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Equipment selection for miningwith c...

Burt, Christina N.

Equipment selection for miningwith case studies /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Equipment selection for miningedited by Christina N. Burt, Louis Caccetta.
Reminder of title:	with case studies /
other author:	Burt, Christina N.
Published:	Cham :Springer International Publishing :2018.
Description:	xi, 155 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Strip miningEquipment and supplies.
Online resource:	http://dx.doi.org/10.1007/978-3-319-76255-5
ISBN:	9783319762555$q(electronic bk.)

Equipment selection for miningwith case studies /
Equipment selection for miningwith case studies /[electronic resource] :edited by Christina N. Burt, Louis Caccetta. - Cham :Springer International Publishing :2018. - xi, 155 p. :ill., digital ;24 cm. - Studies in systems, decision and control,v.1502198-4182 ;. - Studies in systems, decision and control ;v.3..

Introduction -- Literature Review -- Match Factor Extensions -- Case Studies -- Single Location Equipment Selection -- Multiple Locations Equipment Selection -- Utilisation-based Equipment Selection -- Accurate Costing of Mining Equipment -- Future Research Directions.

This unique book presents innovative and state-of-the-art computational models for determining the optimal truck-loader selection and allocation strategy for use in large and complex mining operations. The authors provide comprehensive information on the methodology that has been developed over the past 50 years, from the early ad hoc spreadsheet approaches to today's highly sophisticated and accurate mathematical-based computational models. The authors' approach is motivated and illustrated by real case studies provided by our industry collaborators. The book is intended for a broad audience, ranging from mathematicians with an interest in industrial applications to mining engineers who wish to utilize the most accurate, efficient, versatile and robust computational models in order to refine their equipment selection and allocation strategy. As materials handling costs represent a significant component of total costs for mining operations, applying the optimization methodology developed here can substantially improve their competitiveness.

ISBN: 9783319762555$q(electronic bk.)

Standard No.: 10.1007/978-3-319-76255-5doiSubjects--Topical Terms:

809693
Strip mining
--Equipment and supplies.

LC Class. No.: TN291

Dewey Class. No.: 622.2920284

Equipment selection for miningwith case studies /
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245 0 0 $a Equipment selection for mining $h [electronic resource] : $b with case studies / $c edited by Christina N. Burt, Louis Caccetta.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a xi, 155 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in systems, decision and control, $x 2198-4182 ; $v v.150
505 0 $a Introduction -- Literature Review -- Match Factor Extensions -- Case Studies -- Single Location Equipment Selection -- Multiple Locations Equipment Selection -- Utilisation-based Equipment Selection -- Accurate Costing of Mining Equipment -- Future Research Directions.
520 $a This unique book presents innovative and state-of-the-art computational models for determining the optimal truck-loader selection and allocation strategy for use in large and complex mining operations. The authors provide comprehensive information on the methodology that has been developed over the past 50 years, from the early ad hoc spreadsheet approaches to today's highly sophisticated and accurate mathematical-based computational models. The authors' approach is motivated and illustrated by real case studies provided by our industry collaborators. The book is intended for a broad audience, ranging from mathematicians with an interest in industrial applications to mining engineers who wish to utilize the most accurate, efficient, versatile and robust computational models in order to refine their equipment selection and allocation strategy. As materials handling costs represent a significant component of total costs for mining operations, applying the optimization methodology developed here can substantially improve their competitiveness.
650 0 $a Strip mining $x Equipment and supplies. $3 809693
650 0 $a Mine haulage $x Mathematical models. $3 809694
650 1 4 $a Engineering. $3 210888
650 2 4 $a Transportation Technology and Traffic Engineering. $3 724870
650 2 4 $a Computational Intelligence. $3 338479
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 252959
700 1 $a Burt, Christina N. $3 809691
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