Predictive Model to Aid Selection of Heat Treating Process Parameter for Alloy Steel Forgings

摘要

Heat treatment is a very complex process involving many process parameters. It is important to select optimum process parameters to achieve desired mechanical properties. Predictive models are very useful tools to aid in the selection of these parameters. A regression model is developed to aid heat-treating process parameter selection for UNS G41300 grade of steel. This study gives a better understanding of factors affecting hardness of heat-treated forgings. The model performed comparable to a human expert in selecting the critical parameter, temper temperature at Gulf Coast Machine and Supply Company (Gulfco), Beaumont, Texas. Suggestions have also been made to improve the monitoring and control of the heat treatment process.