Evaluation of methods for stope design in mining and potential of improvement by pre-investigations

The importance of stope design for mine planning is considerable. Therefore, stope design and its challenges have been in the focus of research for the past 50 years. Empirical, numerical and analytical methods for stope design have been developed over the past decades in order to improve this process. This thesis is assessing which areas for improvement there still are and which problems are still only unsatisfactorily solved. After establishing background knowledge about the importance of stope design for mine planning and evaluating the factors influencing stope design, the focus is laid on the development of stope design methods in the past, as well as current research related to the topic, to create a comprehensive overview of recent and future developments. This is done by means of a literature review and research analysis. On the other side, the mining industry´s needs and challenges related to stope design are assessed, by means of survey, mine visit and interview. The insights gained in both parts are compared and checked for potential harmonies and disharmonies. Finally, from those conclusions practical recommendations for the GAGS-project are extracted and consecutively presented. In stope design research the focus and dominance of empirical methods has slowly shifted towards more research being conducted in the area of numerical and analytical methods. It can also be concluded that numerical methods and personal expertise are far more important for stope design within industry than commonly assumed. It was identified that in order to improve stope design, it is desired to increase the amount of geotechnical data acquired, the software improved, and stope design integrated within the general mine planning process. Additionally, interesting insights were gained by an in-depth analysis of survey responses, for example, the outstanding importance of the cut-off grade for stope design within gold mining operations. In order to allow for an optimal acceptance of novel geotechnical methods for stope design, the acquired data should be implementable into stope design within three days, preferably be compatible or implemented within a software and allow for stope design to be integrated into general mine planning. To promote the benefits a comprehensive scientific case-study demonstrating the realized benefits should be performed

A Review of Primary Mine Ventilation System Optimization

Within the mining industry, a safe and economical mine ventilation system is an essential component of all underground mines. In recent years, research scientists and engineers have explored operations research methods to assist in the design and safe operation of primary mine ventilation systems. The main objective of these studies is to develop algorithms to identify the primary mine ventilation systems that minimize the fan power costs, including their working performance. The principal task is to identify the number, location, and duty of fans and regulators for installation within a defined ventilation network to distribute the required fresh airflow at minimum cost. The successful implementation of these methods may produce a computational design tool to aid mine planning and ventilation engineers. This paper presents a review of the results of a series of recent research studies that have explored the use of mathematical methods to determine the optimum design of primary mine ventilation systems relative to fan power costs

Review of mathematical models for production planning under uncertainty due to lack of homogeneity: proposal of a conceptual model

