Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551039
Pertenecen a esta colección Tesis y Trabajos de grado de las Maestrías correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
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- Experimental analysis of high productivity multivariable cutting tools in milling operations towards the machining of composite material (CFRP/TiAl6V4)(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2021-02-02) Carrasco Mendoza, Heber Nahum; Olvera Trejo, Daniel; puelquio, emimayorquin; Puma Araujo, Santiago Daniel; Elías Zúñiga, Alex; School of Engineering and Information Technology; Campus Monterrey; Urbikain Pelayo, GorkaDuring the last years, there has been an increased interest in the study of composites, but more specifically in Carbon Fiber Reinforced Polymer with Titanium matrix (CFRP/TiAl6V4). Since the machining of composites is different and more complicated than other materials like metals, the cutting theories of metals cannot be used for the machining of composites. This research aims to develop an analytical/mechanistic method that can describe the high productivity multivariable cutting tools and predict the best cutting parameters to avoid chatter using stability lobes; towards the machining of CFRP/TiAl6V4. One outcome is developing and validating a new design for a multivariable cutting tool based on experimental data analysis. The study will be done in a practical and modeling environment to be optimized with a computational approach. Different modeling and optimization techniques will be explored to evaluate the performance of the design cutting tool. To obtain the ideal cutting coefficients, edge characterization was performed. Stability lobes were explored with the multivariable tools to get the best boundaries. Also, time-domain simulations based on the Continuous Wavelet Transform (CWT) graphs, Power Spectral Density (PSD) charts, and Poncairé Maps were used to validate the stability lobes boundaries found by using the first-order EMHPM for the multivariable tools.

