Global optimization of reliability design for large ball mill gear transmission based on the Kriging model and genetic algorithm

• Improves the optimal efficiency of Genetic Algorithm based on the Kriging model
• Takes the Kriging model as the agency function for optimization
• Sets both the volume and reliability as objective function of optimization
• The reliability improves greatly under requirement of max volume.

This paper aims to improve the global optimization operation efficiency in engineering by establishing the Kriging model to simplify the calculated mathematics model. In the case of the large ball mill, this paper presents in detail the application of the stress–strength distribution interference theory to calculate the reliability of gear transmission, establishes the Kriging model for function fitting, and uses genetic algorithm to globally optimize the volume and reliability of large ball mill gear transmission. The optimal result based the Kriging model is contrasted with the Monte Carlo Method in terms of calculation accuracy, greatly improving the efficiency of calculation.