The student Xabier Lazcano Rayo obtained an OUTSTANDING qualification in the thesis

The student Xabier Lazcano Rayo obtained an OUTSTANDING qualification in the thesis

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Thesis title: Tool geometry and cutting conditions optimisation for face milling and reaming machining operations based on the modelling of cutting forces, process stability and surface roughness

Court:

• Chairmanship: Manuel San Juan Blanco (Universidad de Valladolid)
• Vocal:Andrés Sela Barrial (Mondragon Unibertsitatea)
• Vocal:François Ducobu (UMONS)
• Vocal: Jean-Marc Linares (Aix Marseille Université)
• Secretary:Mikel Cuesta Zabaljauregui (Mondragon Unibertsitatea)

Abstract:

• Companies wishing to stay as leaders in the manufacturing sector face with the need to be increasingly responsive to customers. Being machining one of the most important material removal operations for the manufacturing industry, accounting for between 3 % and 10 % of the Gross Domestic Product (GDP) of developed countries, trial-and-error strategies are still employed during manufacturing processes and product design. As a result, response times are not reduced as necessary, and the ability to provide a personalised product to each customer's requirements is lost. One solution to this problem involves implementing the use machining of predictive models. However, current models often require long calculation times, and predictions are frequently carried out one at a time, also resulting in numerous readjustments of the cutting conditions and tool geometry. Consequently, the economic costs are high, and time penalties are numerous.
• The present Ph.D., therefore, presents a series of predictive models for face milling and reaming operations that, overall, allow optimising both cutting tool geometries and cutting conditions by the prediction of cutting forces, process stability and surface roughness, especially in finishing conditions.
• Regarding cutting force prediction, the orthogonal to oblique model was implemented. Depending on whether the material is brittle (48-2-2 y-TiAl) or ductile (A-356, JETHETE-M152), two methodologies were established for database development. These three alloys are considered as key for automotive and aeronautical industries. In order to improve their accuracy in finishing conditions, it was proposed to take into account the effect of the cutting-edge radius and clearance angle, as well as to consider the specific edge coefficient variable. Thus, the prediction errors did not exceed 16 N for both cutting operations.
• In regard to process stability, frequency-domain and time-domain models were implemented for chatter prediction. Frequency domain models were based on the Average Tooth Angle approach and the Fourier Series Approach. Their accuracy was determined, concluding that Fourier Series Approach is more precise for face milling, whereas both are valid for reaming. The importance of calculating precisely the specific cutting energy was demonstrated, as this parameter affects to the width of the stability lobes and the limit cutting edge contact length.
• And for surface roughness, predictive models were developed to calculate 2D roughness profiles for reaming and 3D roughness surfaces for face milling. Roughness was modelled as a split signal in two components: (i) the kinematic movements of the cutting edge and its geometry, and (ii) a novel approach considering the chip removal process, material defects or vibrations (called as stochastic roughness). It was demonstrated that the use of the stochastic roughness improved between a 27 % and a 76 % the predictions of roughness indicators related to the amplitude of the profile (Rf, Rmax, Rt and Rz) and to a lesser extent Ra. In addition, a sensitivity analysis was performed to identify the effects of the feed rate and several geometrical parameters of the tool. Finally, roughness maps were presented as a novel optimization tool to define the micro-geometry of the inserts, their axial position in the tool and the feed rate for face milling tools.