Experimentation on NN Models for Hazard Identification in Machinery Functional Safety

Abstract

The use of Artificial Intelligence (AI) in machinery functional safety can enhance efficiency and accuracy by automating tasks previously carried out by humans. This paper presents an experimental evaluation of Neural Network (NN) models for hazard identification in machinery functional safety. The systematic study includes own implementations of NN models using open source building blocks and the use of an open source conversational AI framework with various pipeline configurations. The paper provides a comparative analysis of the qualitative and quantitative parameters for the models and configurations.