Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
Machining vibrations are an important issue as they occur in all types of machining processes. Due to its negative impact on machining results, this phenomenon is undesirable, and so there have been continuous efforts to find solutions that will minimise it, and thus improve the stability and safety of the machining process. The paper attempts to determine the impact of toolholder type and cutting condition on the vibrations generated while milling an AZ31 magnesium alloy. The tests were performed using the three most common types of toolholders: ER, Shrink Fit and hydraulic. The vibration displacement and acceleration signals were analysed based on parameters such as Peak-to-Peak, Peak, and Root Mean Square. Composite Multiscale Entropy was also applied to check the stability of cutting processes and define the level of signal irregularity. To determine the frequencies of vibrations and to detect chatter vibrations Fast Fourier Transform was performed. This provides information on the stability and enables vibrations to be minimized by avoiding unfavourable cutting conditions.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
489--501
Opis fizyczny
Bibliogr. 49 poz., rys., tab.
Twórcy
autor
- Lublin University of Technology, Faculty of Mechanical Engineering, ul. Nadbystrzycka 36, 20-618 Lublin, Poland
autor
- Lublin University of Technology, Faculty of Mechanical Engineering, ul. Nadbystrzycka 36, 20-618 Lublin, Poland
Bibliografia
- 1. Agic A, Eynian M, Ståhl J-E, Beno T. Experimental analysis of cutting edge effects on vibrations in end milling. CIRP Journal of Manufacturing Science and Technology 2019; 24: 66-74, https://doi.org/10.1016/j.cirpj.2018.11.001.
- 2. Ahmadi K, Ismail F. Analytical stability lobes including nonlinear process damping effect on machining chatter. International Journal of Machine Tools and Manufacture 2011; 51(4): 296-308, https://doi.org/10.1016/j.ijmachtools.2010.12.008.
- 3. Akhavan Niaki F, Pleta A, Mears L, Potthoff N, Bergmann JA, Wiederkehr P. Trochoidal milling: investigation of dynamic stability and time domain simulation in an alternative path planning strategy. The International Journal of Advanced Manufacturing Technology 2019; 102: 1405-1419, https://doi.org/10.1007/s00170-018-03280-y.
- 4. Aslan D, Altintas Y. On-line chatter detection in milling using drive motor current commands extracted from CNC. International Journal of Machine Tools and Manufacture 2018; 132: 64-80, https://doi.org/10.1016/j.ijmachtools.2018.04.007.
- 5. Bejaxhin 2019 Bejaxhin ABH, Paulraj G. Experimental investigation of vibration intensities of CNC machining centre by microphone signals with the effect of TiN/epoxy coated tool holder. Journal of Mechanical Science and Technology 2019; 33: 1321-1331, https://doi.org/10.1007/s12206-018-1232-3.
- 6. Biermann D, Kersting P, Surmann T. A general approach to simulating workpiece vibrations during five-axis milling of turbine blades. CIRP Annals 2010; 59(1): 125-128, https://doi.org/10.1016/j.cirp.2010.03.057.
- 7. Burek J, Żyłka Ł, Płodzień M, Gdula M, Sułkowicz P. The influence of the cutting edge shape on high performance cutting. Aircraft Engineering and Aerospace Technology 2018; 90(1): 134-145, https://doi.org/10.1108/AEAT-11-2015-0243.
- 8. Chen W, Zheng L, Teng X, Yang K, Huo D. Finite element simulation and experimental investigation on cutting mechanism in vibrationassisted micro-milling. International Journal of Advanced Manufacturing Technology 2019; 105(11): 4539-4549, https://doi.org/10.1007/s00170-019-03402-0.
- 9. Dang X-B, Wan M, Zhang W-H, Yang Y. Chatter analysis and mitigation of milling of the pocket-shaped thin-walled workpieces with viscous fluid. International Journal of Mechanical Sciences 2021; 194: 106214, https://doi.org/10.1016/j.ijmecsci.2020.106214.
- 10. Dikshit MK, Puri AB, Maity A. Chatter and dynamic cutting force prediction in high-speed ball end milling. Machining Science and Technology 2017; 21(2): 291-312, https://doi.org/10.1080/10910344.2017.1284560.
- 11. Eynian M. Vibration frequencies instable and unstable milling. International Journal of Machine Tools and Manufacture 2015; 90: 44-49, https://doi.org/10.1016/j.ijmachtools.2014.12.004.
- 12. Goyal, D., Pabla, B.S. The Vibration Monitoring Methods and Signal Processing Techniques for Structural Health Monitoring: A Review. Archives of Computational Methods in Engineering 2016; 23: 585-594, https://doi.org/10.1007/s11831-015-9145-0.
