Structural modeling of the production quality as a multidimensional object of measurement and control

Authors

  • Наталья Анатольевна Зубрецкая Kyiv National University of Technologies and Design, Str. Nemirovich-Danchenko, 2, Kyiv, 01011, Ukraine https://orcid.org/0000-0003-0439-330X

DOI:

https://doi.org/10.15587/2312-8372.2015.41541

Keywords:

product quality, multi-dimensional, structural modeling, process of quality evaluation, information support

Abstract

The structural-analytical models of product quality as a multidimensional process of evaluation, measurement and control are developed. The product quality is represented as a multi-factor, multi-criteria and multi-parameter estimation object. This structural formalization of quality demonstrates the multidimensional qualities: comprehensiveness due to a set of environmental factors; multicriteriality due collectively evaluated quality criteria; multiparameter information models that describe the relationship between the factors and evaluated criteria. The developed models allow us to establish the relationship between the structural elements of the formation of the product quality.

The advantages of neural network modeling to quantify and data quality assurance are proved. Using the level of formality of quality control processes based on advanced intelligent technologies allows creating a computational and experimental base of automated problem solving of information quality and reducing the cost of development, testing and manufacture of product.

Author Biography

Наталья Анатольевна Зубрецкая, Kyiv National University of Technologies and Design, Str. Nemirovich-Danchenko, 2, Kyiv, 01011

Doctor of Technical Sciences, Professor

Department of Metrology, Standardization and Certification

 

References

  1. Zubretska, N. A. (2012). Kontseptualna model systemy informatsiinoho zabezpechennia yakosti promyslovoi produktsii. Visnyk KNUTD, 3, 68–74.
  2. Fedin, S. S., Zubretskaya, N. A. (2012). Otsenka i prognozirovanie kachestva promyshlennoi produktsii s ispol'zovaniem adaptivnyh sistem iskusstvennogo intellekta. K.: Interservis, 206.
  3. Boguslaev, A. V. et al.; In: Pavlenko, D. V., Subbotin, S. A. (2009). Progressivnye tehnologii modelirovaniia, optimizatsii i intellektual'noi avtomatizatsii etapov zhiznennogo tsikla aviatsionnyh dvigatelei. Zaporozh'e: Motor Sich, 468.
  4. Borisov, V. V., Kruglov, V. V., Fedulov, A. S. (2007). Nechetkie modeli i seti. M.: Goriachaia liniia – Telekom, 284.
  5. Dolgov, M. A., Buketova, N. M., Zubrets’ka, N. A. (2012, March). On the problem of modeling adhesive strength of protective coating depending on the content and conditions of formation of composition. Strength of Materials, Vol. 44, № 2, 212–217. doi:10.1007/s11223-012-9374-5
  6. Bouzeghoub, M., Kedad, Z. (2002). Quality in Data Warehousing. Advances in Database Systems. Springer Science + Business Media, 163–198. doi:10.1007/978-1-4615-0831-1_8
  7. Pedersen, T. B., Jensen, C. S. (2001). Multidimensional database technology. Computer, Vol. 34, № 12, 40–46. doi:10.1109/2.970558
  8. Pedersen, T. B., Jensen, C. S., Dyreson, C. E. (2001, July). A foundation for capturing and querying complex multidimensional data. Information Systems, Vol. 26, № 5, 383–423. doi:10.1016/s0306-4379(01)00023-0
  9. Gilev, S. E., Gorban, A. N. (1996). On Completeness Of The Class Of Functions Computable By Neural Networks. Proc. of the World Congress on Neural Networks (WCNN’96), CA, Lawrens Erlbaum Accociates, 984–991.
  10. Hornik, K., Stinchcombe, M., White, H. (1989, January). Multilayer feedforward networks are universal approximators. Neural Networks, Vol. 2, № 5, 359–366. doi:10.1016/0893-6080(89)90020-8

Downloads

Published

2015-04-02

How to Cite

Зубрецкая, Н. А. (2015). Structural modeling of the production quality as a multidimensional object of measurement and control. Technology Audit and Production Reserves, 2(3(22), 44–48. https://doi.org/10.15587/2312-8372.2015.41541

Issue

Vol. 2 No. 3(22) (2015): Systems and control processes

Section

Systems and Control Processes: Original Research

License

Copyright (c) 2016 Наталья Анатольевна Зубрецкая

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.