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Instrumented clamping device and numerical simulations to study machining distortion

  • Iheb CherifEmail author
  • Dominique Cotton
  • Gerard Poulachon
  • Jose Outeiro
  • Alexandre Brosse
  • Joana Rebelo Kornmeier
ORIGINAL ARTICLE
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Abstract

Machining part distortion is due to residual stresses induced by previous manufacturing processes. This study aims to evaluate the influence of machining conditions on AISI 316L plate distortion. Therefore, a special experimental device with force sensors integrated in the clamping system and numerical model of distortion were developed. Residual stresses due to previous machining processes were measured using a layer removal method and neutron diffraction technique. Then, distributions of these residual stresses were integrated in a developed model of machining distortion, which considers the clamping and machining sequence effects after each stage of the toolpath. A comparison of the experimental and numerical results revealed that the finite element method can adequately predict machining distortion. The results also suggest that clamping and machining sequence can affect part distortion.

Keywords

Machining Residual stresses Part distortion Numerical simulation 

Notes

Funding information

This research was financially supported by the Burgundy regional council of Bourgogne-Franche-Comte through the Regional Action Plan for Innovation, the European Union through the PO FEDER-FSE Bourgogne 2014/2020 programs, and FRAMATOME.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. 1.
    Pra F, Tochon P, Mauget C, Fokkens J, Willemsen S (2008) Promising designs of compact heat exchangers for modular HTRs using the Brayton cycle. Nucl Eng Des 238(11):3160–3173CrossRefGoogle Scholar
  2. 2.
    Xiuqing L, Le Pierres R, Dewson SJ (2006) Heat exchangers for the next generation of nuclear reactors. American Nuclear Society - ANS, United StatesGoogle Scholar
  3. 3.
    Mannan MA, Sollie JP (1997) A force-controlled clamping element for intelligent fixturing. CIRP Ann 46(1):265–268CrossRefGoogle Scholar
  4. 4.
    Boerma JR, Kals HJJ (1989) Fixture design with FIXES: the automatic selection of positioning, clamping and support features for prismatic parts. CIRP Ann 38(1):399–402CrossRefGoogle Scholar
  5. 5.
    Raghu A, Melkote SN (2004) Analysis of the effects of fixture clamping sequence on part location errors. Int J Mach Tools Manuf 44(4):373–382CrossRefGoogle Scholar
  6. 6.
    Wu NH, Chan KC (1996) A genetic algorithm based approach to optimal fixture configuration. Comput Ind Eng 31(3–4):919–924CrossRefGoogle Scholar
  7. 7.
    Rai JK, Xirouchakis P (2008) Finite element method based machining simulation environment for analyzing part errors induced during milling of thin-walled components. Int J Mach Tools Manuf 48(6):629–643CrossRefGoogle Scholar
  8. 8.
    Richter-Trummer V, Koch D, Witte A, dos Santos JF, de Castro PMST (2013) Methodology for prediction of distortion of workpieces manufactured by high speed machining based on an accurate through-the-thickness residual stress determination. Int J Adv Manuf Technol 68(9):2271–2281CrossRefGoogle Scholar
  9. 9.
    Cerutti X, Mocellin K, Hassini S, Blaysat B, Duc E (2017) Methodology for aluminium part machining quality improvement considering mechanical properties and process conditions. CIRP J Manuf Sci Technol 18:18–38CrossRefGoogle Scholar
  10. 10.
    Li B, Melkote SN (1999) Improved workpiece location accuracy through fixture layout optimization. Int J Mach Tools Manuf 39(6):871–883CrossRefGoogle Scholar
  11. 11.
    Asante JN (2008) A combined contact elasticity and finite element-based model for contact load and pressure distribution calculation in a frictional Workpiece-fixture system. Int J Adv Manuf Technol 39(5–6):578–588CrossRefGoogle Scholar
