Degradation Prediction

Degradation prediction focuses on accurately estimating the remaining lifespan or performance of a system based on observed data, aiming to optimize maintenance and prevent failures. Current research emphasizes leveraging advanced machine learning models, including deep learning architectures like variational autoencoders, transformers, and recurrent neural networks, often incorporating techniques like graph neural networks for spatio-temporal data analysis and diffusion models for image-based degradation. These methods are applied across diverse domains, from semiconductor lasers and photovoltaic systems to organic solar cells and image processing, improving predictive accuracy and enabling more efficient resource management and cost savings.