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Harmonic-based-on analysis to discriminate different mechanical actions involved in the machining of hard-to-cut materials

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Abstract

Cutting force monitoring may be established as a functional control system for machining processes, helping determine the optimal time for tool change since a relationship between tool wear and milling forces exists. However, these forces result from various effect, including chip removal, friction, and vibrations. Predicting the end of functional tool life becomes challenging due to these complex interactions. In this study, it is proposed a decomposed action methodology based on force analysis using the fast Fourier transform and harmonic analysis. In pursuit of a comprehensive understanding of cutting forces during milling process, it is proposed a methodology to capture the signal given by a rotary dynamometer in selective cutting tests directed to discriminate and isolate external friction and other effects. The methodology has been tuned for slot milling of Ti48Al2Cr2Nb titanium aluminide using a single uncoated tungsten carbide insert, under different combinations of depth of cut and feed per tooth, for a fixed cutting speed value. The friction force in the tool flank zone has been demonstrated as the main action due to the small chip section removed, which leads to explain the rapid tool wear in titanium aluminides machining. Friction coefficients ranging from 0.412 to 0.579 have been found in real cutting conditions. This methodology will allow the evaluation of different tool geometries to reduce tool-workpiece friction and wear phenomena, enhancing the tool life.

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Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

References

  1. Peng Y, Song Q, Wang R et al (2024) A tool wear condition monitoring method for non-specific sensing signals. Int J Mech Sci 263:108769. https://doi.org/10.1016/j.ijmecsci.2023.108769

    Article  Google Scholar 

  2. Wang Y, Gao G, Zhang K et al (2024) Modelling of tribological behavior and wear for micro-textured surfaces of Ti2AlNb intermetallic compounds machined with multi-dimensional ultrasonic vibration assistance. Tribol Int 191:109167. https://doi.org/10.1016/j.triboint.2023.109167

    Article  Google Scholar 

  3. Jiang B, Li F, Zhao P et al (2024) Cross-scale identification method for friction damage on the tool flank of high-feed milling cutter. Int J Adv Manuf Technol. https://doi.org/10.1007/s00170-024-13122-9

    Article  Google Scholar 

  4. Gao S, Duan X, Zhu K, Zhang Y (2024) Investigation of the tool flank wear influence on cutter-workpiece engagement and cutting force in micro milling processes. Mech Syst Signal Process 209:111104. https://doi.org/10.1016/j.ymssp.2024.111104

    Article  Google Scholar 

  5. García-Martínez E, Miguel V, Martínez-Martínez A et al (2022) Optimization of the dry turning process of Ti48Al2Cr2Nb aluminide based on the cutting tool configuration. Materials (Basel) 15:1472. https://doi.org/10.3390/ma15041472

    Article  Google Scholar 

  6. Wang Z, Liu Y (2020) Study of surface integrity of milled gamma titanium aluminide. J Manuf Process 56:806–819. https://doi.org/10.1016/j.jmapro.2020.05.021

    Article  Google Scholar 

  7. Cai L, Feng Y, Liang SY (2024) Analytical modelling of cutting force in end-milling with minimum quantity lubrication. Int J Precis Eng Manuf 25:899–912. https://doi.org/10.1007/s12541-023-00837-0

    Article  Google Scholar 

  8. Priarone PC, Klocke F, Faga MG et al (2016) Tool life and surface integrity when turning titanium aluminides with PCD tools under conventional wet cutting and cryogenic cooling. Int J Adv Manuf Technol 85:807–816. https://doi.org/10.1007/s00170-015-7958-5

    Article  Google Scholar 

  9. García-Martínez E, Miguel V, Martínez-Martínez A et al (2019) Sustainable lubrication methods for the machining of titanium alloys: an overview. Materials (Basel) 12:3852. https://doi.org/10.3390/ma12233852

    Article  Google Scholar 

  10. Akıncıoğlu S, Gökkaya H, Uygur İ (2016) The effects of cryogenic-treated carbide tools on tool wear and surface roughness of turning of Hastelloy C22 based on Taguchi method. Int J Adv Manuf Technol 82:303–314. https://doi.org/10.1007/s00170-015-7356-z

