of a statistical modeling, able to override the process used for the preparation of hardening and tempering ovens, which traditionally is performed by means of adjustments from results of mechanical properties, tested in the laboratory and required on customer specifications. We sought to understand the influence of input variables (factors) in the limit mechanical properties tensile strength, hardness and yield, in SAE 9254 steel wires, to the diameters 2.00 mm and 6.50 mm, used in the manufacture of clutch and valve springs for automotive. The main variables were investigated the case diameter, speed, temperature of tempering and quenching medium concentration, for this, we used the methods of design of experiments with block and multiple regression Analysis. For optimization of the methods were used statistical models, Generalized Reduced Gradient Desirability (GRG), Genetic Algorithm (GA) and the Meta-heuristics Simulated Annealing. The results revealed that all variables considered to have significant influence and the models were validated using appropriate statistical methods. This modeling and its optimization, if implemented and applied correctly, can lead to scientific advances which would provide the automation of this process.