Development of a process selection method for gold ores using case-based reasoning

Lotta Rintala

    Research output: ThesisDoctoral ThesisCollection of Articles

    Abstract

    The ore grade, the geometry of an orebody as well as the mineralogical properties of the ore determine process selection for gold extraction. These factors have an effect on the metallurgical response of an ore to a proposed treatment scheme. The uniqueness of each ore deposit is the main challenge in the extraction process development for any ore. The mineralogical mode of occurrence of gold, gold grain size distribution, host and gangue mineral type, mineral associations and alterations all vary. There may be variations in these even within a single deposit, or with time. The research on gold extraction and reaction chemistry of gold is an active research area, even though many of the processes used for gold extraction today are based on techniques that have been known for centuries. Therefore, the amount of knowledge in the form of journal articles and industry reports concerning the processing of gold ores is large and increasing continuously. Typically experimental work is the most time consuming and expensive part of process design. Hence systematic utilisation of these knowledge sources helps to select experiments more precisely and shorten the development time of new process technology. In this thesis, a procedure for externalising and formalising knowledge from public sources regarding the hydrometallurgical gold extraction processes was created. Next, a framework for a case-based reasoning (CBR) system for the systematic utilisation of these knowledge sources in the development of hydrometallurgical gold extraction processes was produced. The quality of the public knowledge sources concerning the gold extraction processes and geological deposit information was analysed. These sources were found to be suitable for the planned CBR system. An open source tool, myCBR 3.0, was used in this study. Part of the tool, myCBR Workbench, was used for modelling. Nine attributes that represented parameters to be determined to understand gold ore-processing requirements were modelled and a case base consisting of 25 cases was constructed for Knowledge model I. This model was evaluated by using hypothetical queries and queries that were based on existing processes. The evaluation results of the Knowledge model I showed that the system works and it is able to find raw materials that have fairly similar process flowsheets from the case base compared with the queries. Furthermore, the results showed that the developed system is also able to retrieve relevant cases when queries are formed based on the ore descriptions of the existing processes. In addition to these results, myCBR Workbench was found suitable for the knowledge modelling of the hydrometallurgical gold extraction processes and it worked in general as intended.
    Translated title of the contributionProsessin valintamenetelmän kehittäminen kultamalmeille tapauspäättelyn avulla
    Original languageEnglish
    QualificationDoctor's degree
    Awarding Institution
    • Aalto University
    Supervisors/Advisors
    • Forsen, Olof, Supervising Professor
    • Aromaa, Jari, Thesis Advisor
    • Roth-Berghofer, Thomas, Thesis Advisor, External person
    Publisher
    Print ISBNs978-952-60-6483-3
    Electronic ISBNs978-952-60-6484-0
    Publication statusPublished - 2015
    MoE publication typeG5 Doctoral dissertation (article)

    Keywords

    • hydrometallurgy
    • case-based reasoning
    • gold ore
    • process development

    Fingerprint Dive into the research topics of 'Development of a process selection method for gold ores using case-based reasoning'. Together they form a unique fingerprint.

    Cite this