LAUSR

Abstract The integration of technologies across the mining value chain is becoming critical, and it is crucial to identify the best possible technologies applicable to an operation, based on the chosen criteria. This study investigates the adoptable technologies for a mining project, develops a conceptual framework for the analytical process and validates the framework using a hypothetical case study. The case study comprised of a technology decision problem, the result of which consisted of six technology alternatives, four criteria, and one decision maker. Of the several Multi-Criterial Decision Making (MCDM) techniques available, the fusion of the analytic hierarchy process (AHP) and preference ranking organisation method of enrichment (PROMETHEE) techniques were used for this study. The AHP was used to determine the hierarchal weight of each decision-making criterion and its consistency, while the PROMETHEE method was used to carry out the overall process evaluation. Additionally, the fuzzy set theory was infused into the hierarchical structure analysis to evaluate the quantitative economic criterion to curb uncertainty and imprecision. The results of the analysis show that the technology alternative A3 – Artificial Intelligence (AI) – is the most preferred alternative, which outranks other comparative technologies. The approach proposed in this study can help provide the basis for any technology adopting mining company to build its technology business case, strategy and or roadmap to achieve the desired outcome.