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Tool wear modelling using micro tool diameter reduction for micro-end-milling of tool steel H13

  • C. S. Manso
  • S. Thom
  • E. Uhlmann
  • C. L. F. de Assis
  • E. G. del ConteEmail author
ORIGINAL ARTICLE
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Abstract

Micro components have been demanded increasingly due to the global trend of miniaturization of products and devices. Micro milling is one of the most promising processes for micro-scale production and differs from conventional milling due to the size effect introducing phenomena like the minimum chip thickness, making the prediction of micro milling process hard. Among challenges in micro milling, tool life and tool wear can be highlighted. Understanding tool wear and modelling in micro milling is challenging and essential to maintaining the quality and geometric tolerances of workpieces. This work investigates how to model the diameter reduction of a tool caused by tool wear for micro milling of H13 tool steel. Machining experiments were carried out in order to obtain cutting parameters affecting tool wear by considering the diameter reduction. Dry full slot milling with TiAlN (titanium aluminium nitride)-coated micro tools of diameter d = 400 μm was performed. Three levels of feed per tooth (fz = 2 μm, 4 μm and 5 μm) and two spindle speed levels (n = 30,000 rpm and 46,000 rpm) were used and evaluated over a cutting length of lc = 1182 mm. The results show that lower levels of feed per tooth and spindle speed lead to higher tool wear with a total diameter reduction over 22%. The magnitude of the cutting parameters affecting tool wear was determined by ANOVA (analysis of variance), and the model validation meets the statistical requirements with a coefficient of determination R2 = 83.5% showing the feasibility of the approach to predict tool wear using diameter reduction modelling in micro milling.

Keywords

Tool wear Micro milling Full slot milling Machining parameters 

Notes

Funding information

This study was financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001" and the Deutsche Forschungsgemeinschaft (DFG) through the Bragecrim (Brazilian-German Collaborative Research Initiative on Manufacturing Technology) project Micro-O: Micro Milling Process Optimization.

