The deep drawing process is widely employed in the manufacturing of gas cylinders, where force monitoring plays a crucial role in ensuring process stability, product quality, and operational safety. However, the integration of experimental force monitoring systems with Industrial Internet of Things (IIoT) architectures in real industrial environments remains limited. This study presents the development and experimental validation of an IIoT-based force monitoring system applied to the deep drawing process of gas cylinders. The system employs load cells installed on an industrial press to acquire force signals in real time, combined with a low-cost data acquisition unit and wireless communication for data transmission and storage. Experimental tests were conducted on a 500-ton hydraulic press during the deep drawing of steel gas cylinders, allowing the analysis of force evolution throughout the forming cycle. The results demonstrate good signal stability and repeatability, as well as the capability of the proposed system to capture characteristic force patterns associated with the deep drawing process. The integration with an IIoT architecture enables real-time monitoring, data traceability, and remote access, supporting future implementations of process control and predictive analysis. The proposed approach demonstrates the feasibility of implementing experimental force monitoring aligned with Industry 4.0 concepts in industrial deep drawing operations.
Morais et al. (Mon,) studied this question.