  12. 12.
    Siebenaler SP, Melkote SN (2006) Prediction of workpiece deformation in a fixture system using the finite element method. Int J Mach Tools Manuf 46(1):51–58CrossRefGoogle Scholar
  13. 13.
    Rai JK, Xirouchakis P (2009) FEM-based prediction of workpiece transient temperature distribution and deformations during milling. Int J Adv Manuf Technol 42(5–6):429–449CrossRefGoogle Scholar
  14. 14.
    Committee AIH, Douthett J (1991) ASM handbook: heat treating. ASM InternationalGoogle Scholar
  15. 15.
    Wawszczak R, Baczma A, Braham C, Berent K (2016) Evolution of microstructure and residual stress during annealing of austenitic and ferritic steels, Materials Characterization, p 14Google Scholar
  16. 16.
    Totten GE (2002) Handbook of residual stress and deformation of steel. ASM InternationalGoogle Scholar
  17. 17.
    Hospers F, Vogelesang LB (1975) Determination of residual stresses in aluminum-alloy sheet material. Exp Mech 15(3):107–110CrossRefGoogle Scholar
  18. 18.
    Yang Y, Li M, Li KR (2014) Comparison and analysis of main effect elements of machining distortion for aluminum alloy and titanium alloy aircraft monolithic component. Int J Adv Manuf Technol 70(9–12):1803–1811CrossRefGoogle Scholar
  19. 19.
    Laracine M, Bignon C, Boivin M, Lormand M, Geslot R (1986) Residual stresses measurements in plates by electrochemical machining of fine layers. CIRP Ann 35(1):409–412CrossRefGoogle Scholar
  20. 20.
    Javadi Y, Smith MC, Abburi Venkata K, Naveed N, Forsey AN, Francis JA, Ainsworth RA, Truman CE, Smith DJ, Hosseinzadeh F, Gungor S, Bouchard PJ, Dey HC, Bhaduri AK, Mahadevan S (2017) Residual stress measurement round robin on an electron beam welded joint between austenitic stainless steel 316L(N) and ferritic steel P91. Int J Press Vessel Pip 154:41–57CrossRefGoogle Scholar
  21. 21.
    Dreier S, Denkena B (2014) Determination of residual stresses in plate material by layer removal with machine-integrated measurement. Proc CIRP 24:103–107CrossRefGoogle Scholar
  22. 22.
    Ekmekçi B, Ekmekçi N, Tekkaya AE, Erden A (2004) Residual stress measurement with layer removal method, Proceedings Of the First Cappadocia International Mechanical Engineering Symposium, 1, p. 9Google Scholar
  23. 23.
    Hofmann M, Gan W, Rebelo-Kornmeier J (2015) STRESS-SPEC: materials science diffractometer, Journal of large-scale research facilities JLSRF, 1Google Scholar
  24. 24.
    Brokmeier H-G, Gan WM, Randau C, Völler M, Rebelo-Kornmeier J, Hofmann M (2011) Texture analysis at neutron diffractometer STRESS-SPEC. Nucl Inst Methods Phys Res A 642:87–92CrossRefGoogle Scholar
  25. 25.
    Noyan IC, Cohen JB (2013) Residual stress: measurement by diffraction and interpretation. SpringerGoogle Scholar
  26. 26.
    Jiang W, Luo Y, Wang B, Woo W, Tu ST (2015) Neutron diffraction measurement and numerical simulation to study the effect of repair depth on residual stress in 316l stainless steel repair weld. J Press Vessel Technol 137(4):041406CrossRefGoogle Scholar
  27. 27.
    Rebelo-Kornmeier J, Hofmann M, Gan WM, Randau C, Braun K, Zeitelhack K, Defendi I, Krueger J, Faulhaber E, Brokmeier HG (2017) New developments of the materials science diffractometer STRESS-SPEC. Mater Sci Forum 905:151–156CrossRefGoogle Scholar

Copyright information

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

Authors and Affiliations

  • Iheb Cherif
    • 1
    Email author
  • Dominique Cotton
    • 1
  • Gerard Poulachon
    • 1
  • Jose Outeiro
    • 1
  • Alexandre Brosse
    • 2
  • Joana Rebelo Kornmeier
    • 3
  1. 1.Arts et Metiers ParisTech, LaBoMaP, UBFCClunyFrance
  2. 2.FRAMATOME, 10 rue Juliette RécamierLyon Cedex 06France
  3. 3.Heinz Maier-Leibnitz Zentrum (MLZ)Technische Universitaet MuenchenGarchingGermany

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