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DC Field | Value | Language |
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dc.contributor.author | Aruna, M. | |
dc.contributor.author | Murthy, Ch.S.N. | |
dc.contributor.author | Pai, R. | |
dc.contributor.author | Nand, R. | |
dc.date.accessioned | 2020-03-31T08:18:58Z | - |
dc.date.available | 2020-03-31T08:18:58Z | - |
dc.date.issued | 2007 | |
dc.identifier.citation | Journal of Mines, Metals and Fuels, 2007, Vol.55, 44018, pp.191-194 | en_US |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/10346 | - |
dc.description.abstract | Now-a-days computer is used in every field of engineering, including mining industry, at various stages in various capacities. One of the major problems in surface mining is material handling, which involves transportation of both ore and overburden. Most of the projects make use of shoveldumper system in spite of its huge capital investment and recurring costs. Hence a lot of mind and time has to be devoted before its procurement so as to optimize their number and maximize its utility. This paper addresses various optimization models available for productivity analysis of shovel-dumper fleet. Match factor method is one of the commonly used techniques to know the relative coverage which shovels are getting from truck fleet. Operations research techniques like queuing theory, integer programming, simulation and goal programming consider the probabilistic nature associated with the system. Even though many models are available for optimization and analyzing the productivity of shovel dumper system, further research and study is needed to devise a desirable technique for the same. | en_US |
dc.title | Applications of computer in mining industry with special regard to shovel-dumper productivity | en_US |
dc.type | Article | en_US |
Appears in Collections: | 1. Journal Articles |
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