Data mining, mining data: energy consumption modelling


As increasingly more data tracking production and business processes continue to be collected, mines are facing a problem seen in other businesses: being data-rich while information-poor. As additional efforts and technology are placed at developing even more information sources, a new technological focus should emerge: how to concentrate data into information; analyze information sufficiently to become knowledge; and finally, act on that knowledge (data®information®knowledge®action). New technologies, developed in non-mining industries, have begun to redress some of these data-rich–information-poor issues, specifically data warehousing (the enabling technology) and data mining (the analytical technology). An approach to develop applications and skills, wherein data is transformed into action, continues to be performed and tested at the Mining Information Systems and Operations Management (MISOM) lab at the University of Arizona. The data-to-action approach was exercised in the development of an energy consumption model (ECM), in partnership with a major US-based copper mining company, two software companies, and the MISOM lab, funded by the U.S. Department of Energy (DOE). The project, called Infrastructure for Integrated Data Environments and Analysis(IIDEA) for Mining and Processing Systems, began as a oneyear pilot study that used a copy of the 1.2 Terabyte corporatedata warehouse containing all records from every major information system (IS) used at all the operations of the partner mining company.
The data-to-action approach begins by integrating several key data sources using data warehousing techniques, namely the highly granular fleet management system (FMS, namely Dispatch®) and all cost transactions for the past four years from the enterprise system (ES, namely Ellipse®). The project began by increasing the existing level of integration and data cleaning. The information step involved the creation of online analytical processing (OLAP) cubes to investigate the data and identify a subset of several million records. Data mining algorithms, mostly neural-network based, were applied using the information that was isolated by the OLAP cube. The data mining results showed that traditional cost drivers of energy consumption, namely tons and distance for diesel, and tons for kWhrs, are poor predictors. A comparison was made between the traditional means on predicting energy consumption and the prediction formed using data mining. Traditionally, in the mines for which data were available, monthly averages of tons and distance are used to predict diesel fuel consumption. New information technology can be used to incorporate many more variables into the budgeting process, whereby far more accurate predictions can be made. The figure shows the predicted (using NN) versus actual using neural networking and includes other variables such as distance travelled up or down, time of year, and truck class, predicted by week. The data mining results are far closer to actual than when using traditional means of prediction. The final step in evolving data into action is using the newly created knowledge. The most valuable knowledge will not generate real value unless it is acted upon. Other business sectors were transformed by IT only once workflows were re-engineered to take advantage of the new capabilities. The project undertook a deliberate work and data-flow mapping of the budgeting process at the mines under study.An idealized workflow was then engineered considering data availability, technical skills of the local personnel, and cultural considerations. The ECM was developed to help mine planners improve the prediction of energy use in the materials handling system.
Business management processes, such as improvement initiatives and mine engineering, can be greatly improved through more data integration, measure development, and workflow analysis. This has been the experience in other industries such as in retail and marketing. The enabling technology is now available. What remains is solidifying and deploying data to action procedures.
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Summary: The Mildred Lake Settling Basin (MLSB) is the largest disposal site for mature fine tailings (MFT) at the Syncrude Canada Ltd. oil sands plant. Over the past years (since 1996), there has been a marked change in the densification behaviour of MFT in the MLSB. Methane-producing microorganisms, known as methanogens, have become very active, and large amounts of biogas (mainly methane) have been produced. In certain regions within the MLSB, gas bubbles are released to the water surface of the...
Publication: CIM Bulletin
Author(s): C. Guo, R.J. Chalaturnyk, J.D. Scott, M. MacKinnon
Issue: 6
Volume: 2
Year: 2007
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Summary: The orebody in Chikla Mine, particularly between the -70 and -170 ft levels, displays two systematic joint sets: one has an average spacing of 2.5 m, with its strike direction along N60°E and dipping almost vertical due east; and the other has an average spacing of 2.0 m, with its strike direction along N80°W and dipping almost vertical due south. Schistocity planes, which are horizontal and sub-horizontal, form the third plane of weakness in the orebody. Such planes exhibit a spacing...
Publication: CIM Bulletin
Author(s): M.R. Saharan, A.K. Chakraborty, A. Sinha, N.K. Babar, H.R. Kalihari, C.P.N. Pathak
Issue: 6
Volume: 2
Year: 2007
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Summary: Mining operations are under constant pressure when it comes to optimization and cost reduction. Drilling and blasting, though by themselves comprise a minor percentage (about 15%) of mining costs, have a strong influence on the downstream operation costs, as they are responsible for the fragmentation of the blasted rock. Strong emphasis has been put on the fragmentation of the muckpile (e.g., the mine-tomill approach), despite the difficulties for measuring it, in order to establish its...
Publication: CIM Bulletin
Author(s): P. Segarra, J.A. Sanchidrián, J.J. Montoro, L.M. López
Issue: 6
Volume: 2
Year: 2007
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Summary: During the process of open-pit mine development, some sites are considered for dumping of surface soils and for waste disposal. Mine spoils include overburden, waste rock, low-grade materials, and tails from the process plant, each of them having their own unique characteristics. For each type of overburden, waste rock, low-grade materials, and process tail, separate storage sites are considered so that it becomes possible to transport or reuse the individual items. Parameters that affect...
Publication: CIM Bulletin
Author(s): K. Shahriar, F. Samimi Namin
Issue: 6
Volume: 2
Year: 2007
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