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RESEARCH PAPER
Equivalent availability index for the performance measurement of haul truck fleets
 
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1
Industrial Engineering Department, Universidad Técnica Federico Santa María, Av. España 1680, Valparaíso, Chile
 
2
MINES ParisTech, PSL Research University, Sophia Antipolis, France
 
3
Energy Department, Politecnico di Milano, Via La Masa 34, 20156 Milan, Italy
 
4
Department of Nuclear Engineering, College of Engineering, Kyung Hee University, Republic of Korea
 
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Mechanical Engineering Department, Universidad de Chile, Av. Beauchef 851, Santiago, Chile
 
 
Publication date: 2020-12-31
 
 
Eksploatacja i Niezawodność – Maintenance and Reliability 2020;22(4):583-591
 
HIGHLIGHTS
  • This article presents a model of performance analysis for a truck fleet system.
  • The algorithm considers heterogeneous fleets with individual characteristics.
  • Equivalent Availability is a key indicator to determine the productive capacity.
  • The methodology strengths are based on the capacity to define dynamic indicator
KEYWORDS
ABSTRACT
This article presents a model of performance analysis for a truck fleet system in an openpit mine, considering special characteristics of haul fleets. In these systems, the expected availability of each piece of equipment and its operating capacity are the fundamental variables to construct a global fleet performance function. Our analytical algorithm considers heterogeneous fleets with known individual characteristics of transport capacity and failure and repair behavior. The results converge to a new indicator denominated “Equivalent Availability” (EA), which arises from the need to evaluate the capacity of the truck fleet to operate at a lower payload than required using different combinations of equipment to achieve an availability goal. EA is a key indicator to determine the productive capacity of a process, and for selecting equipment and their combinations to achieve production objectives. To exemplify the potentialities of the EA, a case study is implemented in a Chilean copper truck fleet mining process.
 
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eISSN:2956-3860
ISSN:1507-2711
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