[EN] Lack of homogeneity in the product (LHP) appears in some production processes that confer heterogeneity in the characteristics of the products obtained. Supply chains with this issue have to classify the product in different homogeneous subsets, whose quantity is uncertain during the production planning process. This paper proposes a generic framework for reviewing in a unified way the literature about production planning models dealing with LHP uncertainty. This analysis allows the identification of similarities among sectors to transfer solutions between them and gaps existing in the literature for further research. The results of the review show: (1) sectors affected by LHP inherent uncertainty, (2) the inherent LHP uncertainty types modelled, and (3) the approaches for modelling LHP uncertainty most widely employed. Finally, we suggest a conceptual model reflecting the aspects to be considered when modelling the production planning in sectors with LHP in an uncertain environment.This research was initiated within the framework of the project funded by the Ministerio de Economía y Competitividad [Ref. DPI2011-23597] entitled ‘Methods and models for operations planning and order management in supply chains characterised by uncertainty in production due to the lack of product uniformity’ (PLANGES-FHP) already finished. After, the project leading to this application has received funding from the European Union’s research and innovation programme under the H2020 Marie Skłodowska-Curie Actions with the grant agreement No 691249, Project entitled ’Enhancing and implementing Knowledge based ICT solutions within high Riskand Uncertain Conditions for Agriculture Production Systems’ (RUC-APS).Mundi, I.; Alemany Díaz, MDM.; Poler, R.; Fuertes-Miquel, VS. (2019). 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A decision support tool for the order promising process with product homogeneity requirements in hybrid Make-To-Stock and Make-To-Order environments. Application to a ceramic tile company. Computers & Industrial Engineering, 122, 219-234. doi:10.1016/j.cie.2018.05.040Alfalla-Luque, R., Medina-Lopez, C., & Dey, P. K. (2012). Supply chain integration framework using literature review. Production Planning & Control, 24(8-9), 800-817. doi:10.1080/09537287.2012.666870Al-Othman, W. B. E., Lababidi, H. M. S., Alatiqi, I. M., & Al-Shayji, K. (2008). Supply chain optimization of petroleum organization under uncertainty in market demands and prices. European Journal of Operational Research, 189(3), 822-840. doi:10.1016/j.ejor.2006.06.081Al-Shammari, A., & Ba-Shammakh, M. S. (2011). Uncertainty Analysis for Refinery Production Planning. Industrial & Engineering Chemistry Research, 50(11), 7065-7072. doi:10.1021/ie200313rAmaro, A. C. S., & Barbosa-Póvoa, A. P. F. D. (2009). 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Risk Management in the Oil Supply Chain: A CVaR Approach. Industrial & Engineering Chemistry Research, 49(7), 3286-3294. doi:10.1021/ie901265nChakraborty, M., & Chandra, M. K. (2005). Multicriteria decision making for optimal blending for beneficiation of coal: a fuzzy programming approach. Omega, 33(5), 413-418. doi:10.1016/j.omega.2004.07.005LUO, C., & RONG, G. (2009). A Strategy for the Integration of Production Planning and Scheduling in Refineries under Uncertainty. Chinese Journal of Chemical Engineering, 17(1), 113-127. doi:10.1016/s1004-9541(09)60042-2Davoli, G., Gallo, S., Collins, M., & Melloni, R. (2011). A stochastic simulation approach for production scheduling and investment planning in the tile industry. International Journal of Engineering, Science and Technology, 2(9). doi:10.4314/ijest.v2i9.64006Denizel, M., Ferguson, M., & Souza, G. (2010). Multiperiod Remanufacturing Planning With Uncertain Quality of Inputs. IEEE Transactions on Engineering Management, 57(3), 394-404. doi:10.1109/tem.2009.2024506Dong, M., Lu, S., & Han, S. (2011). Production Planning for Hybrid Remanufacturing and Manufacturing System with Component Recovery. Advances in Electrical Engineering and Electrical Machines, 511-518. doi:10.1007/978-3-642-25905-0_66Dubois, D., Fargier, H., & Fortemps, P. (2003). Fuzzy scheduling: Modelling flexible constraints vs. coping with incomplete knowledge. European Journal of Operational Research, 147(2), 231-252. doi:10.1016/s0377-2217(02)00558-1DUENYAS, I., & TSAI, C.-Y. (2000). Control of a manufacturing system with random product yield and downward substitutability. IIE Transactions, 32(9), 785-795. doi:10.1080/07408170008967438Esteso, A., Alemany, M. M. E., & Ortiz, A. (2018). Conceptual framework for designing agri-food supply chains under uncertainty by mathematical programming models. International Journal of Production Research, 56(13), 4418-4446. doi:10.1080/00207543.2018.1447706French, M. L., & LaForge, R. L. (2005). Closed-loop supply chains in process industries: An empirical study of producer re-use issues. Journal of Operations Management, 24(3), 271-286. doi:10.1016/j.jom.2004.07.012Gallo, M., R. Grisi, G. Guizzi, and E. Romano. 