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  • 1.
    Allahkarami, Zeynab
    et al.
    Faculty of Engineering, Department of Mining Engineering, University of Tarbiat.
    Sayadi, Ahmad Reza
    Tarbiat Modares University, Faculty of Engineering, Department of Mining Engineering, University of Tarbiat.
    Lanke, Amol
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Reliability Analysis of Motor System of Dump Truck for Maintenance Management2016Inngår i: Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective / [ed] Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde, Encyclopedia of Global Archaeology/Springer Verlag, 2016, s. 681-688Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Dump truck is one of the main machinery in open pit mines. From an economic point of view, more than 50–60 % of production costs in open pit mines are allocated to hauling and loading costs, so it is important to keep equipment in good condition. Reliability is a useful tool for evaluating the performance of this machine. In this research, the reliability of motor subsystem of a dump truck in Miduk Copper Mine in Iran has been analyzed. The failure data were collected during 20 months of dump truck operation. Trend and serial correlation tests were used to validate the assumption of independent and identically distribution (IID). According to tests, the data are independent and identically distributed therefore the renewal process technique is used for modelling. For finding the best-fit distribution, different types of statistical distributions were tested using the Easyfit software. The analysis results indicated the time between failures (TBF) data obey the Weibull (3p) distribution. The developed model based on these data showed that the reliability of the motor subsystem decreases to a zero value after approximately 430 h of operation. Regarding to the obtained reliability plot, preventive reliability-based maintenance time interval for 90 % reliability levels for machine in the motor subsystem is 21 h.

  • 2.
    Lanke, Amol
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Mine Production Assurance Program- Development and Application2016Doktoravhandling, med artikler (Annet vitenskapelig)
    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

  • 3.
    Lanke, Amol
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Mine production index: Development and application2014Licentiatavhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Assuring 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). Since such a guideline does not exist for mining as a process industry, this study started by reviewing four such techniques used in similar industries. These methods include: total productive maintenance, six sigma, a method prescribed by European foundation of quality management, and production assurance program (PAP) used in the oil and gas industry.These methods and techniques were reviewed according to their objectives and applications. Their implementation and achieved success was determined through a literature review and field participation/study. 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 a lack of tools for specific analysis or a lack of consideration of the requirements of mining. However, given certain similarities in objective and methods, PAP from the oil and gas industry may provide some guidance for MPA.As 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. Overall equipment effectiveness (OEE) which includes these three elements has some limitations for application in mining. A Mine Production index (MPi) is thus proposed. This index involves all three parameters for equipment productivity mentioned above. It also consists of weights for each parameter. The weights in this study are determined through expert opinions/judgements using fuzzy analytical hierarchy process (FAHP). Equipment with low MPi can be labelled as bottlenecks. 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 exact cause 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. Further root cause analysis and uncertainty detection for bottleneck equipment is also possible, and this forms the basis for MPA.

  • 4.
    Lanke, Amol
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ghodrati, Behzad
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Comparison of Mine Production Index Factors for Rock Bolter and Shovel2016Inngår i: Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective / [ed] Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde, Encyclopedia of Global Archaeology/Springer Verlag, 2016, s. 645-656Konferansepaper (Fagfellevurdert)
    Abstract [en]

    MPi uses availability, utilisation and performance to compare and evaluate equipment. These measures apply to all equipment in mining. However equipment use in mining operations could lead to different evaluation of its availability, utilisation and production performance. MPi evaluation and comparison of equipment on MPi basis thus becomes difficult. Shovel and rock bolters are equipment used in open pit and underground mining respectively. Rock bolters are used to place bolts in mining room. Bolts reinforce rock masses through restraining the deformation within the rock masses. In open pit mining shovels are used for loading broken rock in truck for hauling. MPi can be used as scale for comparison of these equipment. However the operational difference between two equipment leads to different evaluation of MPi. Using hypothetical case study difference between availability, utilisation and performance of the rock bolters and shovel is studied. It was found that these parameters must be measured differently for rock bolters than shovel. Rock bolters availability and utilisation should be given less weights consideration as compared to other equipment in continuous mining operation. Its performance measurement it dependent upon bolts installed and capacity of bolts installation rather than tonnage of ore produced. This study can be helpful for evaluating MPi for equipment which are non-continuously used and lacks output in terms of ore tonnage..

  • 5.
    Lanke, Amol
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ghodrati, Behzad
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Reducing defects and achieving business profitability using innovative and lean thinking2013Inngår i: IEEE International Conference on Industrial Engineering and Engineering Management: IEEM 2013, Bangkok, Thailand; 10 - 13 December 2013, Piscataway, NJ: IEEE Communications Society, 2013, s. 1026-1030Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The case study conducted in magnet manufacturing shows that with use of innovative thinkingusing TRIZ an organization can achieve the quality ofproduct without sacrificing business goals. Cost of qualityand cost of manufacturing were both balanced with simplesolution to the production problems. Simple innovations leadto increased output capacity and reduction of defects. Thiscontributed to reducing the wastage of resources i.e. achieveLEAN. This case study holds a prime example of TRIZ andhow an manufacturing organization can benefit using such anew technique.

