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Sensitivity analysis of key operating parameters of combine harvesters

Author

Listed:
  • M. Kavka

    (Department of Machinery Utilization, Faculty of Engineering, Czech University of Life Sciences Prague, Prague, Czech Republic)

  • M. Mimra

    (Department of Machinery Utilization, Faculty of Engineering, Czech University of Life Sciences Prague, Prague, Czech Republic)

  • F. Kumhála

    (Department of Agricultural Machines, Faculty of Engineering, Czech University of Life Sciences Prague, Prague, Czech Republic)

Abstract

The sensitivity analysis of key operating parameters on the average annual sub-profit in a group of three combine harvesters operating in companies providing agricultural services were analysed. Based on the results of the cost analysis, the following key operating parameters with the greatest influence on the costs were identified: the purchase price of the machine, the price of fuel, maintenance costs, personnel costs and annual performance. These parameters were used in the sensitivity analysis to investigate their effect on unit costs. Changing the above-mentioned parameters is calculated within ± 30% from their mean value. To perform a sensitivity analysis of the average annual sub-profit of combine harvesters, the unit price of mechanized work was additionally used. The results showed that greatest impact on both the average annual earnings of combines operation and on the changes in unit cost was those of the annual performance of the combine harvester, combine harvester purchase price and the cost of fuel. On the other hand, maintenance and personnel costs had a smaller influence concerning these changes of parameters.

Suggested Citation

  • M. Kavka & M. Mimra & F. Kumhála, 2016. "Sensitivity analysis of key operating parameters of combine harvesters," Research in Agricultural Engineering, Czech Academy of Agricultural Sciences, vol. 62(3), pages 113-121.
    • Handle: RePEc:caa:jnlrae:v:62:y:2016:i:3:id:48-2015-rae
    DOI: 10.17221/48/2015-RAE
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    References listed on IDEAS

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