Advancing Industrial Performance: Deep Learning and Machine Learning Techniques for Predictive Analytics of Key Performance Indicators

This collection of research explores the application of deep learning and machine learning techniques to enhance predictive analytics for key performance indicators (KPIs) across various industrial contexts. Focusing on electrical machines and the automotive industry, these studies investigate methods for efficiently forecasting KPIs to optimize operational efficiency and equipment effectiveness. Through the integration of techniques such as ensemble learning, semi-supervised learning, and various machine learning algorithms, the research aims to significantly reduce computational costs and improve the accuracy of predictions, providing actionable insights that can guide operational improvements and strategic decision-making in industrial settings.