The interest of the scientific community for ultrasound techniques has increased in recent years due to its wide range of applications. A continuous effort of researchers and industries has been made in order to improve and increase the applicability of non-destructive evaluations (NDE). In this context, the monitoring of manufacturing processes, such as the grinding process, arises. This work proposes a novel technique of ultrasound monitoring (chirp-through-transmission) through low-cost piezoelectric diaphragms and digital signal processing. The proposed technique was applied to the monitoring of material removal during the grinding process. The technique is based on changes in ultrasonic waves when propagated through the material under study, with the difference that this technique does not use traditional parameters of ultrasonic techniques but digital signal processing (RMS and Counts). Furthermore, the novelty of the proposed technique is also the use of low-cost piezoelectric diaphragms in the emission and reception of ultrasonic waves, enabling the implementation of a low-cost monitoring system. The results show that the monitoring technique proposed in this work, when used in conjunction with the frequency band selection, is sensitive to the material removal in the grinding process and therefore presents an advance for monitoring the grinding processes.

Additive manufacturing (AM) has been playing a crucial role in the fourth industrial revolution. Sensor-based monitoring technologies are essential for detecting defects and providing feedback for process control. Acoustic emission (AE) sensors have been used for a long time in a wide range of processes and fields, but they are still a challenge in AM processes. This work presents a study on the AE signals in the time-domain—raw and root mean square (RMS) values—regarding their behavior during the manufacture of a single-layer part in the fused filament fabrication process for two infill patterns. The tests were conducted on a cartesian 3D printer using polylactic acid material. The AE sensor was attached to the printer table through a magnetic coupling, and the signal was collected by an oscilloscope at 1 MHz sampling frequency. It was found that the raw AE signals behaved quite differently not just for the two infill patterns, but within the same pattern. The raw and RMS AE signals contained many spikes along the whole process, but the higher ones were those generally occurring at the end and/or start of a fabrication line. The RMS values, however, were useful for finding the start and end times of each fabricated line for both patterns. The mean RMS values showed nearly constant but distinct averages for the extruder-only, table-only and extruder–table movements.

The fused deposition modeling (FDM) process, commonly known as three-dimensional (3D) printing, deals with the manufacturing of parts by the subsequent addition of layers of fused plastic filament. The parts obtained during this process can be used for domestic applications, rapid prototyping, or final applications. During the preparation of the printing model (slicing), different process parameters must be defined, such as extruder speed, extruder height in relation to the bed, and bed temperature. Parameters that, if incorrectly defined, can lead to a series of deficiencies in the parts, such as low dimensional accuracy, low surface quality, reduced mechanical resistance, and, eventually, the occurrence of several printing defects in the parts, impairing or even preventing its use. The 3D printing process has a critical period at its beginning during the manufacturing of the piece’s first layer. The present work aims to study some of the geometric anomalies observed in monolayer pieces when some of the printing parameters are improperly defined. Printing tests on monolayer parts were carried out with a polylactic acid (PLA) filament. Herein, a home grade 3D printer, model Graber i3, was used. The height of the extruder to the bed was altered in relation to the recommended value, and three pieces were printed for each height used. The printed parts were scanned with a 1200 × 1200 dpi resolution, using a DCP-L2540DW model scanner. The images obtained were then analyzed using the Matlab^® software and the geometric characteristics of the pieces were compared. The study is a first step towards a better understanding of the geometric defects obtained when an incorrect definition of basic parameters occurs when processing the three-dimensional model.

The 3D printing process deals with the manufacture of parts by adding layers of material onto a heated printing bed. Electret microphones are widely used as low-cost and precise measuring devices. However, its response was negatively affected by higher temperatures due to the field effect transistor utilized in its construction. The Pencil Lead Break (PLB) method is a standardized artificial acoustic emission source utilized for the evaluation of sensors response. The present work aimed to study the electret microphone response for 3D printing monitoring and to evaluate the efficiency of a proposed housing to reduce the printing bed temperature’s influence on the electret microphone’s response. The microphone housing was 3D-printed utilizing ABS filament; its geometry was designed with the purpose of separating the sensor from the heated bed and creating an acoustic shell. Then, PLB tests were performed, and the raw signal was collected from housed and non-housed microphones at 5 MHz sampling frequency. The sensors were tested under three temperatures of the printer bed: at 25 °C (ambient), at 65 °C (operating temperature), and, finally, after the temperature of the table was naturally stabilized from 65 °C to 25 °C. The signals were investigated in the time and frequency domain. The results showed that the housing impacts the microphone’s response positively when operating at 25 °C, where the signals presented higher amplitudes in both domains. However, the response obtained by the housed sensor was considerably attenuated at 65 °C. Furthermore, the signals collected at 25 °C after exposing the housed microphone to heat demonstrated a “greenhouse effect”, keeping the sensor at higher temperatures for an extended period. It can be concluded that the proposed housing failed in reducing the temperature effects in the sensor’s response. However, these effects were shown to be significant and the need for an alternative method to attenuate them was reinforced.

The 3D printing process deals with the production of three-dimensional objects with defined geometries. However, this manufacturing process has a crucial point established at the beginning of the object manufacturing, where anomalies can occur and compromise the entire object produced. The piezoelectric diaphragm has been studied as an alternative to the conventional acoustic emission (AE) sensor concerning the monitoring of structures and processes. It has in its assembling a ceramic element with piezoelectric properties, which makes its response sensitive to temperature variations. The Pencil Lead Break (PLB) method is widely used due to its efficiency in the characterization of AE sensors. The present work aims to study the influence of temperature on the piezoelectric diaphragm response for the monitoring of the 3D printing process. PLB tests were performed on the glass surface of a 3D printer at three different temperatures, and the raw signal was collected at 5 MHz sample rate. The signal was investigated in the time and frequency domain. The results demonstrate that the frequency response of the sensor is directly influenced by the temperature variations. In addition, the signal amplitude variations occur differently along the entire spectrum, and frequency bands with small and large amplitude variations can be selected for a comparison study. Furthermore, two frequency bands were carefully selected, and the mean error was obtained regarding the reference temperatures of 25 and 45 °C. It can be inferred that the piezoelectric transducer has low sensitivity to temperature variation if a proper frequency band is selected, where an acceptable error of 16.9% was obtained.