2009. “A Comparison of Production Policies in Remanufacturing Systems,” Proceedings of the 8th WSEAS International Conference on System Science and Simulation in Engineering, ICOSSSE ‘09, pp. 334.Goodfellow, R., & Dimitrakopoulos, R. (2017). Simultaneous Stochastic Optimization of Mining Complexes and Mineral Value Chains. Mathematical Geosciences, 49(3), 341-360. doi:10.1007/s11004-017-9680-3Graves, S. C. (2010). Uncertainty and Production Planning. Planning Production and Inventories in the Extended Enterprise, 83-101. doi:10.1007/978-1-4419-6485-4_5Grillo, H., Alemany, M. M. E., Ortiz, A., & Fuertes-Miquel, V. S. (2017). Mathematical modelling of the order-promising process for fruit supply chains considering the perishability and subtypes of products. Applied Mathematical Modelling, 49, 255-278. doi:10.1016/j.apm.2017.04.037Guan, Z., & Philpott, A. B. (2011). A multistage stochastic programming model for the New Zealand dairy industry. International Journal of Production Economics, 134(2), 289-299. doi:10.1016/j.ijpe.2009.11.003Guide, V. D. R. (2000). Production planning and control for remanufacturing: industry practice and research needs. Journal of Operations Management, 18(4), 467-483. doi:10.1016/s0272-6963(00)00034-6Gupta, V., & Grossmann, I. E. (2011). Solution strategies for multistage stochastic programming with endogenous uncertainties. Computers & Chemical Engineering, 35(11), 2235-2247. doi:10.1016/j.compchemeng.2010.11.013Gupta, S., and Z. Nan. 2006. “‘Multiperiod Planning of Refinery Operations Under Market Uncertainty,’ AIChE Annual Meeting.” Conference Proceedings.Heckmann, I., Comes, T., & Nickel, S. (2015). A critical review on supply chain risk – Definition, measure and modeling. Omega, 52, 119-132. doi:10.1016/j.omega.2014.10.004Heydari, J., & Ghasemi, M. (2018). A revenue sharing contract for reverse supply chain coordination under stochastic quality of returned products and uncertain remanufacturing capacity. Journal of Cleaner Production, 197, 607-615. doi:10.1016/j.jclepro.2018.06.206Hovelaque, V., Duvaleix-Tréguer, S., & Cordier, J. (2009). Effects of constrained supply and price contracts on agricultural cooperatives. European Journal of Operational Research, 199(3), 769-780. doi:10.1016/j.ejor.2008.08.005Hsieh, S., & Chiang, C.-C. (2001). Manufacturing-to-Sale Planning Model for Fuel Oil Production. The International Journal of Advanced Manufacturing Technology, 18(4), 303-311. doi:10.1007/s001700170070Igarashi, M., de Boer, L., & Fet, A. M. (2013). What is required for greener supplier selection? A literature review and conceptual model development. Journal of Purchasing and Supply Management, 19(4), 247-263. doi:10.1016/j.pursup.2013.06.001Jamshidi, M., & Osanloo, M. (2019). Reliability analysis of production schedule in multi-element deposits under grade-tonnage uncertainty with multi-destinations for the run of mine material. International Journal of Mining Science and Technology, 29(3), 483-489. doi:10.1016/j.ijmst.2018.04.016Jin, X., Hu, S. J., Ni, J., & Xiao, G. (2013). Assembly Strategies for Remanufacturing Systems With Variable Quality Returns. IEEE Transactions on Automation Science and Engineering, 10(1), 76-85. doi:10.1109/tase.2012.2217741Jindal, A., & Sangwan, K. S. (2016). Multi-objective fuzzy mathematical modelling of closed-loop supply chain considering economical and environmental factors. Annals of Operations Research, 257(1-2), 95-120. doi:10.1007/s10479-016-2219-zJohnson, P., G. Evatt, P. Duck, and S. Howell. 2010. “The Derivation and Impact of an Optimal Cut-off Grade Regime Upon Mine Valuations,” Proceedings of the World Congress on Engineering 2010 Vol I.Junior, M. L., & Filho, M. G. (2011). Production planning and control for remanufacturing: literature review and analysis. Production Planning & Control, 23(6), 419-435. doi:10.1080/09537287.2011.561815Kamrad, B., & Ernst, R. (2001). An Economic Model for Evaluating Mining and Manufacturing Ventures with Output Yield Uncertainty. Operations Research, 49(5), 690-699. doi:10.1287/opre.49.5.690.10610Kannegiesser, M., Günther, H.-O., van Beek, P., Grunow, M., & Habla, C. (2008). Value chain management for commodities: a case study from the chemical industry. OR Spectrum, 31(1), 63-93. doi:10.1007/s00291-008-0124-9Karabuk, S. (2008). Production planning under uncertainty in textile manufacturing. Journal of the Operational Research Society, 59(4), 510-520. doi:10.1057/palgrave.jors.2602370Khor, C. S., Elkamel, A., & Douglas, P. L. (2008). Stochastic Refinery Planning with Risk Management. Petroleum Science and Technology, 26(14), 1726-1740. doi:10.1080/10916460701287813Kumral, M. (2004). Genetic algorithms for optimization of a mine system under uncertainty. Production Planning & Control, 15(1), 34-41. doi:10.1080/09537280310001654844Lalmazloumian, M., and K. Y. Wong. 2012. “A Review of Modelling Approaches for Supply Chain Planning Under Uncertainty,” Service Systems and Service Management (ICSSSM), 2012 9th International Conference on, pp. 197.Leiras, A., Ribas, G., Hamacher, S., & Elkamel, A. (2013). Tactical and Operational Planning of Multirefinery Networks under Uncertainty: An Iterative Integration Approach. 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Sound mining in the North : a guide to environmental regulation and best practices supporting social sustainability

