Waste to Energy Conversion and Predictive maintenance in Circular Economics Through AI

Abstract

This paper explores the transformative role of artificial intelligence (AI) in advancing the circular economy through waste-to-energy (WtE) conversion and predictive maintenance. By leveraging AI, waste management processes can be optimized to enhance the efficiency of resource recovery, minimize environmental impact, and generate renewable energy. Predictive maintenance, driven by AI, ensures the smooth operation of industrial equipment, reducing downtime and extending machinery lifespan. This integration supports sustainable production and aligns with important circular economy principles, including biomimicry, lean manufacturing, and the Butterfly Model. The study underscores the potential of AI-driven technologies in fostering a resilient and sustainable future by addressing critical environmental challenges and promoting efficient resource utilization.