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Agustina Tejerizo, Beatriz De

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0000-0003-0149-6928
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Agustina Tejerizo
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Beatriz De
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  • Publicación
    Analysis of Force Signals for the Estimation of Surface Roughness during Robot-Assisted Polishing
    (MDPI, 2018-08-15) Teti, Roberto; Agustina Tejerizo, Beatriz De; Marín Martín, Marta María; Rubio Alvir, Eva María
    In this study feature extraction of force signals detected during robot-assisted polishing processes was carried out to estimate the surface roughness during the process. The purpose was to collect significant features from the signal that allow the determination of the end point of the polishing process based on surface roughness. For this objective, dry polishing turning tests were performed on a Robot-Assisted Polishing (RAP) machine (STRECON NanoRAP 200) during three polishing sessions, using the same polishing conditions. Along the tests, force signals were acquired and offline surface roughness measurements were taken at the end of each polishing session. As a main conclusion, it can be affirmed, regarding the force signal, that features extracted from both time and frequency domains are valuable data for the estimation of surface roughness.
  • Publicación
    A Multi-Response Optimization of Thrust Forces, Torques, and the Power of Tapping Operations by Cooling Air in Reinforced and Unreinforced Polyamide PA66
    (MDPI, 2018-03-20) Domingo Navas, María Rosario; Agustina Tejerizo, Beatriz De; Marín Martín, Marta María
    The use of cooling air during machining is an environmentally conscious procedure, and its applicability to different processes is a research priority. We studied tapping operations, an important operation in the assembly process, using cooling air with unreinforced polyamide (PA66) and polyamide reinforced with glass fiber (PA66-GF30). These materials are widely used in industry, but their behavior with respect to tapping has not been studied. We analyze the outcomes regarding the thrust force, torque, and power at cutting speeds between 15 and 60 m/min. The experimental tests were executed using cooling air at 22 °C, 2 °C, and −18 °C in dry conditions. The M12 × 1.75 mm taps were high-speed steel, with cobalt as the base material and coatings of TiN and AlCrN. To identify the more influential factors, an analysis of variance was performed, along with multi-response optimization to identify the desirability values. This optimization shows that the optimum for PA66can be found in environments close to 3 °C, while the optimum for PA66-GF30 is found at the minimal temperature studied (−18 °C). Thus, cooling air can be considered an adequate procedure for tapping operations, to increase the sustainability of the manufacturing processes.
  • Publicación
    Tool Selection in Drilling of Magnesium UNSM11917 Pieces under Dry and MQL Conditions based on Surface Roughness
    (Elsevier, 2017) Berzosa Lara, Fernando; Agustina Tejerizo, Beatriz De; Rubio Alvir, Eva María
    Nowadays, the use of lighter materials for transportation purposes is still a challenge; especially in the aeronautical and aerospace sectors. The use of certain materials, such as magnesium alloys which have exceptional mechanical properties relative to density as structural materials, allows a remarkable reduction of weight. These alloys have significant challenges in machining. On the one hand, their use with water-based lubricants can produce flammable hydrogen atmospheres and, on the other hand, the operational parameters can produce tiny chips which, at high temperature, could burn. Regarding the tools, drills are the most used ones in drilling operations; manufacturers do not always take in consideration magnesium alloys. This is why, sometimes, the data from other types of similar alloys need to be extrapolated. This work shows an experimental study about the drilling of magnesium pieces based on surface roughness. The main goal is to determine the tools that best suit the requirement of surface roughness for this type of operations, which, for the aeronautical sector, is from 0.8 to 1.6 μm. The tests have been conducted under different cutting conditions, using several types of tools and two sustainable lubrication systems. In particular, dry machining and minimum quantity of lubrication (MQL) system have been used. A design of experiments (DOE) has been used to optimize the resources. The average roughness, Ra, has been selected as a response variable. The roughness values obtained are lower than 0.9 μm (namely, from 0.13 μm to 0.87 μm); so, it is possible to increase some of the parameter values, in order to improve the productivity, without they go outside the established limits. The results have been analyzed using the analysis of variance (ANOVA) method. A model for estimating the expected surface roughness in terms of the Rae, has been developed.