W Scott Dunbar
Relevant Degree Programs
Graduate Student Supervision
Doctoral Student Supervision (Jan 2008 - Mar 2019)
From transportation to infrastructure, from energy to information technology, mining makes a significant contribution to society. It also impacts the lives of millions of people living in regions where mining occurs. Today, an increasing number of individuals and groups have earned a legitimate right to be considered as stakeholders in projects affecting their communities. This has given rise to mining-community conflict and is forcing companies to reconsider the approach to earning and retaining social approval. Global mining leaders have been working to implement policies and practices aligned with corporate social responsibility (CSR) tenets yet conflict between mining companies and the communities that host extractive operations appears to be growing.This research seeks to quantify incidents of mining-community conflict and test a theory that reframing CSR to create shared value could deliver financial returns to mining operations while advancing economic and social conditions in associated communities. It is suggested that the UN 2030 Sustainable Development Goals (SDGs) provide a context for reframing CSR as a strategic business imperative. A new model of engagement is proposed that places the SDGs at the centre of mining-community engagement to align mining with the values of society and rebuild the sector’s current trust deficit.A multi-method research approach is used. The quantitative portion analyzes mining community conflicts from 2012 – 2015 as reported in the international media. Media coverage was hand-coded using a system adapted from conflict literature, and a document analysis of a sub-set of the conflict situations was employed to explore the results. A qualitative, theory-building case study investigates collaboration between personnel at the Cerro Verde Mine and regional stakeholders to address regional water supply issues and develop a strategy with parallel goals: improving operational performance while delivering tangible social benefits. The research seeks to contributes to CSR as a management strategy. The findings confirm there is both monetary and reputational value to investing in core social needs that intersect with business interests. A new model to build trust in mining and advance progress on the SDGs is proposed, and a concept presented that places CSR approaches within life-of-mine stages.
Mass caving systems require significant capital expenditure and long-term commitment of resources before production commences. Cave mining projects are confronted with numerous challenges in maintaining their construction schedule expectations. Any delay in construction impacts on the production schedule and, in turn, reduces the project value. In order to increase the expected economic value, the construction schedule needs to be accelerated through strategic flexibilities. It is hypothesized that construction acceleration (crashing) can be achieved by prioritizing the construction schedule or changing the construction strategy. This thesis seeks to expand current knowledge on three interrelated domains for decision making in engineering systems—(i) recognition, (ii) modeling and (iii) pricing of flexibility in cave mining construction. An objective of this study was to provide state-of-the-art project formulation techniques employed in planning that can be used to support decision-making processes in cave mining systems. The first domain requires identifying construction strategies that allow the mine management to implement construction crashing in multiple heading development. Three independent and interrelated flexibilities are considered. The second domain requires development of a methodology suitable for investigating and forecasting through modeling the development and construction rates enabling implementation of flexible strategies. A method capable of modeling the development and construction processes with respect to the advance undercut mining strategy is developed, which integrates the geotechnical and equipment-related uncertainties, using the framework of discrete event simulation. Several models are developed to investigate the impact of implementing these flexibilities on the development and construction rates. The results from the flexible models compared to the benchmark models confirmed that significant construction benefits can be achieved. The third domain requires development of an algorithm suitable for evaluating the cost of implementing a construction crashing option that can accommodate delays. A method that is able to respond to schedule uncertainties in construction projects by incorporating the decision-making strategy of project crashing into the budget, including the cost contingency valuation, is developed using the framework of real options and Monte Carlo simulation from a contractor’s perspective. The results indicated that significant change in costs stems from the variation in risk perceptions and confidence levels.
