AI Based Predictive Maintenance for Circular Economy

This document is a research article that discusses the integration of artificial intelligence (AI) in predictive maintenance (PdM) as a means to support the circular economy (CE). It outlines the KYKLOS 4.0 project, which aims to develop a circular manufacturing ecosystem utilizing AI technologies. The article explains the importance of digitalization in extending product life cycles through practices such as sharing, leasing, and recycling. It details the functionalities of a deep learning toolkit developed within the project, which assists in data collection, model definition, and validation for predictive maintenance applications. The toolkit is designed to analyze machine conditions, predict failures, and optimize maintenance schedules, thereby reducing waste and enhancing productivity. The document also presents a pilot case study involving data collected from a shipyard in Spain, illustrating the practical application of the toolkit in a real-world manufacturing environment. The findings emphasize the role of AI in improving maintenance strategies and promoting sustainability in industrial practices.