Skip to main content
Log in

Influence of the main technological parameters and material properties of the workpiece on the geometrical accuracy of the machined surface at wedm

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

Geometrical accuracy is currently one of the important parameters regarding the machined surfaces of components used in modern technical equipment. Even though the WEDM technology belongs to the precise final machining technologies, the most demanding requirements for the geometrical accuracy of the machined surface are not always met. These geometrical deviations consequently manifest themselves not only in the assembly of particular parts of the final product but also in their operation. In addition, errors of the geometrical accuracy of the machined surface also have negative effect on the serviceability of the finished parts and their overall service life. Even though these shortcomings are only minimally reflected in planar cuts, the production of circular profiles is a problem in particular. The important factors causing this poor quality are the technological parameters in combination with the specific physical and mechanical properties of the workpiece and wire electrode. Experimental research was therefore focused on identifying the influence of selected technological parameters and material properties of the workpiece on the size of geometrical deviations of the machined surface that occur at WEDM using CuZn37 wire electrode. In general, it is also a serious problem to maintain the prescribed geometrical tolerance of the machined surface in a narrow tolerance field. By exceeding it, the product becomes unsatisfactory. However, the problem is also achieved quality, which significantly exceeds the expected values. This essentially reduces productivity and worsens the economic efficiency of production. For this reason, it is ideal to achieve the exact required quality of the machined surface in terms of geometrical accuracy. Therefore, an algorithm of simulation software was proposed, which includes empirically determined mathematical models, based on which the software can predict the necessary setting of technological parameters, derived from the dimensional and material properties of the workpiece and wire. The mentioned solution thus will bring the geometrical accuracy of the production of circular holes in a narrow tolerance field to the customer’s requirements with a significant increase of the economic efficiency of production.

This is a preview of subscription content, log in via an institution to check access.

Access this article

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

Instant access to the full article PDF.

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
Fig. 17
Fig. 18
Fig. 19
Fig. 20

Similar content being viewed by others

Data Availability

All data is published with the paper.

Abbreviations

I :

Maximum peak current (A)

U :

Maximum electrical voltage (V)

t on :

Pulse on-time duration (μs)

t off :

Pulse off-time duration (μs)

A 1 :

Location of concentric circles with the center in C1,

A 2 :

Location of concentric circles with the center in C2,

H S :

Sample profile height (mm)

H PL :

Scanned line of the sample profile height (mm)

Fw :

Wire tension force (N)

C 1, C 2 :

Centers of circles

HSS:

High-speed steel

LSC:

Least squares mean circle

MTP:

Main technological parameters

MZC:

Minimum zone circles

MCC:

Minimum circumscribed circle

MIC:

Maximum inscribed circle

T :

Tolerance field

WEDM:

Wire electrical discharge machining

Δ :

Geometrical deviations of shape (μm)

Δ r1, Δ r2 :

Particular radial distances of the circles (mm)

y Ci :

Diameter of the workpiece profile (μm)

y Ci max/y Ci min :

Max./min. measured value of deviation (μm)

y Cmax/avg :

Measured value max./average deviations of circularity (μm)

λ :

Thermal conductivity (W.m−1.K−1)

κ :

Electrical conductivity (Siemens.m.mm−2)

ϕ E :

Wire electrode diameter (mm)

ϕ Ci :

Circle profile diameter (mm)

ϕ C1, ϕ C2 :

First/second measured value of the circle profile diameter (mm)

References

  1. Davis R et al (2020) A comparative study of EDD and PM-EDD in producing holes in Inconel 718 alloy. Key Eng Mat 833:48–53. https://doi.org/10.4028/www.scientific.net/KEM.833.48

    Article  Google Scholar 

  2. Sarma DK, Singh MA (2020) Machining of thin sections using multi-pass wire electrical discharge machining process. International journal of machining and machinability of materials 22(1):62–78. https://doi.org/10.1504/IJMMM.2020.10025678

    Article  Google Scholar 

  3. Islam MN, Rafai NH, Subramanian SS (2010) An investigation into dimensional accuracy achievable in wire-cut electrical discharge machining. In Proceedings of the World Congress on Engineering, WCE 2010, June 30 - July 2, 2010, London, U.K. III: 1-6