Master's Student Supervision (2010-2017)
Artisanal and small-scale mining (ASM) is a poverty driven activity in many developing countries, associated with environmental and social degradation such as acid rock drainage, soil erosion, child labour, gambling, prostitution, alcoholism and social instability due to worker migration (Veiga et al., 2014a). Although ASM is an informal and illegal activity, it has been tolerated in developing countries because of its significant economic role in poverty reduction. Indeed, it has been estimated that about 100 million people across developing countries depend on artisanal mining for their livelihoods (World Bank, 2013) and Burkina Faso (located in West Africa) as a developing country is not spared the environment and socio-economic impacts related to ASM.The objectives of the model developed in this study are to mitigate the environmental impacts of artisanal mining while enhancing its socio-economic benefits. The developed model is based on the theory of an economic growth pole (EGP) and its concepts of inter-industry linkage, external economies, and agglomeration. This approach has found success in better and sustainable organization of the agricultural sector in Burkina Faso, where most of the small farmers were previously left alone to produce food without tools, proper regulation, finance and land titles. In this study, the economic and environmental factors affecting artisanal mining have been defined and analysed in order to apply them to the EGP model.The starting EGP model suggests that first a clean processing plant is required to generate sustainable growth, followed by a working organization to centralize activities and ensure better growth distribution for stakeholders (investors, miners, national authorities). As a theoretical approach toward the artisanal mining sector, there are no previous cases of the application of an economic growth pole. Therefore, this study discusses the feasibility of the model and its ability to tackle the impacts of artisanal mining. Importantly, the model tries to tackle the issues in artisanal mining by removing the financial restrictions for implementation of technological services at artisanal mining sites, and by providing a working organization for better distribution of revenues from technological service and for controlling the impacts of processing on the environment and health.
There is limited research on the topic of outsourcing in the mining industry. The purpose of the study is to fill this gap and gain a general understanding of the state of outsourcing in the mining industry. The study seeks to answer basic questions such as how prevalent is outsourcing, what activities are being outsourced and why they are outsourcing. Upon surveying the upper management (e.g. CEOs and COOs) of 106 primarily Canadian mining companies with global operations, it became evident that outsourcing is widespread among both juniors and large mining companies. Some 89.7% of mining companies outsource or have outsourced in the past. Mining companies outsource mining more than mineral processing because mineral processing is a revenue generator and require large investments, which outsourcing suppliers generally do not have. Other popular activities for outsourcing include construction during mining operations. The biggest reason for outsourcing is access to specialized competencies, including skilled labour, followed by flexibility such adapting to seasonality, changes in geology and commodity prices. According to the criteria created by Quinn and Hilmer (1994), mining and mineral processing are not core competencies for mining companies and should be evaluated carefully for outsourcing although some 92.1% of mining companies perceive these activities as being core competencies. The seven traits of core competency put forward by Quinn and Hilmer were that they are: based on skills and intellectual property in the company; create flexibility; one of the top three capabilities of the company; fills a gap in the industry; performed better than providers; shareholders/customers care about them; and embedded in company processes. None of the traits reached the 92.1% agreement (to match the mining companies’ perception) necessary to be a core competency and therefore, mining and mineral processing are not core competencies for mining companies.
The full abstract for this thesis is available in the body of the thesis, and will be available when the embargo expires.
The application of geostatistics to strongly skewed data has always been problematic. The ordinary geostatistical methods cannot deal with highly skewed data very well. Multi-Indicator methods are potential candidates for the interpolation of this type of datasets, but the workload associated with them is sometimes intimidating. In this study, six geostatistical estimators, namely, ordinary kriging, simple kriging, universal kriging, trend-only kriging, lognormal kriging and indicator kriging, as well as two deterministic estimating techniques – inverse distance weighted and nearest neighbor – were applied to a highly negatively skewed RQD dataset to determine which one is more appropriate for interpolating a geotechnical model, based on their summary statistics. Universal kriging was identified to be the best method, with the trend being modeled by a quadratic drift item and the residual being estimated with simple kriging. Two simulators – sequential Gaussian and sequential indicator – were applied in this thesis for the purpose of identifying the probabilistic distribution at each location and joint-distribution for multiple locations. A transfer function was defined to transform each of the realizations to a single conceptual cost value for the sake of risk analysis, based on the relation between RQD and tunnel support specifications summarized by Merritt (1972). The distribution of the cost values corresponding to all of the realizations are quasi-normal and no estimators except KT produced a cost value that was less than two standard deviations away from the mean, once again proving the smoothing effect of all linear weighted estimators. If high values account for a dominant percentage in the sample dataset, the estimated RQD models are likely to be over-pessimistic compared with their simulated counterparts. GSLIB was used in this thesis, which in its original form does not impose a limit on the maximum number of samples coming from the same borehole when performing either estimation or simulation. It is recommended to customize the source code of GSLIB to implement this constraint to check what effect it would have on the results, if some commercial FORTRAN compiler can be made handy.