Pribory i Metody Izmerenij (Dec 2017)

INFLUENCE OF THE AVERAGE WEIGHTED ESTIMATION TYPE ON THE DEPENDENCE OF THE COMPLEX QUALITY INDEX ON THE PARAMETERS OF OBJECT

  • A. M. Dolzhanskiy,
  • O. A. Bondarenko,
  • Ye. A. Petlyovaniy

DOI
https://doi.org/10.21122/2220-9506-2017-8-4-63-67
Journal volume & issue
Vol. 8, no. 4
pp. 398 – 407

Abstract

Read online

Objects quality is usually assessed by a complex indicator. It includes single quality indicators with their significance factors. The convolution of the corresponding dependencies represents average weighted quantities: arithmetic, geometric, harmonic, quadratic, etc. At the same time, the influence of the convolution type on the level of the complex quality index, the stability of the calculation results and, the reliability of the quality comparison among a number of similar objects is unknown in advance. Therefore, the aim of the study was to assess the influence of the average weighted type on the level and stability of the calculating results of the complex quality index in different objects compressing.For typical private objects compared the values of the complex quality index calculated according to the formulas of various average weighted estimates. Significance of the corresponding unit quality indicators, incompleteness of the object description and control factors influence on the object took into account.The results of the research were got using the method of virtual experiment planning. They showed that the influencing parameters changes, the calculated levels and stability of the complex quality index essentially depend on the type of convolution. It was shown that under the priori uncertainty of the necessary convolution for the best representative choosing of the corresponding class of objects, the arithmetic average weighted estimate is the best for using.The obtained data can serve as a basis for an informed choice of the type of average weighted in the quality assessment of various objects and decision-making on rational levels of controlled factors.

Keywords