- 13. Grzesik W, Niesłony P, Habrat W. Investigation of the tribological performance of AlTiN coated cutting tools in the machining of Ti6Al4V titanium alloy in terms of demanded tool life. Eksploatacja i Niezawodnosc – Maintenance and reliability 2019; 21 (1): 153-158, http://doi.org/10.17531/ein.2019.1.17.
- 14. Hsiao TC, Huang SC. The Effect of Cutting Process Parameters on the Stability in Milling. Advanced Materials Research 2014; 887-888: 1200-1204, https://doi.org/10.4028/www.scientific.net/AMR.887-888.1200.
- 15. Józwik J, Mika D, Dziedzic K. Vibration of thin walls during cutting process of 7075 T651 aluminium alloy. Manufacturing Technology 2016; 16: 113-120, https://doi.org/10.21062/ujep/x.2016/a/1213-2489/MT/16/1/113.
- 16. Kalinski KJ, Galewski MA. Chatter vibration surveillance by the optimal-linear spindle speed control. Mechanical Systems and Signal Processing 2011; 25(1): 383-399, https://doi.org/10.1016/j.ymssp.2010.09.005.
- 17. Kozłowski E, Antosz K, Mazurkiewicz D, Sęp J, Żabiński T. Integrating advanced measurement and signal processing for reliability decisionmaking. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2021; 23 (4): 777-787, http://doi.org/10.17531/ein.2021.4.20.
- 18. Kozłowski E, Mazurkiewicz D, Żabiński T, Prucnal S, Sęp J. Assessment model of cutting tool condition for real-time supervision system. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2019; 21 (4): 679-685, http://doi.org/10.17531/ein.2019.4.18.
- 19. Le Lan JV, Marty A, Debongnie JF. Providing stability maps for milling operations. International Journal of Machine Tools and Manufacture 2007; 47: 1493-1496, https://doi.org/10.1016/j.ijmachtools.2006.09.026.
- 20. Lehrich K, Wąsik M, Kosmol J. Identifying the causes of deterioration in the surface finish of a workpiece machined on a rail wheel lathe. Eksploatacja i Niezawodnosc – Maintenance and reliability 2018; 20 (3): 352-358, http://doi.org/10.17531/ein.2018.3.2.
- 21. Li L, Zhong J, Wang H, Gao Y. Machine tool chatter test and analysis. The Journal of Engineering 2019; 23: 8880-8883, https://doi.org/10.1049/joe.2018.9134.
- 22. Effect of cutter body geometry in Ti-6Al-4V face-milling process. The International Journal of Advanced Manufacturing Technology 2019; 100: 1881-1892, https://doi.org/10.1007/s00170-018-2794-z.
- 23. Munoa J, Beudaert X, Dombovari Z, Altintas Y, Budak E, Brecher C, Stepan G. Chatter suppresion techniques in metal cutting. CIRP Journal of Manufacturing Science and Technology 2016; 65: 785-808, https://doi.org/1 0.1016/j.cirp.2016.06.004.
- 24. Nguyen V, Johnson J, Melkote S. Active vibration suppression in robotic milling using optimal control. International Journal of Machine Tools and Manufacture 2020; 152:103541, https://doi.org/10.1016/j.ijmachtools.2020.103541.
- 25. Quintana, Quintana G, Ciurana J. Chatter in machining processes: A review. International Journal of Machine Tools and Manufacture 2011; 51: 363-376, https://doi.org/10.1016/j.ijmachtools.2011.01.001.
- 26. Salehi M, Blum M, Fath B, Akyol T, Haas R, Ovtcharova J. Epicycloidal Versus Trochoidal Milling-Comparison of Cutting Force, Tool Tip Vibration, and Machining Cycle Time. Procedia CIRP 2016; 46: 230-233, https://doi.org/10.1016/j.procir.2016.04.001.
- 27. Shi Y, Mahr F, Wagner U, Uhlmann E. Chatter frequencies of micromilling processes: Influencing factors and online detection via piezoactuators. International Journal of Machine Tools and Manufacture 2012; 56: 10-16, https://doi.org/10.1016/j.ijmachtools.2011.12.001.
- 28. Sivasakthivel PS, Velmurugan V, Sudhakaran R. Prediction of vibration amplitude from machining parameters by response surface methodology in end milling. The International Journal of Advanced Manufacturing Technology 2011; 53(5-8): 453-461, https://doi.org/10.1007/s00170-010-2872-3.
- 29. Teti R, Jemielniak K, O’Donnell G, Dornfeld D. Advanced monitoring of machining operations. CIRP Annals 2010; 59(2): 717-739, https://doi.org/10.1016/j.cirp.2010.05.010.
- 30. Wang C, Zhang X, Liu J, Cao H, Chen X. Adaptive vibration reshaping based milling chatter suppression. International Journal of Machine Tools and Manufacture 2019; 141:30-35, https://doi.org/10.1016/j.ijmachtools.2019.04.001.
