Management of quality of technological processes in mechanical engineering using three-parameter modeling

Keywords: quality, technological process, modeling, numerical characteristics, dimensionless index

Abstract

DOI: https://doi.org/10.32820/2079-1747-2019-23-159-165

The article considers the expediency of using statistical methods for the analysis of accuracy, stability and control of the technological process, which involves controlling the process with only one indicator of product quality. Recently, for the management of the quality of the technological process in mechanical engineering, preliminary simulation using two-parameter models is used. Mass experiments show that with the time of the technological process, not only the mean and dispersion but also the shape of the distribution curve changes. This suggests that the distribution of quality indices should have a form parameter. To find a generalized model quality indicator that has three parameters, it is advisable to apply a dimensionless quality score. In some works this figure is given, but it is used only with symmetric deviations about the middle of the field of admission. Therefore, in the work, the dimensionless quality index is offered at any deviations of the middle of the field of admission at any time. The studies carried out on the accuracy of the manufacture of products showed that the dimensionless characteristic may also have distribution laws

For the dimensionless quality index, the estimations of parameters are considered and numerical characteristics of these models are found, namely variance, mathematical expectation. In this paper a method for obtaining estimates of model parameters and using the obtained recurrence value for mathematical expectations of ordinal statistics was proposed.

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References

Kucin, AN & Sozonov, JuI 2004, ‘Ocenka kachestva tehnicheskih sistem’, Sborka v mashinostroenii, priborostroenii, no. 7, pp. 23-27.

Reznichenko, NK 2006, ‘Bezrazmernyj kompleksnyj parametr kachestva tehnologicheskoj sistemy’, Vysoki tekhnolohii v mashynobuduvanni, Kharkivskyi politekhnichnyi instytut, Kharkiv, iss. 1 (12), pp. 417-423.

Djejvid, G 1979, Porjadkovye statistiki, Nauka. Glavnaja redakcija fiziko-matematicheskoj literatury, Moskva.

Abdullah M.M., Tari J.J. "The influence of ST and HT quality management practices on performance". Asian pacific management review, Vol.17, No. 2, 2012, 177-193.

Islam M.A., A.F.M.A. Haque "Pillars of TQM implementation in manufacturing organization- An empirical study", Journal of Research in international business and management, Vol.2, No.5, 2012, 128-141.

Li, J. G, Yao, Y. X., Wang, P. Assembly accuracy prediction based on CAD model [Text]. /J. G. Li, Y. X. Yao, P. Wang // The International Journal of Advanced Manufacturing Technology. 2014–Volume 75 – P. 825–832.

Mohammed A. Rahim, Yasir A. Siddiqui, Moustafa Elshafei /Integration of Multivariate Statistical Process Control and Engineering Process Control// Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management Bali, Indonesia, January 7 – 9, 2014.

Published
2024-12-31