Skip to main content

Modelling and simulation of controlled depth abrasive water jet machining (AWJM) for roughing passes of free-form surfaces

The International Journal of Advanced Manufacturing Technology volume 114, pages 3581–3596 (2021)Cite this article

Abstract

Controlled depth abrasive waterjet machining (AWJM) is an unconventional and promising process for materials introducing challenges in conventional machining for high value manufacturing (HVM) industries such as aerospace and automotive. In such applications, waterjet acts as a flexible cutting tool compared to conventional milling. The kerf profile, i.e. the removed material volume, nonlinearly depends on the process parameters such as water pressure, jet traverse speed, abrasive rate, and stand-off-distance unlike the deterministic case in mechanical milling. Thus, prediction of kerf profile, i.e. width, depth, and shape, is of great importance for accurate and efficient process development and tool path generation in AWJM. In this paper, a novel analytical model is proposed for prediction of kerf profile, relying on conservation of energy and momentum, where the material removal is related to the machinability number of the workpiece material, so that the requirement of calibration tests is eliminated. Then, the proposed AWJM process model is used in a framework to predict 3D in-process workpiece (IPW) geometry, which is represented using signed distance field (SDF) approach. The process model is verified by experimental results with an average error of 15%, where the machine profiles are measured by confocal optical microscopy. In some of the experiments, undulated material removal was observed which is due to inconsistent abrasive supply of the system, which is considered to be the major source of the kerf depth prediction errors. The IPW simulation model is verified by variable jet traverse speed AWJM experiments, considering the significant effect of jet traverse speed on the kerf depth. The machined specimens are sectioned along the jet traverse direction and the cross section of the test pieces is visually compared with the simulations. The machined profiles introduced some amount of undulated profile, which may be attributed to the non-consistent abrasive supply in the system. It is shown that the proposed IPW simulation approach demonstrates a reasonable accuracy to plan controlled depth AWJM processes.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Data availability

Not applicable

References

  1. Konig W, Cronjager L, Spur G, H-K T, Vigneau M, Zdeblick WJ (1991) Machining of new materials. Process. Adv. Mater. 1:11–26

    Google Scholar 

  2. Lauwers B, Klocke F, Klink A, Tekkaya AE, Neugebauer R, Mcintosh D (2014) Hybrid processes in manufacturing. CIRP Annals 63(2):561–583

    Article  Google Scholar 

  3. Kong MC, Srinivasu D, Axinte D, Voice W, McGourlay J, Hon B (2013) On geometrical accuracy and integrity of surfaces in multi-mode abrasive waterjet machining of NiTi shape memory alloys. CIRP Annals. 62(1):555–558

    Article  Google Scholar 

  4. Axinte DA, Karpuschewski B, Kong MC, Beaucamp AT, Anwar S, Miller D, Petzel M (2014) High energy fluid jet machining (HEFJet-Mach): from scientific and technological advances to niche industrial applications. CIRP Annals 63(2):751–771

    Article  Google Scholar 

  5. Liao Z, Sanchez I, Xu D, Axinte D, Augustinavicius G, Wretland A (2020) Dual-processing by abrasive waterjet machining–a method for machining and surface modification of nickel-based superalloy. Journal of Materials Processing Technology 285:116768

  6. Matsumura T, Muramatsu T, Fueki S (2011) Abrasive water jet machining of glass with stagnation effect. CIRP Annals 60(1):355–358

    Article  Google Scholar 

  7. Siores E, Wong WCK, Chen L, Wager JG (1996) Enhancing abrasive waterjet cutting of ceramics by head oscillation techniques. CIRP Annals 45(1):327–330

    Article  Google Scholar 

  8. Wei H, Peng C, Gao H, Wang X, Wang X (2019) On establishment and validation of a new predictive model for material removal in abrasive flow machining. International Journal of Machine Tools and Manufacture 138:66–79

    Article  Google Scholar 

  9. Momber, A. W., & Kovacevic, R. (2012). Principles of abrasive water jet machining. Springer Science & Business Media.

    MATH  Google Scholar 

  10. Fowler G, Shipway P, Pashby I (2005) Abrasive water-jet controlled depth milling of Ti6Al4V alloy–an investigation of the role of jet–workpiece traverse speed and abrasive grit size on the characteristics of the milled material. Journal of Materials Processing Technology. 161:407–414

