The grinding process is a manufacturing process that is performed at the end of the machining chain. In such step, the workpiece has a high added-value and therefore critical problems are not allowed, as they may lead to scrap and significant financial loss. Regenerative chatter is the most common form of self-excited vibration. It can occur often because most metal cutting operations involve overlapping cuts which can be a source of vibration amplification. The occurrence of the chatter phenomenon in the grinding process is considered a critical problem because it causes several negative effects, such as poor surface quality, unacceptable inaccuracy, and disproportionate tool wear, to name a few. The objective of this research work is to monitor the onset of the chatter phenomenon in grinding of SAE 1045 steel with an aluminum oxide grinding wheel by digital signal processing techniques of the acceleration signals. Experimental tests were performed in a surface grinding machine and using a data acquisition system with sampling frequency of 2 MHz. The data was analyzed with respect to the frequency content and the Ratio of Power (ROP) statistical parameter obtained for normal and chatter conditions. Visual inspections through digital images of the workpieces surfaces were conducted and then chatter frequency was determined. Results showed that the magnitudes related to the frequencies close to 30 Hz change as chatter phenomenon occurs. The ROP shows features related to the chatter vibrations. The methodology presented herein therefore allows for the automation and optimization of the grinding process.

Among the methods used in structural health monitoring (SHM), the electromechanical impedance technique (EMI), which uses piezoelectric transducers of lead zirconate titanate (PZT), stands out for its low cost. This paper presents a new approach for monitoring of the dressing operation based on structural health monitoring from the digital processing of voltage signals based on the time-domain response of a PZT transducer by EMI method. Experimental tests of the dressing process were performed by using a single-point dresser equipped with a natural diamond. The voltage signals in the time-domain were collected in different damage levels using a measurements EMI System. By using damage metrics, it was possible to qualify different damage levels that the diamond suffered during the dressing operation, observing variations from the magnitude of the signals. The dressing operation is of utmost importance for the grinding process and the dresser wear negatively affects the result of the process, which owns high added value. In this way, this work contributes with a new monitoring tool which aims ensuring a consistent dressing operation.Keywords: Manufacturing process, automation, electromechanical impedance, dressing operation.

The grinding process is usually one of the last stages in the manufacturing process chain since it can provide superior surface finish and closer dimensional tolerances. However, due to peculiarities of the grinding process, a workpiece material is susceptible to many problems, and demands a reliable real-time monitoring system. Some grinding monitoring systems have been proposed by means of sensors. However, the literature is still scarce in terms of employing time–frequency analysis techniques during the grinding of ceramics. Thus, this paper proposes an application of a low-cost piezoelectric transducer (PZT) in the analysis of the surface quality of ceramic workpieces during the grinding process by means of the frequency–time domain technique along with the ratio of power (ROP) parameter. An integrated, high-cost, commonly-used acoustic emission (AE) sensor was employed in order to compare the results with the low-cost PZT transducer. Tests were performed using a surface grinding machine. Three depth of cut values were selected in order to represent slight, moderate, and severe grinding conditions. Signals were collected at 2 MHz. The short-time Fourier transform (STFT) was studied in order to obtain the frequency variations over time. An analysis of the ROP values was performed in order to establish a correlation with the surface roughness. The ROP values are highly desirable for setting a threshold to detect the workpiece surface quality and for implementing it into a monitoring system. The results using the PZT transducer showed a great similarity to those obtained using the AE sensor.