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Uncertainty Analysis of Production in Open Pit Mines: operational parameter regression analysis of Mining Machinery
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
Department of Mining Engineering, Hamedan University of Technology, Hamedan.
Number of Authors: 3
2016 (English)In: Mining science, ISSN 2353-5423, Vol. 23, p. 147-160, article id msc162312Article in journal (Refereed) Published
Abstract [en]

In mining uncertainties related to equipment and operation are major reasons for loss of production. In order to address this issue a wide literature review was done in this study. It showed that reliability of equipment, spare part availability, automation of equipment are researched areas focused. However, a methodology which relates operational issues directly to production levels have been not studied with detailed analysis. In order to overcome this issue and propose, a method to achieve production assurance is the objective of this study. A case study with 2.5 years of data from a large open pit mine is carried out. Following the statistical principles, multiple regressions modeling with details analysis, optimization of payload and interpretation of analysis are used. It showed that at system level availability, utilization and maximum capacities are important criteria for finding root cause in loss of production. Model for shovel fleet showed that availability is most important characteristics hindering it to achieve higher level of production. It was also seen that 3 to 4 number of shovels are optimal for achieving current level of production. For truck fleet model represented that capacities involved are less important factor as compared to utilization of fleet.

Place, publisher, year, edition, pages
2016. Vol. 23, p. 147-160, article id msc162312
National Category
Other Engineering and Technologies Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-61117DOI: 10.5277/msc162312Scopus ID: 2-s2.0-85021130262OAI: oai:DiVA.org:ltu-61117DiVA, id: diva2:1057195
Projects
CAMM
Available from: 2016-12-16 Created: 2016-12-16 Last updated: 2017-11-24Bibliographically approved
In thesis
1. Mine Production Assurance Program- Development and Application
Open this publication in new window or tab >>Mine Production Assurance Program- Development and Application
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

ssuring production forms a crucial part of mining business profitability. Factors related to various mine operations, activities and business processes can threaten required/planned mine production.   To address problems and ensure production level in mining, it is necessary to implement a mine production assurance program (MPA). In order to propose a guideline and its component, this study started by reviewing four such techniques used in process industries. Comparing the tools, techniques   and focus with mining productivity and production factors, it was observed that applicability of these methods for mining is limited due to lack of focus on equipment focus, cost focus and other parameters. Similarity of objectives and requirements of equipment focus lead to conclusion that PAP from oil and gas industry seems to be method which can guide MPA.\parAs a basis of MPA, an index is required to create a clear relationship between different situations which can occur in mining operation and production loss. A literature review on mining productivity improvement methods shows availability, utilisation and production performance of equipment are the key factors in determining overall production. A single index applicable for chain operation in mining is needed. A Mine Production index (MPi) is thus proposed. This index involves all three parameters for equipment productivity mentioned above.  Weights associated with MPi calculation for bottleneck equipment can point out critical factors in equipment operation. Once bottleneck equipment and relevant critical factors are known, further analysis can be carried out to determine the possible causes of production loss. By using MPi for machine operations, it is possible to rank machines in terms of production effectiveness. When the study applied MPi to chain operations in a mining case study, a crusher was determined as bottleneck equipment.\parMining operation is heavily influenced by internal and external uncertainties. Operational uncertainties related to equipment includes its key factors leading to production i.e. availability, utilisation and performance. These factors are in turn dependent upon downtime, idle time, rated capacities. External parameters related to weather are based upon location of mining operation. Influence of these factors on production volume, could be used for better decision making during mining operations optimization. To effectively propose a method for correlating internal and external parameters with production volume, case studies in an open pit mine were conducted. During these case studies a multi-regression modelling methodology is used. It was found that at system level availability is important criteria for increasing production. At level of shovel and truck fleet, availability and utilisation are most important characteristics to be focused for reduction in production uncertainty. Environmental factors are although correlate to less variation in production volume compared to operational factors.  Amongst considered environmental factors snowfall is highly influencing followed by rainfall.  At system level  use of maximum capacities of equipment and availability are key point for increasing production. Based on analysis of internal operational factors, it was concluded that capacity of shovel and trucks is underutilised. For shovels availability and idle time are influential factors. For trucks utilisation is highly correlated to production volume generated.  Analysis of environmental factors concluded that, period of zero snowfall and rainfall are perfect condition for equipment production increase. Period when either snowfall or rainfall stabilisation are also equivalent to achieve higher production. Although these production levels are significantly less than period without snow and rain

Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2016
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
National Category
Other Engineering and Technologies
Research subject
Mining and Rock Engineering
Identifiers
urn:nbn:se:ltu:diva-61123 (URN)978-91-7583-787-1 (ISBN)978-91-7583-788-8 (ISBN)
Public defence
2016-01-31, F1031, Luleå, Luleå, 10:00 (English)
Supervisors
Available from: 2016-12-19 Created: 2016-12-16 Last updated: 2017-11-24Bibliographically approved

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Publisher's full textScopushttp://www.miningscience.pwr.edu.pl/Uncertainty-Analysis-of-Production-in-Open-Pit-Mines-operational-parameter-regression-analysis-of-Mining-Machinery,67268,0,2.html

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