During the casting process of the high-voltage coil in dry-type transformers, significant deviations in the concentricity and verticality of the inner and outer molds can lead to an asymmetric coil structure, affecting the consistency of electrical parameters and potentially causing local overheating and electric field distortion. To address this issue, a detection and adjustment algorithm for mold concentricity and verticality in dry-type transformer coils is proposed. The algorithm utilizes high-precision laser displacement sensors to obtain the relative position of the mold within the three-dimensional framework and calculates the concentricity and verticality based on the measured position data. Subsequently, the gradient descent algorithm is employed to optimize the calculation and accurately determine the concentricity and verticality deviations. Upon completing the calculations, a microcontroller generates adjustment commands and drives push rods via stepper motors to precisely adjust the mold position. The system displays real-time detection data and integrates closed-loop feedback control to enhance adjustment accuracy and stability. Additionally, the system can automatically record detection data, supporting trend analysis over multiple measurements to optimize adjustment strategies. Experimental results demonstrate that the proposed algorithm operates stably and achieves high adjustment precision, maintaining a concentricity error within 2 mm and a verticality error of less than 1.5°. Compared with particle swarm optimization algorithm and genetic algorithm, this method has higher computational efficiency. Under the condition of a concentricity deviation of 20 mm, the optimization time only takes 11.2 s, which is suitable for real-time detection and online adjustment. It can effectively improve the manufacturing accuracy and consistency of dry variable coils, reduce manual intervention, and improve the automation level of production.