A study of the high temperature DC performance of nitride high electron mobility transistors (HEMTs) on Si(111) and sapphire substrates with different gate lengths is reported. All single gate transistors decrease their drain current (I_D) and transconductance (g_m) from room temperature (RT) up to 350 °C, mainly due to the electron mobility reduction by optical phonon scattering. At RT, HEMTs on Si(111) present higher I_D and g_m than transistors on sapphire, probably related to their lower self‐heating. As devices are heated, these differences tend to disappear, indicating that the substrate thermal conductivity becomes less important. Compact devices have low relative reduction in I_D and g_m values with temperature, since shorter gate lengths lead to higher fields under the gate and lower temperature dependence of the drift velocity.

The evolution of the manufacturing industry has favored the use of new technologies that increase the level of autonomy in production systems. The work presented shows a methodology that allows for online estimation of cutting parameters based on the analysis of the cutting force signal pattern. The dynamic response of the tool is taken into account through a function that relates the response time to the input variables in the process. The force signal is obtained with a dynamometric platform based on piezoelectric sensors. The final section of the paper shows the experimental validation where machining tests with variable machining conditions were carried out. The results reveal high precision in the estimation of depths of cut in end milling.

This work presents a non-invasive and low-cost alternative to traditional methods for measuring the performance of machining processes directly on existing machine tools. A prototype measuring system has been developed based on non-contact microphones, a custom designed signal conditioning board and signal processing techniques that take advantage of the underlying physics of the machining process. Experiments have been conducted to estimate the depth of cut during end-milling process by means of the measurement of the acoustic emission energy generated during operation. Moreover, the predicted values have been compared with well established methods based on cutting forces measured by dynamometers.

This study aimed to develop a workstation to investigate robotic sanding processes of wooden parts. The applied methodology includes the conceptual design of the station, incorporating sensors for online measurement of process variables. The station is controlled by a computer that enables interaction with the robot, controlling the abrasive tool rotating speed, and acquiring and visualizing the process signals. The implemented workstation was used to investigate the influence of the sanding parameters on the process variables. The results established that the grain size and the rotational speed of the sandpaper produce statistically significant variations in the surface finishing. Finally, equations are proposed for relating the surface roughness with the sanding torque and acoustic emission measured during the operation. Keywords: wood sanding; industrial robotics; surface roughness; sanding torque; acoustic emission.