A sample of polyvinylidene fluoride removed from a riser component was tested in laboratory to evaluate its electromechanical behavior. For this, an experimental setup was developed, after Fourier Transform Infrared Spectroscopy (FTIR) results have shown through the absorption bands, that this sample had a spectrum of the piezoelectric phase β. In order to identify if such sample would be able to respond electrically to the application of external mechanical excitation applied by a shaker, measurements were made of the induced voltages by piezoelectric effect, with varying accelerations and frequencies. The results indicated that the material, although it has not been processed for this purpose, responds electrically to the applied mechanical stimulus, demonstrating a good correlation between the measured signals and the accelerations.

Smart manufacturing comprises fully integrated manufacturing systems that respond in real time to meet the changing demands and conditions in industrial activities, supply networks and customer needs. A smart manufacturing environment will face new challenges, including those concerning metrological issues, i.e., analysis of large quantities of data; communication systems for digitalization; measurement standards for automated process control; digital transformation of metrological services; and simulations and virtual measurement processes for the automatic assessment of measured data. Based on the assumption that the interplay between smart manufacturing and digitalization of metrology is an emerging research field, this paper aims to present a systematic literature review (SLR) based on a bibliographic data collection of 160 scientific articles retrieved from the Web of Science and Scopus databases over the 2016–2022 time frame. The findings presented in this review and recommendations for building a research agenda can help policy makers, researchers and practitioners by providing directions for the evolution of digital metrology and its role in the digitalization of the economy and society.

The objective was to analyze a recently developed flow measurement technique based on the vibration captured by an accelerometer attached to the pipeline surface for use in the oil industry. The applied methodology consists of performing an experimental study to obtain data in an accredited laboratory for calibration of flowmeters, estimating a flow rate for each vibration measured, followed by an uncertainty analysis. The results of water flow rates showed a measurement uncertainty between 2.5% and 5.0% of reading (95% confidence). While these results do not meet to Brazilian regulations for the measurement of crude oil of 0.3% of reading, they are acceptable under the regulations for produced, injected, captured, or discarded water, which occur the processing of oil.

Three-dimensional (3D) imaging technologies have been increasingly explored in academia and the industrial sector, especially the ones yielding point clouds. However, obtaining these data can still be expensive and time-consuming, reducing the efficiency of procedures dependent on large datasets, such as the generation of data for machine learning training, forest canopy calculation, and subsea survey. A trending solution is developing simulators for imaging systems, performing the virtual scanning of the digital world, and generating synthetic point clouds from the targets. This work presents a guideline for the development of modular Light Detection and Ranging (LiDAR) system simulators based on parallel raycasting algorithms, with its sensor modeled by metrological parameters and error models. A procedure for calibrating the sensor is also presented, based on comparing with the measurements made by a commercial LiDAR sensor. The sensor simulator developed as a case study resulted in a robust generation of synthetic point clouds in different scenarios, enabling the creation of datasets for use in concept tests, combining real and virtual data, among other applications.