- 31. Weremczuk A, Borowiec M, Rudzik M, Rusinek R. Stable and unstable milling process for nickel superalloy as observed by recurrence plots and multiscale entropy. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2018; 20(2): 318-326, https://doi.org/10.17531/ein.2018.2.19.
- 32. Weremczuk A, Kęcik K, Rusinek R, Warmiński J. The dynamics of the cutting process with Duffing nonlinearity. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2013; 15 (3): 209-21.
- 33. Weremczuk A, Rudzik M, Rusinek R, Warmiński, J. The concept of active elimination of vibrations in milling process. Procedia CIRP 2015; 31: 82-87, https://doi.org/10.1016/j.procir.2015.03.036.
- 34. Wojciechowski S, Twardowski P, Pelic M. Cutting Forces and Vibrations During Ball End Milling of Inclined Surfaces. Procedia CIRP 2014; 14:113-118, https://doi.org/10.1016/j.procir.2014.03.102.
- 35. Wu S, Li R, Liu X, Yang L, Zhu M. Experimental study of thin wall milling chatter stability nonlinear criterion. Procedia CIRP 2016; 56: 422-427, https://doi.org/10.1016/j.procir.2016.10.075.
- 36. Wu S-D, Wu C-W, Lin S-G, Wang C-C, Lee K-Y. Time Series Analysis Using Composite Multiscale Entropy. Entropy 2013; 15(3): 1069-1084, https://doi.org/10.3390/e15031069.
- 37. Wu S-D, Wu C-W, Lin S-G, Lee K-Y, Peng C-K. Analysis of complex time series using refined composite multiscale entropy. Physics Letters A 2014; 378(20): 1369-1374, https://doi.org/10.1016/j.physleta.2014.03.034.
- 38. Yang Y, Zhang W-H, Ma Y-C, Wan M. Chatter prediction for the peripheral milling of thin-walled workpieces with curved surfaces. International Journal of Machine Tools and Manufacture 2016; 109:3 6-48, https://doi.org/10.1016/j.ijmachtools.2016.07.002.
- 39. Yuan Y, Jing X, Li H, Ehmann KF, Zhang D. Chatter detection based on wavelet coherence functions in micro-end-milling processes. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 2019; 233(9): 1934-1945, https://doi.org/10.1177/0954405418808214.
- 40. Yue C, Gao H, Liu X, Liang SY, Wang L. A review of chatter vibration research in milling. Chinese Journal of Aeronautics 2019; 32: 215-242, https://doi.org/10.1016/j.cja.2018.11.007.
- 41. Yusoff AR. Identifying bifurcation behavior during machining process for an irregular milling tool geometry. Measurement 2016; 93: 57-66, https://doi.org/10.1016/j.measurement.2016.07.001.
- 42. Zagórski I, Korpysa J, Weremczuk A. Influence of tool holder types on vibration in rough milling of AZ91D magnesium alloy. Materials 2021; 14(10): 1-17, https://doi.org/10.3390/ma14102517.
- 43. Zagórski I, Kulisz M, Kłonica M, Matuszak J. Trochoidal milling and neural networks simulation of magnesium alloys. Materials 2019; 12(13): 1-25, https://doi.org/10.3390/ma12132070.
- 44. Zawada-Michałowska M, Kuczmaszewski J, Pieśko P. Influence of pre-machining on post-machining deformation of thin-walled elements made of aluminium alloy EN AW-2024. IOP Conference Series: Materials Science and Engineering 2018; 393: 1-8, https://doi.org/10.1088/1757-899X/393/1/012100.
- 45. Zębala W, Słodki B, Struzikiewicz G. Productivity and reliability improvement in turning Inconel 718 alloy – case study. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2013; 15 (4): 421-426.
- 46. Zhang Y, Guo K, Sun J. Investigation on the milling performance of amputating clamping supports for machining with industrial robot. International Journal of Advanced Manufacturing Technology 2019; 100: 321-332, https://doi.org/10.1007/s00170-019-03341-w.
- 47. Zheng G, Sun W, Zhang H, Zhou Y, Gao C. Tool wear condition monitoring in milling process based on data fusion enhanced long shortterm memory network under different cutting conditions. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2021; 23 (4): 612-618, http://doi.org/10.17531/ein.2021.4.3.
- 48. Zhu Q, Sun W, Zhoua Y, Gao C. A tool wear condition monitoring approach for end milling based on numerical simulation. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2021; 23 (2): 371-380, http://doi.org/10.17531/ein.2021.2.17.
- 49. Zhuo Y, Han Z, An D, Jin H. Surface topography prediction in peripheral milling of thin-walled parts considering cutting vibration and material removal effect. International Journal of Mechanical Sciences 2021; 211: 106797, https://doi.org/10.1016/j.ijmecsci.2021.106797.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f1a23108-08c6-4d06-b4aa-ee3da512d30b