Improvement of algorithm and prediction precision of an extended Oxley's theoretical model

Algorithm-related problems including more than one convergent solutions, endless loop, no solution within the recommended search ranges, low prediction precision, and low efficiency arise when the Oxley's theoretical model and its extended models are applied. A new parameter-based algorithm is proposed in this paper which turns the model-solution-seeking process into an issue of multivariable optimization in order to solve the extended Oxley's theoretical model with higher prediction precision and efficiency. Genetic optimization algorithms and multivariable constrained optimization are combined with other functions offered by Matlab which are used to solve univariate transcendental equations to determine satisfactory model parameters (C-0, phi, delta), and the global optimal solution is selected as the only solution of the extended Oxley's theoretical model after a comparison of the predicted cutting forces, thrust forces, and chip thicknesses with experimental data. A method to calculate the temperature of the shear plane (T-AB) is introduced into the extended Oxley's theoretical model to further improve the prediction precision. With the above algorithm and improvements, the predicted results turn out to be in better agreement with the experimental data than the original results of the extended Oxley's theoretical model.