Comparison of Alternative Truck Maintenance Strategies using Simulation

Richard Durham, Jean-Pierre Schaillee

Research output: Chapter in Book/Conference paperConference paper

Abstract

Recently the Australian mining industry has focussed on improving the efficiency of existing operations and lowering production costs.
This study explored alternative surface mining truck maintenance strategies, namely condition based maintenance (CBM) and clustered maintenance (CM). The strategies were compared using performance metrics such as truck availability, workshop utilisation and efficiency.
The study examined the application of CBM and combined CB and CM maintenance (CBCM) through computer modelling and simulation. Multiple models, each representing a single maintenance strategy, were constructed. Initial results were analysed before the completion of a sensitivity analysis, which established the influence of key variables on maintenance strategy performance.
The study shows that both CBM and CBCM reduced workshop utilisation, increasing truck availability by 3% and 5%, respectively, over the base case. CBCM provides the greatest reduction in individual maintenance bookings, substantially reducing workshop related delays and increasing workshop efficiency.
Further analysis of CBCM showed that the critical condition threshold governs maintenance strategy performance, while the diagnostic condition threshold largely affects clustering efficiency.
The study concludes that operators who implement CBM should realise significant benefits in terms of both increased production, due to higher truck availability, and lower operating costs.
Original languageEnglish
Title of host publicationMine Planning and Equipment Selection
Subtitle of host publicationMPES 2017
EditorsBehzad Ghodrati, Uday Kumar, Hakan Schunnesson
Place of PublicationLulea
PublisherLulea University of Technology
Pages57-66
ISBN (Electronic)9789175839363
ISBN (Print)9789175839356
Publication statusPublished - 2017
EventInternational Symposium on Mine Planning & Equipment Selection 2017: (MPES2017) - Lulea, Lulea, Sweden
Duration: 29 Aug 201731 Aug 2017

Conference

ConferenceInternational Symposium on Mine Planning & Equipment Selection 2017
CountrySweden
CityLulea
Period29/08/1731/08/17

Fingerprint

Trucks
Availability
Open pit mining
Mineral industry
Operating costs
Sensitivity analysis

Cite this

Durham, R., & Schaillee, J-P. (2017). Comparison of Alternative Truck Maintenance Strategies using Simulation. In B. Ghodrati, U. Kumar, & H. Schunnesson (Eds.), Mine Planning and Equipment Selection: MPES 2017 (pp. 57-66). Lulea: Lulea University of Technology.
Durham, Richard ; Schaillee, Jean-Pierre. / Comparison of Alternative Truck Maintenance Strategies using Simulation. Mine Planning and Equipment Selection: MPES 2017. editor / Behzad Ghodrati ; Uday Kumar ; Hakan Schunnesson. Lulea : Lulea University of Technology, 2017. pp. 57-66
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abstract = "Recently the Australian mining industry has focussed on improving the efficiency of existing operations and lowering production costs. This study explored alternative surface mining truck maintenance strategies, namely condition based maintenance (CBM) and clustered maintenance (CM). The strategies were compared using performance metrics such as truck availability, workshop utilisation and efficiency.The study examined the application of CBM and combined CB and CM maintenance (CBCM) through computer modelling and simulation. Multiple models, each representing a single maintenance strategy, were constructed. Initial results were analysed before the completion of a sensitivity analysis, which established the influence of key variables on maintenance strategy performance. The study shows that both CBM and CBCM reduced workshop utilisation, increasing truck availability by 3{\%} and 5{\%}, respectively, over the base case. CBCM provides the greatest reduction in individual maintenance bookings, substantially reducing workshop related delays and increasing workshop efficiency. Further analysis of CBCM showed that the critical condition threshold governs maintenance strategy performance, while the diagnostic condition threshold largely affects clustering efficiency.The study concludes that operators who implement CBM should realise significant benefits in terms of both increased production, due to higher truck availability, and lower operating costs.",
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Durham, R & Schaillee, J-P 2017, Comparison of Alternative Truck Maintenance Strategies using Simulation. in B Ghodrati, U Kumar & H Schunnesson (eds), Mine Planning and Equipment Selection: MPES 2017. Lulea University of Technology, Lulea, pp. 57-66, International Symposium on Mine Planning & Equipment Selection 2017, Lulea, Sweden, 29/08/17.

Comparison of Alternative Truck Maintenance Strategies using Simulation. / Durham, Richard; Schaillee, Jean-Pierre.

Mine Planning and Equipment Selection: MPES 2017. ed. / Behzad Ghodrati; Uday Kumar; Hakan Schunnesson. Lulea : Lulea University of Technology, 2017. p. 57-66.

Research output: Chapter in Book/Conference paperConference paper

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AU - Durham, Richard

AU - Schaillee, Jean-Pierre

PY - 2017

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AB - Recently the Australian mining industry has focussed on improving the efficiency of existing operations and lowering production costs. This study explored alternative surface mining truck maintenance strategies, namely condition based maintenance (CBM) and clustered maintenance (CM). The strategies were compared using performance metrics such as truck availability, workshop utilisation and efficiency.The study examined the application of CBM and combined CB and CM maintenance (CBCM) through computer modelling and simulation. Multiple models, each representing a single maintenance strategy, were constructed. Initial results were analysed before the completion of a sensitivity analysis, which established the influence of key variables on maintenance strategy performance. The study shows that both CBM and CBCM reduced workshop utilisation, increasing truck availability by 3% and 5%, respectively, over the base case. CBCM provides the greatest reduction in individual maintenance bookings, substantially reducing workshop related delays and increasing workshop efficiency. Further analysis of CBCM showed that the critical condition threshold governs maintenance strategy performance, while the diagnostic condition threshold largely affects clustering efficiency.The study concludes that operators who implement CBM should realise significant benefits in terms of both increased production, due to higher truck availability, and lower operating costs.

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Durham R, Schaillee J-P. Comparison of Alternative Truck Maintenance Strategies using Simulation. In Ghodrati B, Kumar U, Schunnesson H, editors, Mine Planning and Equipment Selection: MPES 2017. Lulea: Lulea University of Technology. 2017. p. 57-66