Sistema de automação IoT para gestão de ativos no cenário da indústria 4.0

Abstract

The fourth industrial revolution has several pillars, with the Internet of Things and Big Data being one of the most prominent. These technologies make it possible to collect and analyze large data sets in real time, allowing the development of models for the most diverse situations, from consumer behavior to the prevention of manufacturing failures. In this context, the present work addresses the development of a complete architecture for the implementation of an automation system for Industry 4.0, at the hardware and software level, based on the collection of temperature, hour meter, vibration and current data in electric motors of a primary aluminum industry. From the measured variables, vibration data can be obtained in the frequency domain, phase imbalance and Kalman filter estimation. A multicriteria decision algorithm was adopted to assist in choosing the programming language. After elaborating this systematic, a set of solutions was obtained that made the development of the system feasible, which was validated in a controlled experimental setup. The automation system developed was called IOTCORE, which performs the collection of variables in real time, with low latency, high performance, and makes it possible to transmit, store and visualize the data in several supervisory systems.