References

  1. 1.
    Lu X, Jia Z, Wang H, Si L, Liu Y, Wu W (2016) Tool wear appearance and failure mechanism of coated carbide tools in micro-milling of Inconel 718 super alloy. Ind Lubr Tribol 68(2):267–277CrossRefGoogle Scholar
  2. 2.
    Kang IS, Kim JS, Kim JH, Kang MC, Seo YW (2007) A mechanistic model of cutting force in the micro end milling process. J Mater Process Technol 187–188:250–255CrossRefGoogle Scholar
  3. 3.
    Kuram E, Ozcelik B (2014) Micro milling. In: Davim JP (ed) Modern mechanical engineering - materials forming, machining and tribology. Springer International Publishing, Aveiro, pp 325–466Google Scholar
  4. 4.
    Ding H, Ibrahim R, Cheng K, Chen S (2010) Experimental study on machinability improvement of hardened tool steel using two dimensional vibration-assisted micro-end-milling. Int J Mach Tools Manuf 50:1115–1118CrossRefGoogle Scholar
  5. 5.
    Pal S, Heyns PS, Freyer BH, Theron NJ, Pal SK (2011) Tool wear monitoring and selection of optimum cutting conditions with progressive tool wear effect and input uncertainties. J Intell Manuf 22:491–504CrossRefGoogle Scholar
  6. 6.
    Campos MA, Mewis J, Del Conte EG (Sep. 2017) In-situ magnetic inspection of the part fixture and the residual stress in micromilled hot-work tool steel. NDT E Int 90:33–38CrossRefGoogle Scholar
  7. 7.
    Teng X, Huo D, Shyha I, Chen W, Wong E (2018) An experimental study on tool wear behaviour in micro milling of nano Mg / Ti metal matrix composites. Int J Adv Manuf Technol 96:2127–2140CrossRefGoogle Scholar
  8. 8.
    Aramcharoen A, Mativenga PT (2009) Size effect and tool geometry in micromilling of tool steel. Precis Eng J 33:402–407CrossRefGoogle Scholar
  9. 9.
    Lai X, Li H, Li C, Lin Z, Ni J (2008) Modelling and analysis of micro scale milling considering size effect , micro cutter edge radius and minimum chip thickness. Int J Mach Tools Manuf 48:1–14CrossRefGoogle Scholar
  10. 10.
    Liu X, Devor RE, Kapoor SG (2016) An analytical model for the prediction of minimum chip thickness in micromachining. J Manuf Sci Eng 128:474–481CrossRefGoogle Scholar
  11. 11.
    Cheng K (2009) Machining dynamics - fundamentals, applications and practices. Springe, LondonCrossRefGoogle Scholar
  12. 12.
    Afazov SM, Zdebski D, Ratchev SM, Segal J, Liu S (2013) Effects of micro-milling conditions on the cutting forces and process stability. J Mater Process Technol 213:671–684CrossRefGoogle Scholar
  13. 13.
    Li H, Lai X, Li C, Feng J, Ni J (2008) Modelling and experimental analysis of the effects of tool wear , minimum chip thickness and micro tool geometry on the surface roughness in micro-end-milling. J Micromech Microeng 18:12ppGoogle Scholar
  14. 14.
    Kiswanto G, Zariatin DL, Ko TJ (2014) The effect of spindle speed , feed-rate and machining time to the surface roughness and burr formation of Aluminum Alloy 1100 in micro-milling operation. J Manuf Process 16:435–450CrossRefGoogle Scholar
  15. 15.
    Ucun I, Aslantas K, Bedir F (2013) An experimental investigation of the effect of coating material on tool wear in micro milling of Inconel 718 super alloy. Wear J 300:8–19CrossRefGoogle Scholar
  16. 16.
    Lee K, Dornfeld DA (2005) Micro-burr formation and minimization through process control. Precis Eng 29:246–252CrossRefGoogle Scholar
  17. 17.
    Zhu K, Yu X (2017) The monitoring of micro milling tool wear conditions by wear area estimation. Mech Syst Signal Process 93:80–91CrossRefGoogle Scholar
  18. 18.
    Uhlmann E, Kuche Y, Polte J, Polte M (2018) Influence of cutting edge micro-geometry in micro-milling of copper alloys with reduced lead content. Procedia CIRP 77(Hpc):662–665CrossRefGoogle Scholar
  19. 19.
    Oliaei SNB, Karpat I (2016) Influence of tool wear on machining forces and tool deflections during micro milling. Int J Adv Manuf Technol 84(9–12):1963–1980CrossRefGoogle Scholar
  20. 20.
    Alhadeff LL, Marshall MB, Curtis DT, Slatter T (2019) Protocol for tool wear measurement in micro-milling. Wear 421(December 2018):54–67CrossRefGoogle Scholar
  21. 21.
    Saedon JB, Soo SL, Aspinwall DK, Barnacle A, Saad NH (2012) Prediction and optimization of tool life in micromilling AISI D2 ( ~ 62 HRC ) hardened steel. Int Symp Robot Intell Sensors 41:1674–1683Google Scholar
  22. 22.
    Wang C, Huang M, Chung TT, Young HT, Li KM (2017) Tool condition monitoring with current signals for a low-power spindle. In: International Conference on Applied System Innovation, pp 686–689Google Scholar
  23. 23.
    Wang W, Kweon SH, Yang SH (2005) A study on roughness of the micro-end-milled surface produced by a miniatured machine tool. J Mater Process Technol 163:702–708CrossRefGoogle Scholar
  24. 24.
    Kuram E, Ozcelik B (2015) Effects of tool paths and machining parameters on the performance in micro-milling of Ti6Al4V titanium with high-speed spindle attachment. Int J Adv Manuf Technol (1–4):691–703Google Scholar
  25. 25.
    Kuram E, Ozcelik B (2015) Optimization of machining parameters during micro-milling of Ti6Al4V titanium alloy and Inconel 718 materials using Taguchi method. J Eng Manuf 231(2):1–15Google Scholar
  26. 26.
    do Santos AG, Silva MBD, Jackson MJ (2018) Tungsten carbide micro-tool wear when micro milling UNS S32205 duplex stainless steel. Wear 414–415:109–117CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  • C. S. Manso
    • 1
  • S. Thom
    • 2
  • E. Uhlmann
    • 2
  • C. L. F. de Assis
    • 3
  • E. G. del Conte
    • 1
    Email author
  1. 1.Federal University of the ABCSanto AndréBrazil
  2. 2.Institut für Werkzeugmaschinen und FabrikbetriebTU BerlinBerlinGermany
  3. 3.Federal Institute of São PauloVotuporangaBrazil

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