  • 6.
    Lanke, Amol
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ghodrati, Behzad
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Hoseinie, Hadi
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Uncertainty Analysis of Production in Open Pit Mines: Effect of environmental conditions2016Inngår i: Archives of Mining Sciences, ISSN 0860-7001, E-ISSN 1689-0469Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Production volume by mining equipment is influenced by internal and external parameters. External parameters include weather conditions, human factors etc. This study shows impact of temperature, rainfall and snowfall on production volume achieved under influence of these factors in open pit mine.  The case study is carried out which include data from weather station near an open pit mine and production tonnage. Multi regression modelling in performed using stated factors and production volume.  It was observed that Snowfall and rainfall has impact on production volume. Temperature has no effect on payload achieved as represented by model. With increasing snowfall and rainfall decreases. Higher snowfall (0.8 meter to 1 meter) although has tends to lead higher tonnage compared to low snowfall (0 to 0.8meters). Rainfall causes decrease in production of ore, with increase in rainfall from 1.2 mm, there is sharp decrease in production volume. The optimization table shows that with either no snowfall coupled with maximum rainfall (39 mm) it is possible to achieve production levels of 120 thousand per day. With high snowfall (1.06 metres) and no rainfall, it is possible to achieve maximum of 118 thousand tonnes per day.

  • 7.
    Lanke, Amol
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ghodrati, Behzad
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Hoseinie, Hadi
    Department of Mining Engineering, Hamedan University of Technology, Hamedan.
    Uncertainty Analysis of Production in Open Pit Mines: operational parameter regression analysis of Mining Machinery2016Inngår i: Mining science, ISSN 2353-5423, Vol. 23, s. 147-160, artikkel-id msc162312Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 8.
    Lanke, Amol
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ghodrati, Behzad
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Lundberg, Jan
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Production improvement techniques in process industries for adoption in mining: A comparative study2016Inngår i: International Journal of Productivity and Quality Management, ISSN 1746-6474, E-ISSN 1746-6482, Vol. 19, nr 3, s. 366-386Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    High profitability and customer satisfaction are of supreme importance for any business. To achieve both objectives, an organisation must design a structured approach. To achieve profitability, organisations look to principles of lean manufacturing and techniques such as EFQM, business excellence. This paper reviews such methodologies across different industries, comparing techniques and elements. Its objective is to determine which methodologies are most applicable to the Swedish mining industry and propose a method to achieve lean mining. To this end, the paper looks at the methodologies of a food manufacturing industry, an automobile component manufacturing company, the manufacturing and service sector, and the oil and gas industry. It finds that the method used in the oil and gas industry is more relevant to mining, even though it has some flaws. Further research is needed to adapt this method to the mining industry.

  • 9.
    Lanke, Amol
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Hoseinie, Hadi
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ghodrati, Behzad
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Mine Production index (MPi): New method to evaluate effectiveness of mining machinery2014Konferansepaper (Fagfellevurdert)
    Abstract [en]

    OEE has been used in many industries as measure of performance. However due to limitations of original OEE, it has been modified by various researchers. OEE for mining application is special version of classic equation, carries these limitation over. In this paper it has been aimed to modify the OEE for mining application by introducing the weights to the elements of it and termed as Mine Production index (MPi). As a special application of new index MPishovel has been developed by authors. This can be used for evaluating the shovel effectiveness. Based on analysis, utilization followed by performance and availability were ranked in this order. To check the applicability of this index, a case study was done on four electrical and one hydraulic shovel in a Swedish mine. The results shows that MPishovel can evaluate production effectiveness of shovels and determine effectiveness values in optimistic view compared to OEE. MPi with calculation not only give the effectiveness but also can predict which elements should be focused for improving the productivity.

  • 10. Lanke, Amol
    et al.
    Hoseinie, Hadi
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ghodrati, Behzad
    Mine Production index (MPi): new method to evaluate the effectiveness of mining machinery2014Konferansepaper (Annet vitenskapelig)
  • 11.
    Lanke, Amol
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Hoseinie, Hadi
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ghodrati, Behzad
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Mine production index (MPI)-extension of OEE for bottleneck detection in mining2016Inngår i: International Journal of Mining Science and Technology, ISSN 2095-2686, Vol. 26, nr 5, s. 753-760Artikkel i tidsskrift (Fagfellevurdert)
    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.

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