    Article  Google Scholar 

  11. Azmir MA, Ahsan AK (2009) A study of abrasive water jet machining process on glass/epoxy composite laminate. Journal of Materials Processing Technology 209(20):6168–6173

    Article  Google Scholar 

  12. Löschner P, Jarosz K, Niesłony P (2016) Investigation of the effect of cutting speed on surface quality in abrasive water jet cutting of 316L stainless steel. Procedia Engineering 149:276–282

    Article  Google Scholar 

  13. Shukla R, Singh D (2017) Experimentation investigation of abrasive water jet machining parameters using Taguchi and Evolutionary optimization techniques. Swarm and Evolutionary Computation 32:167–183

    Article  Google Scholar 

  14. Uthayakumar M, Khan MA, Kumaran ST, Slota A, Zajac J (2016) Machinability of nickel-based superalloy by abrasive water jet machining. Materials and Manufacturing Processes 31(13):1733–1739

    Article  Google Scholar 

  15. Wang S, Zhang S, Wu Y, Yang F (2017) Exploring kerf cut by abrasive waterjet. The International Journal of Advanced Manufacturing Technology 93(5-8):2013–2020

    Article  Google Scholar 

  16. Yuvaraj N, Kumar MP (2017) Investigation of process parameters influence in abrasive water jet cutting of D2 steel. Materials and Manufacturing Processes 32(2):151–161

    Article  Google Scholar 

  17. Finnie I (1960) Erosion of surfaces by solid particles. Wear. 3:87–103

    Article  Google Scholar 

  18. Bitter JJW (1963) A study of erosion phenomena: Part I. Wear. 6:5–21

    Article  Google Scholar 

  19. Bitter JGA (1963) A study of erosion phenomena: Part II. Wear 6(3):169–190

    Article  Google Scholar 

  20. Hashish M, Du Plessis M (1979) Prediction equations relating high velocity jet cutting performance to stand off distance and multi-passes. Journal of Engineering for industry 101:311–318

    Article  Google Scholar 

  21. Tazibt A, Parsy F, Abriak N (1996) Theoretical analysis of the particle acceleration process in abrasive water jet cutting. Computational Materials Science 5:243–254

    Article  Google Scholar 

  22. Capello E, Groppetti R (1992) On an energetic semi-empirical model of hydro-abrasive jet material removal mechanism for control and optimization. In: Jet cutting technology. Springer, Dordrecht, pp 101–120

    Chapter  Google Scholar 

  23. Raju SP, Ramulu M (1994) Predicting hydro-abrasive erosive wear during abrasive waterjet cutting: Part II-experimental study and model verification. ASME-PUBLICATIONS-PED 68:381–381

    Google Scholar 

  24. Momber AW, Kovacevic R (1999) An energy balance of high-speed abrasive water jet erosion. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology 213(6):463–472

    Article  Google Scholar 

  25. Hoogstrate AM, Karpuschewski B, Van Luttervelt CA, Kals HJJ (2002) Modelling of high velocity, loose abrasive machining processes. CIRP Annals. 51(1):263–266

    Article  Google Scholar 

  26. EITobgy M, Ng EG, Elbestawi MA (2005) Modelling of abrasive waterjet machining: a new approach. CIRP Annals. 54(1):285–288

    Article  Google Scholar 

  27. Pi VN, Tuan NQ (2009) Necessary cutting energy in abrasive waterjet machining. In: Advanced Materials Research, vol 76. Trans Tech Publications Ltd, pp 351–356

  28. Ahmed DH, Naser J, Deam RT (2016) Particles impact characteristics on cutting surface during the abrasive water jet machining: numerical study. Journal of materials processing technology 232:116–130

    Article  Google Scholar 

  29. Axinte DA, Srinivasu DS, Billingham J, Cooper M (2010) Geometrical modelling of abrasive waterjet footprints: a study for 90 jet impact angle. CIRP Annals 59(1):341–346

    Article  Google Scholar 

  30. Billingham J, Miron CB, Axinte DA, Kong MC (2013) Mathematical modelling of abrasive waterjet footprints for arbitrarily moving jets: Part II—Overlapped single and multiple straight paths. International Journal of Machine Tools and Manufacture 68:30–39

    Article  Google Scholar 

  31. Gilles P, Sultan T, Cohen G, Rubio W (2017) A new cutting depth model with rapid calibration in abrasive water jet machining of titanium alloy. The International Journal of Advanced Manufacturing Technology 93(5-8):1499–1512

