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Substatiation of truck selection in terms of minimizing psychophysiological stress on a driver
2015
Journal:  
Eastern-European Journal of Enterprise Technologies
Author:  
Abstract:

The method of selecting efficient truck for solving the pressing problems of cargo transportation and the required number of goods in corresponding road conditions and when updating the rolling stock was proposed. It is based on selecting the most important indicators of trucks, with their hierarchical classification and determining the integral quality criterion of trucks using the profile method and the analytic hierarchy process («AHP»). This allows more efficient use of the truck for transporting cargo in the required amount in the specified location without losses and with minimal material and labor costs in compliance with current legislation. Technical-operational, ergonomic, dynamic, environmental and power characteristics of vehicles have been analyzed, based on which it was revealed that the truck MERCEDES-BENZACTROS with ecological EURO 4 level (integral quality index considering weight coefficients – 0.95) engine occupies the leading position. The theoretical research allowed to substantiate the method of selecting vehicles taking into account ergonomic characteristics. An adequate method for solving such multicriteria problems, which lies in combining the set of indicators into the integral quality factor, which characterizes the vehicle quality was determined. The method for making management decisions on updating the rolling stock of the car enterprise allows to reduce the impact of transport-technological process indicators on the psychophysiological state of drivers.  Author Biographies Олег Валентинович Дерюгін, State Higher Educational Institution «National Mining University» 19, Karl Marks ave., Dnipropetrovsk, Ukraine, 49005 PhD, Associate Professor The Department of Transport Control

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Eastern-European Journal of Enterprise Technologies

Field :   Fen Bilimleri ve Matematik

Journal Type :   Uluslararası

Metrics
Article : 4.764
Cite : 4.485
2023 Impact : 0.294
Eastern-European Journal of Enterprise Technologies