  4. Ali MY, Banu A, Salehan M, Adesta YET, Hazza M, Shaffiq M (2018) Dimensional accuracy in dry micro wire electrical discharge machining. Journal of Mechanical Engineering and Sciences 12(1):3321–3329

    Article  Google Scholar 

  5. Firouzabadi HA, Parvizian J, Abdullah A (2015) Improving accuracy of curved corners in wire EDM successive cutting. Int J Adv Manuf Technol 76:447–459. https://doi.org/10.1007/s00170-014-6270-0

    Article  Google Scholar 

  6. Yan MT, Wang PW, Lai JC (2016) Improvement of part straightness accuracy in rough cutting of wire EDM through a mechatronic system design. Int J Adv Manuf Technol 84:2623–2635. https://doi.org/10.1007/s00170-015-7908-2

    Article  Google Scholar 

  7. Sanchez JA, Rodil JL, Herrero A, De Lacalle LNL, Lamikiz A (2007) On the influence of cutting speed limitation on the accuracy of wire-EDM corner-cutting. JMater Process Technol 182(1-2):574–579. https://doi.org/10.1016/j.jmatprotec.2006.09.030

    Article  Google Scholar 

  8. Raksiri C, Chatchaikulsiri P (2010) CNC wire-cut parameter optimized determination of the stair shape workpiece. International Journal of Mechanical and Mechatronics Engineering 4(10):924–929. https://doi.org/10.5281/zenodo.1073331

    Article  Google Scholar 

  9. Puri AB, Bhattacharyya B (2003) An analysis and optimization of the geometrical in accuracy due to wire lag phenomenon in WEDM. Int. J. Mach. Tool. Manu. 43:151–159

    Article  Google Scholar 

  10. Zhang W, Wang X (2017) Simulation of the inventory cost for rotable spare with fleet size impact. Academic Journal of Manufacturing Engineering 15(4):124–132

    Google Scholar 

  11. Scott D, Boyina S, Rajurkar KP (1991) Analysis and optimization of parameter combination in wire electrical discharge machining. International Journal of Production Research 29:2189–2207

    Article  Google Scholar 

  12. Su JC, Kao JY, Tarng YS (2004) Optimization of the electrical discharge machining process using a GA-based neural network. J. Adv. Manuf. Tech. 24:81–90. https://doi.org/10.1007/s00170-003-1729-4

    Article  Google Scholar 

  13. Tarng YS, Ma SC, Chung LK (1995) Determination of optimal cutting parameters in wire electrical discharge machining. International Journal of Machine Tools and Manufacture 35:1435–1443

    Article  Google Scholar 

  14. Sarkar S, Sekh M, Mitra S, Bhattacharyya B (2007) Modeling and optimization of wire electrical discharge machining of γ-TiAl in trim cutting operation. Journal of Material Processing Technology 205:376–387. https://doi.org/10.1016/j.jmatprotec.2007.11.194

    Article  Google Scholar 

  15. Yan BH, Tsai HC, Huang FY, Lee LC (2005) Examination of wire electrical discharge machining of Al2O3p/6061Al composites. International Journal of Machine Tools & Manufacture 45:251–259. https://doi.org/10.1016/j.ijmachtools.2004.08.015

    Article  Google Scholar 

  16. Yan MT, Lai YP (2007) Surface quality improvement of wire-EDM using a fine-finish power supply. International Journal of Machine Tools & Manufacture 47(11):1686–1694. https://doi.org/10.1016/j.ijmachtools.2007.01.006

    Article  Google Scholar 

  17. Sanchez JA, de Lacalle LNL, Lamikiz A (2004) A computer-aided system for the optimization of the accuracy of the wire electro-discharge machining process. Int J Comp Integ Manuf 17(5):1413–1420. https://doi.org/10.1080/09511920310001626590

    Article  Google Scholar 

  18. Sarkar S, Sekh M, Mitra S, Bhattacharyya B (2011) A novel method of determination of wire lag for enhanced profile accuracy in WEDM. Precision Engineering 35(2):339–347. https://doi.org/10.1016/j.precisioneng.2011.01.001

