Monitoramento dinâmico com Real Time Process Control, uma integração da tecnologia da Indústria 4.0 nos processos de fabricação industrial

Abstract

The increasing complexity of manufacturing processes in the Industry 4.0 era presents significant challenges, particularly in the real-time verification and diagnosis of machine states. Currently, test stations are limited to displaying the pass or fail status of the cell under test, requiring multiple manual interactions with various tools to identify and resolve issues. This process is time-consuming, inefficient, and prone to errors, negatively impacting operational efficiency and product quality. This dissertation aims to investigate and present the implementation of Real Time Process Control (RTPC) as a solution to these challenges. The proposal involves integrating Industry 4.0 technologies such as the Internet of Things (IoT), Big Data, Artificial Intelligence (AI), and Cyber-Physical Systems (CPS) to develop a dynamic monitoring system that allows for immediate and accurate problem identification and resolution. The methods employed include analyzing log results from generated files, calculating Yield and production, and presenting data through an intuitive interface. The research utilized a detailed framework for the implementation of RTPC. The results obtained demonstrate that the implementation of RTPC significantly increased operational efficiency, reduced maintenance costs, and improved product quality, showing reductions in downtime and improvements in productivity, validating the effectiveness of this approach in optimizing industrial manufacturing processes.