Surface Roughness Monitoring and Prediction in a High Speed end Milling Process in Aluminum and Steel Alloys-Edición Única

The present study seeks to monitor and predict surface roughness in a high speed end milling process. Five specific objectives are sought in this study: 1. Establish a technological platform in which process monitoring is possible at high frequency sampling. 2. Analyze and predict the forced vibrations (Acc[x]) produced by the spindle speed and cutting conditions. 3. Determine the effect that the controllable parameters (spindle speed, depth of cut, feed per tooth and feed rate) together with forced vibrations have on the final Surface roughness (Ra). 4. Analyze and predict the machine vibrations (Acc[x]) produced by the spindle speed and its proper feed rate (Vf). 5. Create efficient surface roughness predictors for (7075-T6, 6061- T6 Aluminum and 1045 Steel) different materials in high speed end milling operations, using statistical analysis tools. 6. Compare theorical and estimated surface roughness models. Accelerometers and CNC variables are tested to experimentally acquire data of the machining process in order to develop a model in which the surface roughness of parts is predicted. Process parameters and dynamic vibrations are used to develop the model using regression statistical tools. While experimenting, tool diameter, parts material, and depth of cut are remained constant. Once the model is obtained, final experimentation is made to corroborate its reliability. Finally, a concluding study is made to determine the individual effect of each parameter with the surface roughness. IV TABLE OF CON