Development and Validation of a Thermometallurgical Model for Furnace-Based Austenitization During Hot Stamping

In hot-forming die-quenching (HFDQ) boron manganese steel blanks are heated within a roller hearth furnace, and then simultaneously quenched and formed into fully martensitic body-in-white components. Industry needs models that can predict the instantaneous temperature and austenite phase fraction within the roller furnace to diagnose problems (e.g., incomplete austenitization), forecast costs, and optimize process settings. This paper introduces a thermometallurgical model for Al–Si coated 22MnB5, consisting of a coupled heat transfer and austenitization submodels. Two candidate austenitization submodels are considered: an empirical first-order model and a model based on the detailed austenitization kinetics. In the case of the first-order model, a detailed Monte Carlo procedure is used to construct 95% credibility intervals for the blank temperature and austenite phase fraction that accounts for uncertainties in the furnace temperature and model parameters. The models are first assessed using temperature and austenite phase fractions from Al–Si coated 22MnB5 coupons heated in a laboratory-scale muffle furnace, and then used to simulate austenitization of patched blanks within an industrial roller hearth furnace. The results show that the empirical first-order model provides a more robust estimate of austenite phase fraction compared to the detailed model.

Development of a Thermo-Metallurgical Model to Predict Heating and Austenitization of 22MnB5 for Hot Forming Die Quenching

Hot forming die quenching (HFDQ) is used to transform ultrahigh strength steel blanks into martensitic body-in-white components that are lighter than parts made from traditional mild steels, without sacrificing crash performance. The part is sometimes locally reinforced by spot-welding patches to the blanks, but the increased thickness of the patched blanks sometimes results in incomplete austenitization, which can compromise the strength of as-formed parts. This paper presents an integrated thermo-metallurgical model of the austenitization of Al-Si coated 22MnB5 within a roller hearth furnace. While previous models account for the latent heat of austenitization by heuristically adjusting the specific heat, the present model explicitly simulates austenite formation using a first-order metallurgy submodel derived from dilatometry measurements. The model is validated by comparing predicted temperatures to measurements carried out on coupons heated within a lab-scale muffle furnace and full-sized blanks heated in an industrial-scale roller hearth furnace. Finally, the model is used to optimize roller speed based on zone temperatures.

Direct Contact Heating for Hot Forming Die Quenching

Most hot forming lines use slow, energy-intensive roller hearth furnaces to austenitize boron steel “blanks”. This paper describes an alternative heating technology in which blanks are austenitized by bringing them into contact with a hot monolith. The austenitizing temperature was reached in less than 30 seconds, and subsequent material characterization tests on oil-quenched blanks confirm that a fully martensitic structure is formed, and that the hardness and yield strength are comparable to furnace-treated samples. An Al-Si coating is typically used to prevent the oxidation and decarburization of the blanks within the furnace; preliminary tests found that the coating adheres to the monolith, impeding blank transfer and damaging the Al-Si-Fe ternary coating. Five interchangeable striking surfaces were assessed to see if they were less prone to adhering to the molten Al-Si coating.

Research for Swing Heating Furnace Temperature Optimization System of Plate Roller-Hearth Normalizing Furnace

In recent years, with the continuous improvement of the quality requirements of the plate heat treatment, the swing heated gradually become the focus of attention of many researchers. Based on the above considerations, in this paper, we established the furnace temperature pre-setting system, using the intelligence algorithm of improved PSO, under the premise of swing heating of roller-hearth normalizing furnace; and studied the optimal furnace temperature optimization curve, namely the optimal furnace temperature system, under the heat treatment process of the swing of the whole furnace and steel mixed. Through the Matlab simulation, we obtained the steel Temperature Prediction curve under the optimal furnace temperature system. By comparison, verifying the accuracy of the researched optimal furnace temperature optimization curve.