heavy automotive equipment, integrated quality model, fuzzy mathematics, collective expert assessment, decision support, applied information technology


Subject matter. Justification of the choice of a model range of heavy vehicles when organizing purchases in the framework of large-scale infrastructure projects. Goal. Increasing the efficiency of the process of determining the model range of heavy automobile equipment, in terms of its operation, at the stage of initiating large-scale infrastructure projects, by creating a special methodological approach, and on its basis - an appropriate information technology for decision support. Tasks. To develop a complex fuzzy model for assessing the quality of heavy automobile equipment during its operation. To propose a method for collective expert assessment of the quality of heavy automobile equipment during its operation. To develop an applied information technology to support decision-making on the formation of a model range of purchased heavy vehicles. Methods. System analysis – in the development of a comprehensive model of the quality of heavy automotive equipment; fuzzy mathematics – to ensure the process of fuzzy assessment by experts of the quality of heavy automobile equipment during its operation; expertology – when creating a method for forming a generalized quality assessment by means of collective expert assessment; software engineering – when creating applied information technology for collective expert assessment of the quality of heavy automobile equipment. Results. An approach to the creation of a number of applied information technologies for complex expert assessment of the quality of operation of a wide class of vehicles using the example of heavy automobile equipment. Conclusions. A comprehensive model has been developed for assessing the quality of heavy automobile equipment, at the stage of its operation, using the principles and approaches that are generally accepted in system analysis. The method of presentation and further implementation of a complex quality assessment model by means of fuzzy mathematics, which makes it possible to increase the efficiency of expert assessment, is described. A method for forming a team of experts is proposed, which implements the selection of an expert from several applicants, while taking into account the communication capabilities of individual members of the team of experts. The applied information technology for complex assessment of the quality of heavy automobile equipment in the aspect of its operation is described, in order to justify the choice of a model range for the acquisition of this equipment in the implementation of large-scale infrastructure projects.

Author Biographies

Volodymyr Rudnytskyi, Cherkasy State Technological University

Doctor of Sciences (Engineering), Professor, Head of the Department of Information Security and Computer Engineering

Amineh Hadi, National Aerospace University "Kharkiv Aviation Institute"



Zekunov, A. G., Ivanov, V. N., Mishin, V. M., Pazyuk, Yu. V., Vlasova, T. I. (2015), Quality management : collective monograph, Moscow : Yurayt Publishing House, 475 p.

Huang, E. (2010), "Product quality indicators and methods of their assessment at an industrial enterprise", Questions of modern science and practice, No. 10-12 (31), Р. 246–254.

Medunetskiy, V. M. (2013), Fundamentals of quality assurance and certification of industrial products : a tutorial, SPb. : NRU ITMO, 61 p.

Astanina, M. A. (2014), The system of quality audit: a cognitive approach, Moscow : MISAO, 108 p.

Stylidisa, K., Wickmana, C., Söderberga, R. (2015), "Defining perceived quality in the automotive industry: an engineering approach", Procedia CIRP 36 (2015) P. 165–170, available at :

Paulo, A., Cauchick, M., Terra da Silva, M., Chiosini, E. L., Schütze, K. (2007), "Assessment of service quality dimensions: a study in a vehicle repair service chain", available at :

Liu, X. - B., Zhou, M., Yang, J. – B., Yang, S. - L. (2008), "Assessment of strategic R&D projects for car manufacturers based on the evidential reasoning approach", International Journal of Computational Intelligence Systems, Vol. 1, No. 1, P. 24–49.

Key outcomes from Life Cycle Assessment of vehicles, a state of the art literature review Maarten Messagie1, Cathy Macharis, Joeri. VanMierlo// Barcelona, Spain, November 17-20, 2013.

Huang En. (2010), Product quality indicators and methods of their assessment at an industrial enterprise / Enb Huang // Questions of modern science and practice. - No. 10-12 (31). - Р. 246-254.

Hadi Amineh (2016), "The product quality: characteristics, essence, evolution of approaches", Economy. Management. Modern problems and prospects of development, Kraków, No. 4, P. 64–72.

Kosach, N. I., Siroklyn, V. P., Hadi, A. (2016), "The quality of the system engineering company

Iran Khodro management", All-Ukraine Scientific and Technіc Conferense of Young Scientists in Metrology, No. 1-5,

P. 8296.

Hadi Amineh, Kosach, N. (2016), "Assessment of Consumers’ Satisfaction with the Automotive Product Quality", International Journal of Environmental & Science Education, Vol. 11, No. 16, P. 8726–8739.

Stroganov, V. I. (2012), "Results and prospects of development of electric vehicles and cars with hybrid power plants", Electronics and electrical equipment of transport, No. 2.

Vitovtova, A. A. (2016), "Analysis of quality and evaluation of competitiveness of the product products", Materials of the VIII International Student Electronic Scientific Conference "Student Scientific Forum", available at : (date accessed: 06.12.2016).

Leonov, O. A., Temasova, G. N. (2015), Economy of quality, Saarbruken, 305 р.

Leonov, O. A., Temasova, G. N., Vergazova, Yu. G. (2015), Quality management, Moscow : Publishing house RSAU, Moscow Agricultural Academy, 180 p.

Kovalenko, I. I., Shved, A. V. (2012), Methods of expert assessment of scenarios : textbook allowance, Nikolaev : Publishing house of ChGU im. Petra Mogila, 156 p.

Zadeh, L. (1975), "Fuzzy Logic and Approximate Reasoning", Synthese, Vol. 80, P. 407–428.

Shostak, E. I. (2016), "Fuzzy model for assessing the admissibility of including applicants in the team of executors of high-tech projects, according to the level of competence", Vestnik dvigatelestroyeniya, No. 2, P. 42–48.