    Article  Google Scholar 

  11. Akıncıoğlu G (2021) Investigation of the effect of cryogenic treatment cubic boron nitride turning insert tools. J Mater Eng Perform 30:1280–1288. https://doi.org/10.1007/s11665-021-05453-5

    Article  Google Scholar 

  12. García-Martínez E, Miguel V, Martínez-Martínez A (2024) Economic analysis of eco-friendly lubrication strategies for the machining of Ti48Al2Cr2Nb aluminide. J Clean Prod 435:140541. https://doi.org/10.1016/j.jclepro.2023.140541

    Article  Google Scholar 

  13. Nassef BG, Pape F, Poll G et al (2024) Evaluating the tribological behaviour in cutting operations using a modified ball-on-disc open tribotester. Lubricants 12:77. https://doi.org/10.3390/lubricants12030077

    Article  Google Scholar 

  14. García-Martínez E, Miguel V, Martínez A et al (2021) Tribological characterization of tribosystem Ti48Al2Cr2Nb-coated/uncoated carbide tools at different temperatures. Wear 484–485:203992. https://doi.org/10.1016/j.wear.2021.203992

    Article  Google Scholar 

  15. Banerjee N, Sharma A (2016) Development of a friction model and its application in finite element analysis of minimum quantity lubrication machining of Ti-6Al-4 V. J Mater Process Technol 238:181–194. https://doi.org/10.1016/j.jmatprotec.2016.07.017

    Article  Google Scholar 

  16. Wang Z, Liang Y, Li H, Yu T (2022) Milling force and tool wear mechanisms on milling TC21 titanium alloy under different lubrication conditions. Int J Adv Manuf Technol 123:169–185. https://doi.org/10.1007/s00170-022-10108-3

    Article  Google Scholar 

  17. Du F, Zhou T, Tian P, et al (2024) Cutting performance and cutting fluid infiltration characteristics into tool-chip interface during MQL milling. Meas J Int Meas Confed 225. https://doi.org/10.1016/j.measurement.2023.113989

  18. Chauhan S, Trehan R, Singh RP (2023) State of the art in finite element approaches for milling process: a review. Adv Manuf 11:708–751. https://doi.org/10.1007/s40436-022-00417-x

    Article  Google Scholar 

  19. Ma L, Mao X, Li C et al (2024) Study on friction reduction performance of granular flow lubrication during the milling of Inconel 718 superalloy. Ind Lubr Tribol. https://doi.org/10.1108/ILT-12-2023-0386

    Article  Google Scholar 

  20. Sato R, Noguchi S, Hokazono T et al (2020) Time domain coupled simulation of machine tool dynamics and cutting forces considering the influences of nonlinear friction characteristics and process damping. Precis Eng 61:103–109. https://doi.org/10.1016/j.precisioneng.2019.10.010

    Article  Google Scholar 

  21. Lu Y, Ma H, Zhang Z et al (2024) Real-time chatter detection based on fast recursive variational mode decomposition. Int J Adv Manuf Technol 130:3275–3289. https://doi.org/10.1007/s00170-023-12832-w

    Article  Google Scholar 

  22. Ejiofor Matthew D, Shi J, Hou M, Cao H (2024) Improved STFT analysis using time-frequency masking for chatter detection in the milling process. Meas J Int Meas Confed 225:113899. https://doi.org/10.1016/j.measurement.2023.113899

    Article  Google Scholar 

  23. Perrelli M, Cosco F, Gagliardi F, Mundo D (2022) In-process chatter detection using signal analysis in frequency and time-frequency domain. Machines 10(1). https://doi.org/10.3390/machines10010024

  24. Katamba Mpoyi D, Ekuakille AL, Ugwiri MA et al (2024) Wear monitoring based on vibration measurement during machining: an application of FDM and EMD. Meas Sensors 32:101051. https://doi.org/10.1016/j.measen.2024.101051

    Article  Google Scholar 

  25. Kouguchi J, Yoshioka H (2024) Monitoring method of cutting forces and vibrations by using frequency separation of acceleration sensor signals during milling process with small ball end mills. Precis Eng 85:337–356. https://doi.org/10.1016/j.precisioneng.2023.10.013

    Article  Google Scholar 

  26. Mammadov B, Mohammadi Y, Farahani ND, Altintas Y (2024) A unified FFT-based mechanistic force coefficient identification model for isotropic and anisotropic materials. CIRP J Manuf Sci Technol 49:216–229. https://doi.org/10.1016/j.cirpj.2024.01.009

