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Mine production index (MPI)-extension of OEE for bottleneck detection in mining
Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
Antal upphovsmän: 32016 (Engelska)Ingår i: International Journal of Mining Science and Technology, ISSN 2095-2686, Vol. 26, nr 5, s. 753-760Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Although mining production depends on various equipments, significant amount of production loss can be attributed a specific equipment or fleet. Bottleneck is defined not only by production loss but also by our satisfaction from the equipment. The user satisfaction could be measured as machine effectiveness. Mining literature on performance improvement and optimization of equipment operations assert importance of availability, utilization and production performance as key parameters. These three parameters are useful for evaluating effectiveness of equipment. Mine production index (MPI), which can represent the effect of these factors, has been applied for continuous operation in mining. MPI uses Fuzzy Delphi Analytical Hierarchy Process to determine importance of each three parameter for individual equipment. A case study in a Swedish open pit mine was done to evaluate the field application of MPI. The results reveal that crusher is the bottleneck equipment in studied mine. As a methodical approach, an algorithm which uses MPI and detects bottleneck in continuous mining operation has been proposed.

Ort, förlag, år, upplaga, sidor
2016. Vol. 26, nr 5, s. 753-760
Nationell ämneskategori
Annan samhällsbyggnadsteknik
Forskningsämne
Drift och underhållsteknik
Identifikatorer
URN: urn:nbn:se:ltu:diva-14320DOI: 10.1016/j.ijmst.2016.05.050ISI: 000383712400002Scopus ID: 2-s2.0-85006335485Lokalt ID: dac441fb-01e7-4abb-8794-deb04c2d27fcOAI: oai:DiVA.org:ltu-14320DiVA, id: diva2:987275
Anmärkning

Validerad; 2016; Nivå 1; 20151130 (hadhos)

Tillgänglig från: 2016-09-29 Skapad: 2016-09-29 Senast uppdaterad: 2018-07-10Bibliografiskt granskad
Ingår i avhandling
1. Mine Production Assurance Program- Development and Application
Öppna denna publikation i ny flik eller fönster >>Mine Production Assurance Program- Development and Application
2016 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
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

Ort, förlag, år, upplaga, sidor
Luleå: Luleå University of Technology, 2016
Serie
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
Nationell ämneskategori
Annan teknik
Forskningsämne
Gruv- och Berganläggningsteknik
Identifikatorer
urn:nbn:se:ltu:diva-61123 (URN)978-91-7583-787-1 (ISBN)978-91-7583-788-8 (ISBN)
Disputation
2016-01-31, F1031, Luleå, Luleå, 10:00 (Engelska)
Handledare
Tillgänglig från: 2016-12-19 Skapad: 2016-12-16 Senast uppdaterad: 2017-11-24Bibliografiskt granskad

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Lanke, AmolHoseinie, HadiGhodrati, Behzad

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