Nooshin Salehabadi

A machine learning-driven approach to optimizing maintenance scheduling for industrial machinery

An integrated framework combining supervised machine learning classification with mathematical optimization to predict equipment failures and minimise maintenance costs under prediction uncertainty is developed, ensuring prediction uncertainty propagates into scheduling decisions and bridging predictive analytics with...