A novel data reconciliation and gross error detection tool for the mineral processing industry

This paper describes a data reconciliation and gross error detection software (RAGE) to convert raw data into useful plant information for performance analysis, process control and circuit optimization. The conventional data reconcillation tools used in mineral processing industries generally focus on solid and component balances. RAGE uses Successive Quadratic Programming for data reconciliation and Generalized Likelihood Ratio Test with serial compensation technique for gross error detection. The software not only focuses on solid and component balances but also gives liquid balance across the entire circuit.