    Article  Google Scholar 

  32. Anwar S, Axinte DA, Becker AA (2013) Finite element modelling of overlapping abrasive waterjet milled footprints. Wear 303(1-2):426–436

    Article  Google Scholar 

  33. Kumar N, Shukla M (2012) Finite element analysis of multi-particle impact on erosion in abrasive water jet machining of titanium alloy. Journal of Computational and Applied Mathematics 236(18):4600–4610

    Article  Google Scholar 

  34. Altintas Y, Kersting P, Biermann D, Budak E (2014) Virtual process systems for part machining operations. CIRP Annals 63(2):585–605

    Article  Google Scholar 

  35. Jones MW, Bærentzen JA, Sramek M (2006) 3D distance fields: a survey of techniques and applications. IEEE Trans. Visual. Computer Graphics. 12:581–599

    Article  Google Scholar 

  36. Jamriška O., Havran V. (2010) Interactive ray tracing of distance fields, in: Proc. 14th Cent. Eur. Semin. Comput. Graph., Wien.

  37. Sullivan A, Erdim H, Perry RN, Frisken SF (2012) High accuracy NC milling simulation using composite adaptively sampled distance fields. Computer. Aided Des. 44:522–536

    Article  Google Scholar 

  38. Hashish M (2013) Waterjet machining process. Handbook of Manufacturing Engineering Technology:1–30

  39. Xu M, Thompson PM, Toga AW (2004) An adaptive level set segmentation on a triangulated mesh. IEEE Transactions on Medical imaging 23(2):191–201

    Article  Google Scholar 

  40. Wu Y, Man J, Xie Z (2014) A double layer method for constructing signed distance fields from triangle meshes. Graphical models 76(4):214–223

    Article  Google Scholar 

  41. Chang, B., Cha, D., & Ihm, I. (2008). Computing local signed distance fields for large polygonal models. In Computer Graphics Forum (Vol. 27, 3, pp. 799-806). Oxford, UK: Blackwell Publishing Ltd.

    Google Scholar 

  42. Yu H, Xie J, Ma KL, Kolla H, Chen JH (2015) Scalable parallel distance field construction for large-scale applications. IEEE transactions on visualization and computer graphics 21(10):1187–1200

    Article  Google Scholar 

  43. Pal VK, Choudhury SK (2014) Fabrication and analysis of micro-pillars by abrasive water jet machining. Procedia materials science 6:61–71

    Article  Google Scholar 

Download references

Code availability

Not applicable.

Funding

This study is funded by The Scientific and Technological Research Council or Turkey (TUBITAK) under grant 217M704.

Author information

Authors and Affiliations

  1. Integrated Manufacturing Research and Application Centre, Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey

    Yigit Ozcan, Lutfi Taner Tunc & Beril Cetin

  2. Faculty of Mechanical Engineering, Czech Technical University, Horská 3, 128 00, Praha 2, Czech Republic

    Jan Kopacka & Matej Sulitka

Authors
  1. Yigit Ozcan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lutfi Taner Tunc
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jan Kopacka
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Beril Cetin
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Matej Sulitka
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed in the process of critical literature review. All author contributed in writing and revising the manuscript. Specifically, Yigit Ozcan contributed to the development of kerf geometry prediction model. Taner Tunc contributed to integration of the kerf geometry model with the 3D workpiece simulation model, experimental studies. Beril Cetin contributed to the experimental studies. Jan Kopacka contributed to preparation of the 3D workpiece simulation model for AWJM simulation. Matej Sulitka contributed to the evaluation of the simulation and experimental results.

Corresponding author

Correspondence to Lutfi Taner Tunc.

Ethics declarations

Ethical approval

The manuscript in part or in full has not been submitted or published anywhere. The manuscript will not be submitted elsewhere until the editorial process is completed.

Consent to participate

Not applicable.

Consent to publish

The author transfers to Springer the non-exclusive publication rights.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ozcan, Y., Tunc, L.T., Kopacka, J. et al. Modelling and simulation of controlled depth abrasive water jet machining (AWJM) for roughing passes of free-form surfaces. Int J Adv Manuf Technol 114, 3581–3596 (2021). https://doi.org/10.1007/s00170-021-07131-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-021-07131-1

Keywords

  • Waterjet Machining
  • Workpiece
  • Simulation