Process control in mining industries using Partial Least Square Regression (PLSR) on XRD raw data

摘要

Quantitative phase analysis using X-ray diffraction (XRD) became a standard tool for process optimization and quality control in industrial environments such as mining or metals production. Common methods such as full pattern Rietveld quantification use structural methods to extract/predict information from the full pattern using physical models and fitting techniques. Sometimes this approach is stretched to its limits. That usually happens, when no realistic physical model is available, or when the model is either too complex or doesn't fit to reality. In such cases there is one very elegant way out: multivariate statistics and Partial Least-Squares Regression, a method that does not require pure phases, crystal structures or complex modelling of peak shapes.This paper will describe the advantages of using PLSR for the determination of process parameters in mining industries. Three case studies from heavy mineral-, aluminium- and iron processing will be demonstrated.