Multivariate Specifications in the Mineral Processing Field: An introduction

Abstract

The concept of multivariate specifications on incoming raw material was introduced in the mid-1990s in the chemical process industry as a tool to determine if a lot should be accepted from a supplier prior to its purchase. The objective of this paper is to adapt this concept to the mineral processing field using a simulation case study to assess the profitability of processing ore with different characteristics. To keep it simple, only the ore properties are considered to influence the final quality attributes: the concentrate flow rate and grade. Defining multivariate specification regions for raw ore properties is illustrated using simulated data from a grinding-flotation process where the feed ore average mineral grain size, grade and hardness are modified. This involves defining process performance classes based on an economic criterion, building a projection to latent structure PLS model, and adjusting statistical limits in the latent space of the model (i.e. the specification). The resulting specification region in the latent space based on a linear discriminant classifier allows to correctly classify 91% of the lots of ore in terms of their profitability.