Uso da engenharia 4.0 para modelagem de risco: text mining e machine learning para classificação automática de acidentes de trabalho

Abstract

The evolution of industry throughout the centuries has been marked by revolutions that have transformed the way products are manufactured and processes are managed. The Fourth Industrial Revolution, also known as Industry 4.0, has played a fundamental role in transforming industrial processes, driving significant advances in automation, digitalization, and workplace safety. This work proposes the development of computational algorithms in Python to identify the severity of injuries resulting from workplace accidents, with an emphasis on the use of text mining with machine learning. Using advanced artificial intelligence techniques such as Artificial Neural Networks (ANN) and Support Vector Machines (SVM), the research seeks to understand the occurrence of accidents in the workplace, highlighting the importance of controlling these incidents for the safety and well-being of workers. The results obtained demonstrate that ANN models exhibit high accuracy in estimating working conditions and classifying accidents, while SVM models offer an effective approach in identifying specific classifications. Integration of these techniques is recommended to enhance continuous monitoring and management of occupational risks, contributing to the development of safer, healthier, and more productive work environments.