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Ph.D. / Definitions of sustainable development can be grouped according to their ideological orientation and economic paradigm in which they are placed: neoclassical; social and ecological modernisation of neoclassical; and radical. The view of sustainable development predominant in the mining sector aligns with the dominant neoclassical economic paradigm. It is revealed specifically through the system of metrics used, the most obvious of which is profit, shareholder value, and growth. The idea of sustainability is understood in mining as the need to respond to increasing regulation by adding two extra dimensions to the economic one – social and environmental. This is abbreviated as the triple bottom line, or weak sustainability. In the exercise of process stewardship, mines tend to follow global responsibility guidelines formulated for the sector, but product stewardship is of secondary importance. Narrow definitions of sustainability fail to take into account the biosphere as a complex adaptive system. In this study there is a discussion about an innovative collaborative sustainability model to be developed in a new industrial sector. That sector would operate beyond mining, while at the same time using mining waste residues feedstock as its inputs. The landscape in which the new sector would be located would be the current neoclassical one, but the model has been formulated as a tool to move towards a broader conception of sustainability. As a means of clarifying the fuzzy boundaries between the various entities and components of the complex adaptive system of the biosphere, for the purposes of discussion, the biosphere has been divided into seven separate schematic dimensions (after Gell-Mann, 1994: 345-366). These are ideological, institutional, economic, social, demographic, informational and technological. Six research and development projects, carried out over seven years (2002 to 2009) in a research and development group of a trans-national mining corporation, were directed by the author. These projects, in the fields of improved air quality and of minimisation of mining waste residues, formed the basis for conceptualising a new collaborative sustainability model. The projects, when placed in the context of seven dimensions of the biosphere and as examples of sustainable development, reveal themselves as falling far short of attaining sustainability goals. What a reductionist definition of sustainability used in the mining industry means is that the industry is slow at anticipating needs of communities after a mine closes, or after organisational restructuring and downsizing in the trans-national corporation has happened, or in dealing with the influx of people into the area who come to improve their economic/political opportunities. The implementation of sustainability principles in mines is directed by global protocols, directives and regulatory obligations, and is driven by the market economy.

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering. Johannesburg, 2017 / The primary objective of any mining business unit is to make profit by extracting, processing and selling minerals from a particular mineral deposit. It is important to optimise the extraction of the mineral resource given time, space and resource constraints. The mineral extraction process is often associated with uncertainty due to variable technical and human factors. Technical factors such as grade distribution, ground conditions and equipment reliability influence the performance of the mining production system (MPS). The performance of the MPS is also impacted by human factors such as employee skills, health and attendance. Uncertainty associated with technical and human factors often leads to planned output being different to actuals obtained. Therefore an in-depth analysis of the significant causes of deviations from the planned outcomes becomes a very important exercise. This research investigated the empirical relationships between inputs and outputs in a MPS in order assist management in directing efforts at key production drivers. A literature review revealed that production output is an end result of a chain of processes dependent and directly linked to each other, often referred to as the Mining Value Chain. The processes can be seen as milestones to be achieved within a production project. The process requires technical and human factors as resources. The literature review also highlighted that the production stage is the most obvious stage for investors to realise their return on investment. The production stage which constitutes a MPS was chosen as a relevant research area for the reason mentioned. Once a MPS has been empirically characterised, more effort and resources can be focused on the key decision making variables (DMVs) in order to meet the planned outcomes. A production function was developed accordingly, based on the production logic and historical data. The research concludes that for a typical platinum mine the face advance, face length mined, number of teams, and team size (independent variables) have a statistically significant relationship with the centares (m²) (dependent variable / response variable) produced which is a key performance indicator (KPI) for a platinum mine. A statistically significant regression equation with a coefficient of determination R2 = 0.99835 was obtained for the MPS. The production function can be used to align the physical, technical and human factors together to predict the optimal output level. The production function also highlights that the most significant production lever of the MPS is the face advance, contrary to a commonly held sentiment that lost blasts are the most significant. / MT 2017

This thesis describes preliminary research on the application of Markov Decision Processes (MDPs) to the optimisation of mine scheduling in an uncertain environment. The MDP framework is a novel approach to scheduling in a mining operation and option valuation. The task of scheduling in mining operations is dependent on the availability of models that permit the representation of some of the key stochastic properties of the environment, such as grade and price uncertainty. The tools used to model these processes are respectively sequential Gaussian simulation and Geometric Brownian motion. Three cases of increasing size are used to illustrate the results of the model and demonstrate its suitability to mine scheduling and option valuation. The computational efficiencies of solving an MDP formulation by Policy Iteration and Value Iteration are compared. The impact of the discount rate on the optimal policy is assessed. To determine the value of one or several options, an optimal policy without options is generated and valued. Then, the exercise is repeated with the relevant options to value (e.g., production rate, cut-off grade and time of mine closure). By comparing the values obtained in both cases, the financial benefit of having operational flexibility is determined, thus yielding the option value. A full size case study is conducted to validate the applicability of MDPs to real mining projects.

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