Knowledge Formalisation for Hydrometallurgical Gold Ore Processing

Abstract

This paper describes an approach to externalising and formalising expert knowledge involved in the design and evaluation of hydrometallurgical process chains for gold ore treatment. The objective of this knowledge formalisation effort is to create a case-based reasoning application for recommending a treatment process of gold ores. We describe a twofold approach to formalise the necessary knowledge. First, formalising human expert knowledge about gold mining situations enables the retrieval of similar mining contexts and respective process chains, based on prospection data gathered from a potential gold mining site. The second aspect of our approach formalises empirical knowledge on hydrometallurgical treatments. The latter, not described in this paper, will enable us to evaluate and, where needed, redesign the process chain that was recommended by the first aspect of our approach. The main problems with the formalisation of knowledge in the gold ore refinement domain are the diversity and the amount of parameters used in literature and by experts to describe a mining context. We demonstrate how similarity knowledge was used to formalise literature knowledge. The evaluation of data gathered from experiments with an initial prototype workflow recommender, Auric Adviser, provides promising results.