    Article  Google Scholar 

  19. Werner A (2016) Method for enhanced accuracy in machining curvilinear profiles on wire-cut electrical discharge machines. Precision Engineering 44:75–80. https://doi.org/10.1016/j.precisioneng.2015.10.004

    Article  Google Scholar 

  20. Conde A, Arriandiaga A, Sanchez JA, Portillo E, Plaza S, Cabanes I (2018) High-accuracy wire electrical discharge machining using artificial neural networks and optimization techniques. Robotics and computer-integrated manufacturing 49:24–38. https://doi.org/10.1016/j.rcim.2017.05.010

    Article  Google Scholar 

  21. Abyar H, Abdullah A, Akbarzadeh (2018) Analyzing wire deflection errors of WEDM process on small arced corners. J Manuf Processes 36:216–223. https://doi.org/10.1016/j.jmapro.2018.10.002

    Article  Google Scholar 

  22. Kibria G, Bhattacharyya B (2020) Accuracy enhancement technologies for micromachining processes. Lecture notes in mechanical engineering, Improvement of profile accuracy in WEDM, Springer Singapore. https://doi.org/10.1007/978-981-15-2117-1_4

  23. Selvakumar G, Jiju KB, Sarkar S, Mitra S (2016) Enhancing die corner accuracy through trim cut in WEDM. Int J Adv Manuf Technol 83:791–803. https://doi.org/10.1007/s00170-015-7606-0

    Article  Google Scholar 

  24. Salcedo AT, Arbizu PI, Perez CJL (2017) Analytical modelling of energy density and optimization of the EDM machining parameters of Inconel 600. Metals 7(5):166. https://doi.org/10.3390/met7050166

    Article  Google Scholar 

  25. Naveed R, Mufti NA, Ishfaq K et al (2019) Complex taper profile machining of WC-Co composite using wire electric discharge process: analysis of geometrical accuracy, cutting rate, and surface quality. Int J Adv Manuf Technol 105:411–423. https://doi.org/10.1007/s00170-019-04150-x

    Article  Google Scholar 

  26. Chakraborty S, Mitra S, Bose D (2021) Experimental investigation on enhancing die corner accuracy during powder mixed wire EDM of Ti6Al4V. Materials Today, Proceedings 38(5):3097–3102. https://doi.org/10.1016/j.matpr.2020.09.491

    Article  Google Scholar 

  27. Chen Z, Zhang G (2018) Study on magnetic field distribution and electro-magnetic deformation in wire electrical discharge machining sharp corner workpiece. Int J Adv Manuf Technol 98:1913–1923. https://doi.org/10.1007/s00170-018-2260-y

    Article  Google Scholar 

  28. Yan H, Bakadiasa KD, Chen Z, Yan Z, Zhou H, Han F (2020) Attainment of high corner accuracy for thin-walled sharp-corner part by WEDM based on magnetic field-assisted method and parameter optimization. Int J Adv Manuf Technol 106:4845–4857. https://doi.org/10.1007/s00170-020-04966-y

    Article  Google Scholar 

  29. Simkulet V, Mitaľová Z, Lehocká D, Kočiško M, Manduľák D (2017) Evaluation of fracture surface samples by impact energy test prepared after DMLS additive manufacturing technology. In: DF PM 2017. Košice, SAS, pp 82–83

    Google Scholar 

  30. Van DN, Van BP, Huu PN (2020) Application of Deng’s similarity-based analytic hierarchy process approach in parametric optimization of the electrical discharge machining process of SDK11 die steel. T Can Soc Mech Eng 44(2):294–310. https://doi.org/10.1139/tcsme-2019-0132

    Article  Google Scholar 

  31. Zhu S, Chen W., Zhan X., Ding L., Zhou J. (2019) Parameter optimisation of laser cladding repair for an Invar alloy mould. In: Proceedings of the Institution of Mechanical Engineers, P I Mech Eng B-J Eng 233(8): 1859-1871. https://doi.org/10.1177/0954405418805653

