Mathematical Models Analysis of Combined Processing Methods of Parts

Abstract:

In the article researches mathematical models that ensure effectiveness of use combined methods for parts processing. The use of combined processing methods is always associated with the search for technological compromise and boils down to technical and economic indicators comparative assessment. In this case, it is necessary to rely on mathematical models that objectively reflect manufacturing parts technological processes. Mathematical methods and models for optimizing production processes for manufacturing parts that are applicable in combined methods for processing parts are a complex formalized scientific abstraction that describes production functioning process at all stages of its implementation. In the synthesis of various processing methods, it is necessary to ensure that a number of conditions are met that determine necessary and sufficient conditions for implementing feasibility a particular technology in the combined method of processing parts. Multiple regression analysis methods allow minimizing experiments number in mathematical model determining which adequate to processes under study and form the baseline data for the transition from multi-factor to multi-criteria models. Using this approach, it is necessary to determine objective function optimal values parameters and influence factors in each specific technological process, which will allow us to bring the uncertainty removal in the processing materials technology to a new qualitative level.

• Periodical: Materials Science Forum (Volume 992)
• Pages: 901-906
• DOI: https://doi.org/10.4028/www.scientific.net/MSF.992.901
• Online since: May 2020
• Authors: K.K. Taysaev, L.G. Petrova
• Keywords: Combined Processing Methods (CPM), Fractional Factorial Experiment, Mathematical Model, Multicriteria Analysis, Regression Analysis Method, Technological Process

References

[1] B.P. Saushkina, High technology engineering production, Physico-chemical methods and technologies, Moscow, (2013).

[2] B.P. Saushkina, Physical and mechanical methods in the production of gas turbine engines, Moscow, (2002).

[3] A.A. Gruzdev, Combined methods and technologies for processing machine parts, Industrial Internet portal, https://mirprom.ru/public/kombinirovannye-metody-i-tehnologii-obrabotki-detaley-mashin.html.

[4] V.V. Podinovskiy, V.D. Nogin, Pareto-optimal solutions for multicriteria problems, Science. (1982) 9-64.

[5] V.D. Nogin, I.O. Protodeaconov, I.I. Evlampiev, Fundamentals of optimization theory, Higher School, Moscow, (1986).

[6] M.P. Bazilevsky, Mathematical software for automation of multicriteria selection of regression models: report of PhD thesis of tech, Sciences: 05.13.2018, Irkutsk, (2012).

[7] Yu.B. Kolesov, Yu.B. Sinichenkov, Component technologies of mathematical modeling: studies tutorial, Polytechnic University Publishing, SPb, (2013).

[8] A.S. Antonov, K.A. Aksenov, Multi-criteria decision making under risk based on the integration of multi-agent, simulation, evolutionary modeling and numerical methods, Engineering Newsletter of the Don, 4(2), http://www.ivdon.ru/ magazine/archive/n4p2y2012/1466.

[9] I.G. Chernorutsky, Decision making methods, BHV-Petersburg, SPb., (2005).

[10] E. Mushik, P. Muller, Methods of making technical decisions, Mir, Moscow, (1990).

[11] V.V. Khomenyuk, Elements of the theory of multi-criteria optimization, Science. (1983) 8-25.

[12] I.G. Chernorutsky, Decision making methods, BHV-Petersburg, SPb, (2005).

[13] A.M. Tretyakov, I.N. Kravchenko, Methods of ranking the factors of the objective function in the justification of the optimal method of restoring worn parts, Construction and road machines. 7 (2002) 27-30.

[14] A.M. Tretyakov, I.N. Kravchenko, M.N. Erofeev, Mathematical model of optimization of the choice of the technological process of restoring worn-out parts of construction and road machines, Construction and road machines, 11 (2002), https://exkavator.ru/articles/user/~id=1499.

[15] L. Saati, Thomas, Decision Making with Dependencies and Feedbacks: Analytical Networks, Trans. from English, scientific ed. A.V. Andreichikov, O.N. Andreichikova, M.: Publishing House of LKI, 2008, 360 p.

[16] R. Steuer, Multi-criteria optimization: theory, calculations, applications, Science, Moscow, (1982).