OBRABOTKAMETALLOV Vol. 28 No. 1 2026 147 TECHNOLOGY Intelligent decision support system for the optimization of turning parameters of thin-walled parts in the context of designing hybrid metal-cutting equipment Ayagma Zhargalova 1, a, *, Vadim Skeeba 2, b, **, Ziqi Tong 1, c, Semyon Papko 2, d, Ivan Yulusov 2, e 1 Bauman Moscow State Technical University, 5/1 2nd Baumanskaya St., Moscow, 105005, Russian Federation 2 Novosibirsk State Technical University, 20 Prospekt K. Marksa, Novosibirsk, 630073, Russian Federation a https://orcid.org/0000-0002-6251-1004, azhargalova@bmstu.ru; b https://orcid.org/0000-0002-8242-2295, skeeba_vadim@mail.ru; c https://orcid.org/0009-0008-6174-3234, tongziqi29@gmail.com; d https://orcid.org/0009-0004-4512-5963, papko.duty@yandex.ru; e https://orcid.org/0009-0006-7566-6722, yulusov.2017@stud.nstu.ru Obrabotka metallov - Metal Working and Material Science Journal homepage: http://journals.nstu.ru/obrabotka_metallov Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science. 2026 vol. 28 no. 1 pp. 130–151 ISSN: 1994-6309 (print) / 2541-819X (online) DOI: 10.17212/1994-6309-2026-28.1-130-151 ART I CLE I NFO Article history: Received: 17 January 2026 Revised: 02 February 2026 Accepted: 14 February 2026 Available online: 15 March 2026 Keywords: Thin-walled parts Intelligent decision support system Elastic deformation Optimization of cutting parameters Hybrid machine-tool equipment Simulation-based modeling Finite element method (FEM) Funding This work was supported by the Ministry of Science and Higher Education of the Russian Federation (project FSUN-2026-0005). ABSTRACT Introduction. Machining of thin-walled parts represents one of the most challenging problems in modern mechanical engineering, particularly in the aerospace industry, precision instrumentation, and other high-technology sectors where requirements for geometric accuracy are critical. The low bending stiff ness of such structures causes extreme sensitivity to the forces arising during machining: elastic deformations induced by the combined action of cutting forces and clamping forces lead to signifi cant deviations from specifi ed dimensions and shape, constituting one of the primary causes of manufacturing defects. Conventional methods of cutting parameter selection, based on reference data and operator experience, do not provide the capabilities for quantitative prediction of thin-walled workpiece deformation behavior and fail to account for the specifi cs of their deformation behavior. This problem is particularly relevant in the context of developing next-generation hybrid machine tools integrating mechanical and surface-thermal technological operations, where scientifi cally based selection of machining parameters is an essential condition for ensuring the required product quality. The purpose of the present work is to develop, implement in software, and comprehensively verify an intelligent decision support system (DSS) prototype designed for the scientifi cally based selection of optimal turning parameters to minimize elastic deformation of thin-walled parts as an integral component of a design methodology for hybrid metal-cutting systems. Research methods. The system is based on an analytical mathematical model establishing the functional relationship between cutting parameters, the resultant cutting force, and the elastic defl ection of the workpiece, calculated using the cantilever beam model. An iterative multi-parameter optimization algorithm with the objective function of minimizing maximum defl ection was implemented. Verifi cation of system eff ectiveness was conducted on two representative thin-walled parts – a bushing made of steel 45 and a ring made of AK9ch aluminum alloy – through comprehensive simulation that included: verifi cation of process technological feasibility in the SprutCAM CAM system and evaluation of deformation fi elds via static fi nite element analysis in the ANSYS Mechanical CAE system. Results and discussion. Application of the developed DSS provided a signifi cant reduction in force exerted on the workpiece: the tangential cutting force component decreased by a factor of 2.1 for the steel bushing and by a factor of 10.8 for the aluminum ring. Finite element analysis confi rmed a reduction in maximum elastic deformation of 72.3% (from 0.0602 to 0.0167 mm) for the steel bushing and of 87.9% (from 0.0422 to 0.0051 mm) for the aluminum ring. A key technological result is that deformation values after optimization do not exceed the design tolerances for cylindricity. SprutCAM simulation confi rmed the complete technological feasibility of the machining processes. The obtained results demonstrate the prospects of integrating intelligent decision-making systems into the design methodology of hybrid machine tools to enhance the competitiveness of the domestic machine tool industry. For citation: Zhargalova A.D., Skeeba V.Yu., Tong Ziqi, Papko S.S., Yulusov I.S. Intelligent decision support system for the optimization of turning parameters of thin-walled parts in the context of designing hybrid metal-cutting equipment. Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science, 2026, vol. 28, no. 1, pp. 130–151. DOI: 10.17212/1994-6309-2026-28.1130-151. (In Russian). ______ * Corresponding author Zhargalova Ayağma D., Senior Lecturer Bauman Moscow State Technical University, 5, 2nd Baumanskaya St., Building 1, 105005, Moscow, Russian Federation Tel.: +7 903 177-52-38, e-mail: azhargalova@bmstu.ru ______ ** Corresponding author Skeeba Vadim Yu., Ph.D. (Engineering), Associate Professor Novosibirsk State Technical University, 20 Prospekt K. Marksa, Novosibirsk, 630073, Russian Federation Tel: +7 383 346-17-79, e-mail: skeeba_vadim@mail.ru
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