Transforming Manufacturing with AI: Advanced Predictive Maintenance Solutions

Abstract

This paper examines the use of data analytics and Artificial Intelligence (AI) in predictive maintenance in the industrial sector, emphasizing the importance of these technologies in raising operational effectiveness and decreasing downtime. It addresses integrating Artificial Intelligence (AI) techniques with data analytics to anticipate equipment breakdowns and improve maintenance schedules. These approaches include machine learning algorithms and deep learning models like Long Short Term Memory (LSTM). The chapter also includes a case study on the NASA Turbofan Engine Degradation. The simulation uses LSTM models to predict the remaining lifespan of turbine engines using artificial intelligence data from sensors. Evaluation metrics are used to evaluate the models' prediction ability and pinpoint areas that require more improvement. These metrics include the Mean Square Error (MSE), Mean Absolute Error (MAE), and R-squared score.