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Refractory titanium alloys are often used in aerospace industry for applications requiring high temperature strength and high mechanical resistance. However, the main problems encountered when machining this kind of material are the low material removal rate and the short cutting tool life. Due to their hard nature, an effective manufacturing strategy is required by industrials to optimize cutting parameters and improve machining efficiency. In this work, a new technique of optimization for dry machining refractory titanium alloys has been developed. The optimisation procedure is a new strategy based on both response surface method with “Kriging interpolation” and sequential quadratic programming algorithm. In comparison with previous models taken from the literature, two functions have been formulated in the machining problem to describe the non linear and complex relationship between variables and responses. The first function called “objective function” represents the volume of material removal produced during the cutting tool life and which has to be maximised. The second function called “constraint function” represents the surface roughness and has to be taken below a critical value. Thanks to this new approach, a robust optimization algorithm has been carried out to optimize cutting conditions taking into account productivity and quality.