    Article  Google Scholar 

  27. San-Juan M, Martín Ó, Santos F (2010) Experimental study of friction from cutting forces in orthogonal milling. Int J Mach Tools Manuf 50:591–600. https://doi.org/10.1016/j.ijmachtools.2010.03.013

    Article  Google Scholar 

  28. Castellanos S, Alves JL (2018) A review of milling of gamma titanium aluminides. Porto J Eng 3:1–9. https://doi.org/10.24840/2183-6493_003.002_0001

    Article  Google Scholar 

  29. Hussain A, Layegh SE, Lazoglu I et al (2020) Mechanics of milling 48–2-2 gamma titanium aluminide. CIRP J Manuf Sci Technol 30:131–139. https://doi.org/10.1016/j.cirpj.2020.05.001

    Article  Google Scholar 

  30. Hood R, Aspinwall DK, Soo SL et al (2014) Workpiece surface integrity when slot milling γ-TiAl intermetallic alloy. CIRP Ann - Manuf Technol 63:53–56. https://doi.org/10.1016/j.cirp.2014.03.071

    Article  Google Scholar 

  31. Anwar S, Ahmed N, Pervaiz S et al (2020) On the turning of electron beam melted gamma-TiAl with coated and uncoated tools: a machinability analysis. J Mater Process Technol 282:116664. https://doi.org/10.1016/j.jmatprotec.2020.116664

    Article  Google Scholar 

  32. Beranoagirre A, Urbikain G, Marticorena R et al (2019) Sensitivity analysis of tool wear in drilling of titanium aluminides. Metals (Basel) 9:297. https://doi.org/10.3390/met9030297

    Article  Google Scholar 

  33. Beranoagirre A, Urbikain G, Calleja A, López de Lacalle L (2018) Drilling process in γ-TiAl intermetallic alloys. Materials (Basel) 11:2379. https://doi.org/10.3390/ma11122379

    Article  Google Scholar 

  34. Cheng J, Yang J, Zhang X et al (2012) High temperature tribological behavior of a Ti-46Al-2Cr-2Nb intermetallics. Intermetallics 31:120–126. https://doi.org/10.1016/j.intermet.2012.06.013

    Article  Google Scholar 

  35. Rastkar AR, Bell T (2005) Characterization and tribological performance of oxide layers on a gamma based titanium aluminide. Wear 258:1616–1624. https://doi.org/10.1016/j.wear.2004.11.014

    Article  Google Scholar 

  36. Yao C, Lin J, Wu D, Ren J (2018) Surface integrity and fatigue behavior when turning γ-TiAl alloy with optimized PVD-coated carbide inserts. Chinese J Aeronaut 31:826–836. https://doi.org/10.1016/j.cja.2017.06.002

    Article  Google Scholar 

  37. Wang X, Zhao B, Ding W et al (2024) Wear mechanisms of coated carbide tools during high-speed face milling of Ti2AlNb intermetallic alloys. Int J Adv Manuf Technol 131:2881–2892. https://doi.org/10.1007/s00170-023-12616-2

    Article  Google Scholar 

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Funding

The authors received financial support from the European Commission (FEDER Funds) for the projects EQC2019-006644-P and 2023-GRIN-34346 and the Regional Government of Castilla-La Mancha for the project SBPLY/23/180225/000132.

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Authors and Affiliations

  1. Regional Development Institute of Castilla-La Mancha, Castilla-La Mancha, Spain

    Enrique García-Martínez, Valentín Miguel & Alberto Martínez-Martínez

  2. Higher Technical School of Industrial Engineering of Albacete, Albacete, Spain

    Enrique García-Martínez, Alberto Molina-Yagüe & Valentín Miguel

Authors
  1. Enrique García-Martínez
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  2. Alberto Molina-Yagüe
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  3. Valentín Miguel
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Correspondence to Enrique García-Martínez.

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García-Martínez, E., Molina-Yagüe, A., Miguel, V. et al. Harmonic-based-on analysis to discriminate different mechanical actions involved in the machining of hard-to-cut materials. Int J Adv Manuf Technol (2024). https://doi.org/10.1007/s00170-024-13773-8

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