Obrabotka Metallov 2021 Vol. 23 No. 3

OBRABOTKAMETALLOV Vol. 23 No. 3 2021 98 EQUIPMENT. INSTRUMENTS 23. Duyun T.A., Grinek A.V., Rybak L.A. Methodology of manufacturing process design, providing quality parameters and minimal costs. World Applied Sciences Journal , 2014, vol. 30 (8), pp. 958–963. DOI: 10.5829/idosi. wasj.2014.30.08.14120. 24. Mukherjee I., Ray P.K. A review of optimization techniques in metal cutting processes. Computers and Industrial Engineering , 2006, vol. 50, no. 1–2, pp. 15–34. DOI: 10.1016/j.cie.2005.10.001. 25. Kozochkin M.P., Fedorov S.V., Tereshin M.V. Sposob opredeleniya optimal’noi skorosti rezaniya v protsesse metalloobrabotki [Method for determining the optimal cutting speed in the process of metalworking]. Patent RF, no. 2538750, 2015. 26. Zariktuev V.Ts. Avtomatizatsiya protsessov na osnove polozheniya ob optimal’noi temperature rezaniya [Automatization of process based on concept of optimal cutting temperature]. Vestnik U fi mskogo gosudarstvennogo aviatsionnogo tekhnicheskogo universiteta = Vestnik USATU , 2009, vol. 12, no. 4, pp. 14–19. 27. Lapshin V.P., Khristoforova V.V., Nosachev S.V. Vzaimosvyaz’ temperatury i sily rezaniya s iznosom i vibratsiyami instrumenta pri tokarnoi obrabotke metallov [Relationship of temperature and cutting force with tool wear and vibrations in metal turning]. Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science , 2020, vol. 22, no. 3, pp. 44–58. DOI: 10.17212/1994-6309-2020-22.3-44-58. 28. Lapshin V., Moiseev D., Minakov V. Diagnosing cutting tool wear after change of cutting forces during turning. AIP Conference Proceedings , 2019, vol. 2188, p. 030001. DOI: 10.1063/1.5138394. 29. Begic-Hajdarevic D., Cekic A., Kulenovic M. Experimental study on the high speed machining of hardened steel. Procedia Engineering , 2014, vol. 69, pp. 291–295. DOI: 10.1016/j.proeng.2014.02.234. 30. Blau P., Busch K., Dix M., Hochmuth C., Stoll A., Wertheim R. Flushing strategies for high performance, ef fi cient and environmentally friendly cutting. Procedia CIRP , 2015, vol. 26, pp. 361–366. DOI: 10.1016/j. procir.2014.07.058. 31. Chin C.-H.,WangY.-C., Lee B.-Y. The effect of surface roughness of end-mills on optimal cutting performance for high-speed machining. Strojniski Vestnik = Journal of Mechanical Engineering , 2013, vol. 52 (2), pp. 124–134. DOI: 10.5545/sv-jme.2012.677. 32. Kant G., Sangwan K.S. Prediction and optimization of machining parameters for minimization power consumption and surface roughness in machining. Journal of Cleaner Production , 2014, vol. 83, pp. 151–164. DOI: 10.1016/j.jclepro.2014.07.073. 33. Martinov G., Martinova L., Ljubimov A. From classic CNC systems to cloud-based technology and back. Robotics and Computer-Integrated Manufacturing , 2020, vol. 63. DOI: 10.1016 / j. rcim.2019.101927. 34. Martinov G.M., Kovalev I.A., Grigoriev A.S . А pproach to building an autonomous cross-platform automa- tion controller based on the synthesis of separate modules. Advances in Automation. RusAutoCon 2019 . Cham, Springer, 2020, pp. 128–136. DOI: 10.1007/978-3-030-39225-3_15. 35. Sosonkin V.L., Martinov G.M. Noveishie tendentsii v oblasti arkhitekturnykh reshenii sistem ChPU [Latest trends in the architecture of CNC systems]. Avtomatizatsiya v promyshlennosti = Automation in Industry , 2005, no. 4, pp. 3–9. 36. Martinov G.M., Sokolov S.V., Martinova L.I., Grigoryev A.S., Nikishechkin P.A. Approach to the diagno- sis and con fi guration of servo drives in heterogeneous machine control systems. Advances in Swarm Intelligence. ICSI 2017. Lecture Notes in Computer Science . Ed. by Y. Tan, H. Takagi, Y. Shi, B. Niu. Cham, Springer, 2017, vol. 10386, pp. 586–594. DOI: 10.1007/978-3-319-61833-3_62. 37. Sang Z., Xu X. The framework of a cloud-based CNC system. Procedia CIRP , 2017, vol. 63, pp. 82–88. DOI: 10.1016/j.procir.2017.03.152. 38. Martinov G.M., Kozak N.V., Nikishechkin P.A. Reshenie zadachi rezervirovaniya v stankakh s chislovym programmnym upravleniem [Solution of the redundancy problem in numerical control machines]. STIN = Russian Engineering Research , 2018, no. 7, pp. 2–7. (In Russian). 39. Bazrov B.M., Balakshin B.S. Adaptivnoe upravlenie stankami [Adaptive control of machine tools]. Moscow, Mashinostroenie Publ., 1973. 688 p. 40. Zhdanov A.A., Plotnikov A.L., Tchigirinsky Ju.L., Firsov I.V. Matematicheskaya model’ utochneniya rezhi- mov rezaniya dlya obespecheniya tochnosti tokarnoi obrabotki nezhestkikh valov na stankakh s ChPU [The math- ematical model of corrections the cutting conditions to providing the precision of nonrigid shafts turning on CNC machines]. Nauchnye trudy SWorld = Scienti fi c papers SWorld , 2015, vol. 3, no. 4 (41), pp. 41–47. 41. Nikishechkin P.A., Grigoriev A.S. Prakticheskie aspekty razrabotki modulya diagnostiki i kontrolya rezhush- chego instrumenta v sisteme CHPU [Practical aspects of the development of the module diagnosis and monitoring of cutting tools in the CNC]. Vestnik MGTU STANKIN = Vestnik MSTU STANKIN , 2013, no. 4 (27), pp. 65–70. 42. Bobrovsky A.V., Drachev O.I. Tekhnologiya mekhanicheskoi obrabotki malozhestkikh osesimmetrichnykh detalei [Technology of processing of low-rigid axisymmetric details]. Izvestiya Volgogradskogo gosudarstvennogo tekhnicheskogo universiteta = Izvestia of Volgograd State Technical University , 2019, no. 9 (232), pp. 15–17.

RkJQdWJsaXNoZXIy MTk0ODM1