Statistical Process Control

Statistical Process Control (SPC) focuses on monitoring and controlling processes to ensure consistent quality and performance, adapting traditional methods to address challenges in diverse fields. Current research emphasizes applying SPC to complex systems like machine learning models and robotic process automation, utilizing techniques such as multivariate control charts, convolutional neural networks, and federated learning to enhance detection of anomalies and data drift. This work is significant for improving the reliability and safety of AI-driven systems in healthcare, manufacturing, and finance, as well as for optimizing the efficiency and maintainability of automated processes.