Julkaistu versi

Adapting to climate risks and extreme weather: guide for mining - minerals industry professionals

AbstractExtreme weather events in Australia over recent years have highlighted the costs for Australian mining and mineral processing operations of being under-prepared for adapting to climate risk. For example, the 2010/2011 Queensland floods closed or restricted production of about forty out of Queensland’s fifty coal mines costing more than $2 billion in lost production.Whilst mining and mineral professionals have experience with risk management and managing workplace health and safety, changes to patterns of extreme weather events and future climate impacts are unpredictable. Responding to these challenges requires planning and preparation for events that many people have never experienced before. With increasing investor and public concern for the impact of such events, this guide is aimed at assisting a wide range of mining and mineral industry professionals to incorporate planning and management of extreme weather events and impacts from climate change into pre-development, development and construction, mining and processing operations and post-mining phases. The guide should be read in conjunction with the research  final report which describes the research process for developing the guide and reflects on challenges and lessons for adaptation research from the project.The Institute for Sustainable Futures, University of Technology Sydney (UTS) led the development of the guide with input from the Centre for Mined Land Rehabilitation, University of Queensland and a Steering Committee from the Australasian Institute of Mining and Metallurgy’s Sustainability Committee and individual AusIMM members, who volunteered their time and experience. As the situation of every mining and mineral production operation is going to be different, this guide has been designed to provide general information about the nature of extreme weather events, and some specific examples of how unexpectedly severe flooding, storm, drought, high temperature and bushfire events have affected mining and mineral processing operations. A number of case studies used throughout the guide also illustrate the ways forward thinking operations have tackled dramatically changing climatic conditions.Each section of the guide outlines a range of direct and indirect impacts from a different type of extreme weather, and provides a starting point for identifying potential risks and adaptation options that can be applied in different situations. The impacts and adaptation sections provide guidance on putting the key steps into practice by detailing specific case examples of leading practice and how a risk management approach can be linked to adaptive planning. More information about specific aspects of extreme weather, planning and preparation for the risks presented by these events, and tools for undertaking climate related adaptation is provided in the ‘Additional Resources’ section

Alaska-Canada Rail Link Economic Benefits

Construction of the 1,740 km Alaska-Canada Rail Link (ACRL) between Fort Nelson, BC and Delta Junction, Alaska to join the North American rail system to the Alaska Railroad will result in tremendous economic benefits for Canada and the US. The ACRL will provide valuable additional east-west rail capacity and tidewater access to the Pacific, hugely benefitting not only the Yukon and Eastern Alaska regions, into which it will introduce rail transport for the first time, but throughout both countries. The economic benefits of ACRL construction are consistent with Canadian government’s desire to promote Northern development and comparable in significance to those of Canadian Pacific Railway in the 1880’s and the St. Lawrence Seaway in the 1950’s. Construction of the ACRL alone will bring unprecedented economic stimulus to the region in terms of job creation, wages and income tax revenue over multiple years. Table 7-1 below summarizes the benefits from ACRL construction for the Yukon, BC and Canada as a whole. However, these estimates are conservative as they exclude benefits associated with pre-construction activities, railway operation post-construction, sales taxes and corporate taxes as well as all such benefits that will accrue to Alaska and the US

Sustainable mining, local communities and environmental regulation

Sustainable mining is an objective as well as a tool for balancing economic, social, and environmental considerations. Each of these three dimensions of mining – and sustainable development – has many components, some of which were chosen for closer study in the SUMILCERE project. While there is no single component that in itself provides a definitive argument for or against sustainable mining, the research reveals some that have proven valuable in the process of balancing the different dimensions of sustainability. In the SUMILCERE project, comparative studies enabled us to identify factors such as the following, which are essential when discussing the balancing in practice of the three dimensions of sustainable mining cited above: the framework and functionality of environmental regulation to protect the environment (environmental sustainability); the competitiveness of the mining industry in light of environmental regulation and its enforcement (economic sustainability); public participation and the opportunities local communities have to influence their surroundings, as well as communities’ acceptance of projects (social sustainability) before and during operations; and the protection of Sámi cultural rights in mining projects (social and cultural sustainability). Although each of the three dimensions of sustainability leaves room for discretion in the weight assigned to it, ecological sustainability, protected by smart environmental regulation and minimum standards, sets essential boundaries that leave no room for compromises. Economic and social sustainability are possible only within these limits. Details of the analyses in the Kolarctic area and accounts of the methods used can be found in the cited SUMILCERE articles.publishedVersio

The right to mine? Discourse analysis of social impact assessments of mining projects in Finnish Lapland in the 2000s

Lapland, the northernmost county of Finland, has promising mineral deposits and over half of all Finnish mining operations. In the 2000s two new metallic mineral mines were opened in Lapland, while three projects are undergoing the environmental impact assessment procedure (EIA). This process also involves a social impact assessment (SIA) that reports on the expected impacts of mining on the host communities. SIAs influence the permit process and the ensuing activity and officially represent the views of the local people in the planning and decision-making process. In this study, social impact assessments are examined by discourse analysis introduced by Maarten Hajer. The document analysis identified three recurrent story lines shared by all the investigated SIAs. A story line combines elements from different domains and suggests a common understanding on an issue. The second phase of the discourse analysis was to analyse these story lines in the context they were produced. The first story line sees mines as the only way to develop the remote regions of Lapland. Large-scale mining projects are seen as a solution to economic problems, unemployment and out-migration. The second story line stresses the importance of mines in supporting the “general interest” of the whole province. After the Second World War, the intensive use of natural resources was justified by national interests; now it is justified by the interests of the region. The third story line argues that nature has no intrinsic value – it is merely a resource to be used. With the help of such story lines, SIAs grant the right to mine in Lapland.publishedVersio