Obrabotka Metallov 2024 Vol. 26 No. 3

OBRABOTKAMETALLOV Vol. 26 No. 3 2024 112 TECHNOLOGY 59. GOST 34.201–89. Informatsionnaya tekhnologiya. Kompleks standartov na avtomatizirovannye sistemy. Vidy, komplektnost’ i oboznachenie dokumentov pri sozdanii avtomatizirovannykh system [State Standard 34.201–89. Information technology. Set of standards for automated systems. Types, sets and indication of documents for automated systems making]. Moscow, Goskomstandart Publ., 2002. 36 p. 60. GOST 34.601–90. Informatsionnaya tekhnologiya. Kompleks standartov na avtomatizirovannye sistemy. Avtomatizirovannye sistemy stadii sozdaniya [State Standard 34.601–90. Information technology. Set of standards for automated systems. Automated systems. Stages of development]. Moscow, Goskomstandart Publ., 2002. 84 p. 61. GOST R ISO/MEK 12207–2010. Informatsionnaya tekhnologiya. Sistemnaya i programmnaya inzheneriya. Protsessy zhiznennogo tsikla programmnykh sredstv [State Standard R ISO/MEK 12207–2010. Information technology. System and software engineering. Software life cycle processes]. Moscow, Standartinform Publ., 2011. 105 p. 62. GOST R 15.301–2016. Sistema razrabotki i postanovki produktsii na proizvodstvo. Produktsiya proizvodstvenno-tekhnicheskogo naznacheniya. Poryadok razrabotki i postanovki produktsii na proizvodstvo [State Standard R 15.301–2016. System of product development and launching into manufacture. Products of industrial and technical designation. Procedure of product development and launching into manufacture]. Moscow, Standartinform Publ., 2018. 15 p. 63. GOST ISO/IEC 15420–2010. Avtomaticheskaya identifi katsiya. Kodirovanie shtrikhovoe. Spetsifi katsiya simvoliki shtrikhovogo koda EAN/UPC [State Standard ISO/IEC 15420–2010. Automatic identifi cation. Bar coding. EAN/UPC bar code symbology specifi cation]. Moscow, Standartinform Publ., 2011. 45 p. 64. Ingemansson A.R. Tekhnologicheskaya podgotovka i adaptivnoe upravlenie v tsifrovykh proizvodstvennykh sistemakh [Technological preparation and adaptive control in digital production systems]. Vestnik Kuzbasskogo gosudarstvennogo tekhnicheskogo universiteta = Bulletin of the Kuzbass State Technical University, 2021, no. 4, pp. 5–13. DOI: 10.26730/1999-4125-2021-4-5-13. 65. Suslov A.G., Medvedev D.M., Petreshin D.I., Fedonin O.N. Sistema avtomatizirovannogo tekhnologicheskogo upravleniya iznosostoikost’yu detalei mashin pri obrabotke rezaniem [System for automated wear–resistance technological control of machinery at cutting]. Naukoemkie tekhnologii v mashinostroenii = Science Intensive Technologies in Mechanical Engineering, 2018, no. 5 (83), pp. 40–44. DOI: 10.30987/article_5ad8d291cddcd8.06334386. 66. Tugengold A.K., Izyumov A.I. Printsipy kontseptual’nogo podkhoda k sozdaniyu podsistemy Instrument v smart-pasporte mnogooperatsionnogo stanka [Principles of conceptual approach to creating tool subsystem for multioperation machine smart-passport]. Vestnik Donskogo gosudarstvennogo tekhnicheskogo universiteta = Vestnik of Don State Technical University, 2014, vol. 14 (2), pp. 74–83. DOI: 10.23947/1992-5980-2014-2-74-83. 67. Xiurong Z., Yeu W. Process analysis and parameter optimization of fi ve axis NC machine for machining complex curved surface impellers. 2019 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS), Changsha, China, 2019, pp. 122–124. DOI: 10.1109/ICITBS.2019.00036. 68. Zakovorotny V.L., Gvindjiliya V.E. Sinergeticheskii podkhod k povysheniyu eff ektivnosti upravleniya protsessami obrabotki na metallorezhushchikh stankakh [Synergetic approach to improve the effi ciency of machining process control on metalcutting machines]. Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science, 2021, vol. 23, no. 3, pp. 84–99. DOI: 10.17212/1994-6309-2021-23.3-84-99. 69. Kouguchi J., Yoshioka H. Monitoring method of cutting forces and vibrations by using frequency separation of acceleration sensor signals during milling process with small ball end mills. Precision Engineering, 2024, vol. 85, pp. 337–356. DOI: 10.1016/j.precisioneng.2023.10.013. 70. Lu Z., Wang M., Dai W., Sun J. In-process complex machining condition monitoring based on deep forest and process information fusion. The International Journal of Advanced Manufacturing Technology, 2019, vol. 104, pp. 1953–1966. DOI: 10.1007/s00170-019-03919-4. 71. Yao Z., Shen J., Wu M., Zhang D., Luo M. Position-dependent milling process monitoring and surface roughness prediction for complex thin-walled blade component. Mechanical Systems and Signal Processing, 2023, vol. 198, p. 110439. DOI: 10.1016/j.ymssp.2023.110439. 72. Accattatis A., Saggio G., Giannini F. A real time FFT-based impedance meter with bias compensation. Measurement, 2011, vol. 44 (4), pp. 702–707. DOI: 10.1016/j.measurement.2011.01.00. 73. Guo Y., Shi D., Shen X., Ji J., Gan W.-S. A survey on adaptive active noise control algorithms overcoming the output saturation eff ect. Signal Processing, 2024, vol. 222, p. 109525. DOI: 10.1016/j.sigpro.2024.109525. 74. Chehrehzad M., Kecibas G., Besirova C., Uresin U., Irican M., Lazoglu I. Tool wear prediction through AIassisted digital shadow using industrial edge device. Journal of Manufacturing Processes, 2024, vol. 113, pp. 117– 130. DOI: 10.1016/j.jmapro.2024.01.052. 75. Ponomarev B.B., Nguyen S.H. Vliyanie orientatsii instrumenta na sily rezaniya pri kontsevom frezerovanii [The infl uence of tool orientation on cutting forces during end milling]. Izvestiya vysshikh uchebnykh zavedenii.

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