Development of an Intelligent Machine Parameterization System Using Artificial Intelligence for Industry 4.0

Abstract

The development of intelligent machine parameterization systems represents a significant advancement in the context of Digital Transformation and Industry 4.0, promoting greater efficiency, productivity, and autonomy in industrial processes. In this scenario, the integration of Artificial Intelligence (AI), the Internet of Things (IoT), and automated systems enables the creation of solutions capable of monitoring, analyzing, and adjusting operational parameters in real time. The objective of this work is to develop an intelligent machine parameterization system using Artificial Intelligence techniques to optimize industrial processes, reduce operational failures, and improve decision-making in the manufacturing environment. For this purpose, an integrated system was implemented. The adopted methodology was based on the application of IoT sensors to collect operational data from machines, combined with machine learning algorithms for predictive analysis and automatic parameter adjustment through a collector installed in an integrated and automated manner. The system was structured within an integrated architecture, allowing real-time communication between equipment, databases, and an intelligent monitoring platform. The obtained results demonstrated an increase in operational efficiency, a reduction in machine setup time, a decrease in human errors, and an improvement in the quality of production processes. Furthermore, a greater capacity for machine adaptation to variable production conditions was observed. The conclusion highlights that the use of intelligent systems based on AI and IoT significantly contributes to industrial modernization, making processes more autonomous, efficient, and aligned with the principles of Industry 4.0, thereby strengthening competitiveness and technological innovation within organizations.