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Journal of the Southern African Institute of Mining and Metallurgy
versión On-line ISSN 2411-9717
versión impresa ISSN 2225-6253
Resumen
PETIT, P.J.. Business optimization for platinum mining projects and operations. J. S. Afr. Inst. Min. Metall. [online]. 2016, vol.116, n.2, pp.123-130. ISSN 2411-9717. http://dx.doi.org/10.17159/2411-9717/2016/v116n2a3.
The complex planning required to achieve any planned production yields multiple and dissociated responses over the life of project (LOP). The customary decision-making process negates the possibilities of developing optimized and integral solutions from operating levels up to business and strategic levels. This results in an inefficient project or overall underperformance of the operation. In the project setting, disconnected trade-offs and improved performance studies become inadequate, because they are site-specific and use only a few comparative parameters. They are often based on a small data-set. Decisions taken to achieve overall objectives require the correct determination and dissemination of key performance indicators (KPIs). The KPIs indicate efficiency in operation, whereby the marginal rate of technical substitution corresponds to the rate of production. It is the necessary condition for optimization. Performance realization for sustain-ability follows optimization modelling, the latter often being presented with financial results such as business net present value (NPV). It considers techno-financial constraints and provides a strategic and aligned outlook of KPI decisions for an enhanced and integrated outcome. This paper explains a mining case study that is rendered efficient, and through business optimization (BO) short-term and sustainable targets are reached. Business optimization increases the NPV by 14.7%. This is achieved by challenging conventional decision-making associated with maximizing business value by including environmental externalities within the LOP.
Palabras clave : business optimization; key performance indicators; valuation methodologies; multiple-criteria decision-making (MCDM); analytical hierarchical process (AHP); environmental externalities.