Numerical optimization of SPIF for steel matrix composites using an elastoplastic damage model and desirability-based RSM

The Single Point Incremental Forming (SPIF) technique has received considerable recognition for its improved formability, versatile process capabilities, and diminished forming forces. Nevertheless, its widespread industrial adoption remains limited due to challenges in accurately predicting fracture during forming. This study addresses these challenges by examining the formability and damage mechanisms of a ferritic steel matrix composite reinforced with TiB₂ ceramic particles. By leveraging advanced materials and computational methods, our research focuses on optimizing the SPIF process for these composites, renowned for their exceptional mechanical properties. We analyze three critical process parameters—blank thickness, forming tool diameter, and wall angle of the cone—to evaluate their influences on deformation mechanics and process performance. Numerical simulations generate response surfaces to optimize forming parameters, focusing on punch force, equivalent plastic strain, Von Mises stress, and final forming depth. Employing a desirability function approach, we tackle this multi-objective optimization, providing a robust framework for parameter selection. This study demonstrates the potential of TiB₂-reinforced steel matrix composites in advanced forming applications and highlights the optimal SPIF conditions for achieving superior formability while minimizing damage. The findings offer valuable insights for industries working with innovative composite materials and advancing manufacturing efficiency.