ISSN (print) 1995-2732
ISSN (online) 2412-9003


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DOI: 10.18503/1995-2732-2021-19-3-84-89


The issues of ensuring a set level of consumer properties of new and conventional types of products by efficient quality management in treatment processes are vital for metalware plants. When designing technological processes of metalware production, there are always noise factors, such as inaccurate initial data associated with the uncertainty of ambient conditions, a varying quality of raw materials, and imperfection of technological equipment. In this regard, an urgent issue is to develop a methodology for designing the processes of manufacturing metalware, taking into account parameter uncertainty of initial data. Now, one of the actively developing priorities is a robust parameter design. The use of robust optimization makes it possible to develop a technology that is insensitive to variations of noise factors. The method is based on using orthogonal matrices, representing a minimum set of experiments with various combinations of levels of parameters. A robust experiment is associated with two matrices: a matrix of control parameters and a matrix of noise factors. The paper describes a suggested methodology of designing new and improving existing technological processes of metalware production using robust optimization. This procedure may be applied both for designing a new technology and improving the existing one. To reduce quality indicators to a single objective function, a grey relational analysis (GRA) is used. This is a method of analyzing the degree and level of correlation between different parameters for their discrete sequence. A robust approach may be efficiently applied for developing new and improving existing processes of manufacturing metalware. A practical application of this methodology will significantly reduce time required to work out technological solutions for ensuring a set level of quality of finished products.


Metalware production, robust optimization, robustness, robust experiment, noise factors, quality indicators, ANOVA, GRA.

For citation

Pivovarova K.G. Metalware Quality Management Based on a Robust Parameter Design. Vestnik Magnitogorskogo Gosudarstvennogo Tekhnicheskogo Universiteta im. G.I. Nosova [Vestnik of Nosov Magnitogorsk State Technical University]. 2021, vol. 19, no. 3, pp. 84–89.

Ksenia G. Pivovarova – PhD (Eng.), Associate Professor, Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia. Еmail: This email address is being protected from spambots. You need JavaScript enabled to view it.. ORCID 0000-0002-9961-4074

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