To improve the service life of hot forging die, the additive manufacturing algorithm and additive manufacturing device for die remanufacturing are developed. Firstly, a compound filling algorithm in which the inner zone is filled by linear scanning and the outer contour is filled by offsetting is developed in order to solve the problems encountered in filling path planning for wire arc additive manufacturing (WAAM) like staircase effect at marginal division, degenerated edge at outer contour, programming difficulty, and so forth. Meanwhile, the attitude control algorithm of welding gun is proposed to control the angle between welding gun and welding path so as to improve the welding forming quality. Secondly, the high-temperature and low-temperature wear resistances of Fe-based and Ni-based alloy are tested. The results show that Ni-based alloy has higher high-temperature wear resistance. Finally, a disabled crankshaft hot forging die is selected for application test and the results show that, using the techniques discussed in this paper, welding materials can be saved by more than 50% and machining cost can be saved by more than 60%. In addition, the surface of automatic-repaired die is smooth without oxidation, collapse, and other defects after forging 3000 times, which is much better than that of manual-repaired die.

To improve the service life and reduce the repair cost of continuous casting rollers, a new welding-hammering hybrid remanufacturing process in which the roller was designed with a gradient structure was proposed, and corresponding equipment was developed. First, the failure modes and their causes for a continuous casting roller were analyzed by numerical simulation. The cyclic tension–compression shear stress, cyclic tension–compression normal stress, thermal cycle, and highly corrosive environment caused fatigue cracking and overall peeling of the roller surface. Second, the gradient structure composed of a base layer, transition layer, and strengthened layer of a continuous casting roller was designed, and materials for each layer were selected according to their different service conditions. Third, novel equipment for continuous welding-hammering composite remanufacturing was developed, and the optimized process parameters were obtained through welding experiments. Finally, an application test was carried out; the microscopic analysis showed that refined grains, fewer welding defects, and better surface toughness were obtained. Compared with traditional remanufacturing processes without hammering, the welding-hammering hybrid process achieved a forged structure instead of as-cast structure, which significantly improved the service life of the continuous casting roller by about 100%.

To study the hot deformation behavior of and obtain the optimal hot processing parameters for 2219 aluminum alloy, a new, precise constitutive model based on the partial derivative of flow data was constructed and hot processing maps were constructed based on the new model. First, isothermal compression experiments were conducted at strain rates of 0.01–10 s⁻¹ and temperatures of 573–773 K, and the high-order differences of the logarithmic stress with respect to the temperature and logarithmic strain rate were calculated. Second, a new, precise constitutive model based on the high-order differences was constructed, and the predictive accuracies of the new model and the Arrhenius model were compared. Finally, the hot processing maps of 2219 aluminum alloy were constructed using the new model, and its optimal hot processing parameters were validated with metallographic experiments. The results showed that a first-order approximation between logarithmic stress and temperature and a third-order approximation between logarithmic stress and the logarithmic strain rate need to be considered to construct a high-precision constitutive model without significantly increasing material parameters. The new model exhibited a significantly higher prediction accuracy than the Arrhenius model at a high strain rate and low temperature levels. With an increase in temperature, the energy dissipation increased at a constant strain rate, and with an increase in the strain rate, the energy dissipation first increased and then decreased at constant temperature. The best region for hot processing was located in the temperature range of 673–773 K and the strain rate range of 0.1–1 s⁻¹. The results of microstructure analysis were in good agreement with the prediction results of hot processing maps. Hot processing maps can be used to guide the hot working process formulation of 2219 aluminum alloy.

Ni-based superalloys are widely used in aerospace applications. However, traditional constitutive equations often lack the necessary accuracy to predict their high-temperature behavior. A novel constitutive model, utilizing Taylor series expansions and partial derivatives, is proposed to predict the high-temperature flow behavior of a nickel-based superalloy. Hot compression tests were conducted at various strain rates (0.01 s⁻¹, 0.1 s⁻¹, 1 s⁻¹, and 10 s⁻¹) and temperatures (850 °C to 1200 °C) to gather comprehensive experimental data. The performance of the new model was evaluated against classical models, specifically the Arrhenius and Hensel–Spittel (HS) models, using metrics such as the correlation coefficient (R), root mean square error (RMSE), sum of squared errors (SSE), and sum of absolute errors (SAE). The key findings reveal that the new model achieves superior prediction accuracy with an R value of 0.9948 and significantly lower RMSE (22.5), SSE (16,356), and SAE (5561 MPa) compared to the Arrhenius and HS models. Additionally, the stability of the first-order partial derivative of logarithmic stress with respect to temperature ($\partial \mathrm{l}\mathrm{n}\sigma /\partial T$) indicates that the logarithmic stress–temperature relationship can be approximated by a linear function with minimal curvature, which is effectively described by a second-degree polynomial. Furthermore, the relationship between logarithmic stress and logarithmic strain rate ($\partial \mathrm{l}\mathrm{n}\sigma /\partial \mathrm{l}\mathrm{n}\dot{\epsilon }$) is more precisely captured using a third-degree polynomial. The accuracy of the new model provides an analytical basis for finite element simulation software. This helps better control and optimize processes, thus improving manufacturing efficiency and product quality. This study enables the optimization of high-temperature forming processes for current superalloy products, especially in aerospace engineering and materials science. It also provides a reference for future research on constitutive models and high-temperature material behavior in various industrial applications.