Long-term economic sensitivity analysis of light duty underground mining vehicles by power source

Richard S. Schatz, Antonio Nieto, Serguei N. Lvov

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

LHD's are expensive vehicles; therefore, it is important to accurately define the financial consequences associated with the investment of purchasing the mining equipment. This study concentrates on long-term incremental and sensitivity analysis to determine whether it is feasible to incorporate current battery technology into these machines. When revenue was taken into account, decreasing the amount of haulage in battery operated equipment by 5% or 200 kg per h amounts to a $4.0 × 104 loss of profit per year. On average it was found that using battery operated equipment generated $9.5 × 104 more in income annually, reducing the payback period from seven to two years to pay back the additional $1.0 × 105 investment of buying battery powered equipment over cheaper diesel equipment. Due to the estimated 5% increase in capital, it was observed that electric vehicles must possess a lifetime that is a minimum of one year longer than that of diesel equipment.

Original languageEnglish (US)
Pages (from-to)567-571
Number of pages5
JournalInternational Journal of Mining Science and Technology
Volume27
Issue number3
DOIs
StatePublished - May 2017

Fingerprint

Sensitivity analysis
sensitivity analysis
Economics
economics
diesel
Mining equipment
Purchasing
electric vehicle
haulage
Electric vehicles
Profitability
vehicle
income
battery

All Science Journal Classification (ASJC) codes

  • Geotechnical Engineering and Engineering Geology
  • Energy Engineering and Power Technology
  • Geochemistry and Petrology

Cite this

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Long-term economic sensitivity analysis of light duty underground mining vehicles by power source. / Schatz, Richard S.; Nieto, Antonio; Lvov, Serguei N.

In: International Journal of Mining Science and Technology, Vol. 27, No. 3, 05.2017, p. 567-571.

Research output: Contribution to journalArticle

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