Investigação sobre o potencial da instrumentação de baixo custo na digitalização de máquinas-ferramenta antigas e seu impacto na rugosidade superficial

Abstract

Intelligent manufacturing involves the convergence of Industry 4.0 technologies dedicated to modernizing production systems, which require active and real-time management to maximize their processes. In this sense, the integration of new technologies for monitoring manufacturing processes is becoming increasingly urgent to ensure competitiveness. However, many companies have outdated structures in which old and outdated machine tools that do not offer communication or data transmission represent a significant portion of the equipment in operation. The main reasons for this reality are the lack of financial resources for updating the manufacturing park and the lack of strategic vision for the business. Within this context, this study proposes an investigation into the impact of digitizing legacy machine tools on productivity and the potential for improving surface quality through low-cost instrumentation. For the development of this work, low-cost sensors and hardware were installed on a universal lathe for continuous and real-time monitoring of the turning process. Instrumentation based on the IoT (Internet of Things) concept allowed for data collection and exchange with a cloud-based analysis system via a Wi-Fi connection. A rapid prototyping board was used to collect sensor data and transmit it to the cloud platform, allowing for the creation of a history and real-time monitoring of the process. The results confirm the influence of cutting speed and feed rate on surface finish, as described in the literature. The instrumentation used showed good results in monitoring rotation and feed rate. The difference between the rotations (measured by the sensor and the configuration) was less than 4.38%, while the differences in feed rate did not exceed 6.33%. The results of vibration parameters were not as evident due to the low amplitudes presented in the analyzed spectrum. The main reason is associated with the low sensitivity of the accelerometer associated with the use of new cutting edges in each experiment, which reduces the vibration levels of the process. Despite the low amplitudes, it was possible to establish the influence of the RMS values on surface roughness. It is expected that this study will contribute to recent research on manufacturing process monitoring and enable a solid analysis of the benefits of real-time monitoring of machining on universal mechanical lathes.