<p>Inductive heating has gained popularity for its rapid heating, precise temperature control, and eco-friendliness, but optimizing system efficiency remains a challenge. This research addresses this issue by using the Taguchi method, a statistical approach, to systematically evaluate and optimize nine key control factors in inductive heating. These factors include the number of coils, coil turns, frequency, inner and outer coil radii, coil length, billet radius, billet translational velocity, and initial billet temperature. Each factor is tested at three levels, and the L27 orthogonal array (OA) is used to optimize them simultaneously, avoiding the traditional trial-and-error approach. The study finds that number of coils, the billet radius, the billet translational velocity, and the Frequency are the most critical factors influencing inductive heating efficiency. A main effect screener analysis validates the results, confirming the effectiveness of the Taguchi method in optimizing the system. As a practical application, the study uses COMSOL Multiphysics software to design an inductive heating system that achieves 85% efficiency. The optimized system features three coils, 13,000 coil turns, a 50&#xa0;Hz frequency, and specific dimensions and parameters for the coils and billet. By fine-tuning control parameters, this method streamlines the design process for inductive heating systems, making it more efficient and cost-effective. The findings not only enhance performance but also broaden the potential applications of inductive heating technology across various fields.</p> Graphical abstract <p></p>