  32. Yaman S, Cakir O (2020) Investigation of the effects of EDM parameters on surface roughness. Journal of advances in manufacturing engineering 1(2):46–55

    Google Scholar 

  33. Grigoriev SN, Kozochkin MP, Porvatov AN, Volosova MA, Okunkova AA (2019) Electrical discharge machining of ceramic nanocomposites: sublimation phenomena and adaptive control. Heliyon 5(10):1–19. https://doi.org/10.1016/j.heliyon.2019.e02629

    Article  Google Scholar 

  34. Mouralova K, Zahradnicek R, Houska P (2016, 2016) Evaluation of surface quality of X210Cr12 steel for forming tools machined by WEDM. MM Science Journa (5):1366–1369. https://doi.org/10.17973/MMSJ.2016_11_2016123

  35. Rouniyar AK, Shandilya P (2019) Fabrication and experimental investigation of magnetic field assisted powder mixed electrical discharge machining on machining of aluminum 6061 alloy. P I Mech Eng B-J Eng 233(12):2283–2291. https://doi.org/10.1177/0954405419838954

    Article  Google Scholar 

  36. Yan S, Yao J, Li J, Zhu X, Wang C, He W, Ma S (2018) Study on point bar residual oil distribution based on dense well pattern in Sazhong area. Journal of Mines, Metals and Fuels: Books and Journals Private Ltd. 65(12):743–748

    Google Scholar 

  37. Straka Ľ (2014) Analysis of wire-cut electrical discharge machined surface; Publisher: LAP Lambert Academic Publishing, Germany

  38. Wang J, Sánchez J.A., Izquierdo B., Ayesta I. (2020) Experimental and numerical study of crater volume in wire electrical discharge machining. Materials 13(3): art. no. 577. https://doi.org/10.3390/ma13030577

  39. Najm VN (2018) Experimental investigation of wire EDM process parameters on heat affected zone. Engineering and Technology Journal 36 part A(1):64–65

    Google Scholar 

  40. Straka L’, Hašová S (2016) Prediction of the heat-affected zone of tool steel EN X37CrMoV5–1 after die-sinking electrical discharge machining. P I Mech Eng B-J Eng 9:1–12. https://doi.org/10.1177/0954405416667405

    Article  Google Scholar 

  41. Świercz R, Oniszczuk-Świercz D (2017) Experimental investigation of surface layer properties of high thermal conductivity tool steel after electrical discharge machining. Metals 7(12):550. https://doi.org/10.3390/met7120550

    Article  Google Scholar 

  42. Ngocpi V et al (2020) Multi-objective optimization of PMEDM process parameters for processing cylindrical shaped parts using Taguchi method and grey relational analysis. International Journal of Mechanical and Production Engineering Research and Developmen 10(2):669–678

    Google Scholar 

  43. Evin E, Tomáš M, Kmec J (2020) Optimization of electro-discharge texturing parameters for steel sheets' finishing rollers. Materials 13(5): art. no. 1223. https://doi.org/10.3390/ma13051223

  44. Meshram DB, Puri YM (2020) Optimized curved electrical discharge machining-based curvature channel. J Brazil Soc Mech Sci 42(2) art. no.:82. https://doi.org/10.1007/s40430-019-2162-4

    Article  Google Scholar 

  45. Equbal A, Equbal MI, Sood AK (2019) An investigation on the feasibility of fused deposition modelling process in EDM electrode manufacturing. CIRP Journal of Manufacturing Science and Technology 26:10–25. https://doi.org/10.1016/j.cirpj.2019.07.001

    Article  Google Scholar 

  46. Swiercz R, Holubek R (2020) Experimental investigation of influence electrical discharge energy on the surface layer properties after EDM. Welding Technology Review 92(5):7–13. https://doi.org/10.26628/wtr.v92i5.1115

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the grant agency for supporting research work by the project VEGA 1/0205/19 and also by the Project of the Structural Funds of the EU, ITMS code 26220220103.

Code availability

Not applicable.

Funding

This research was funded by Scientific Grant Agency of the Ministry of Education, Science, Research and Sport of the Slovak Republic, grant number VEGA 1/0205/19, and also by the Project of the Structural Funds of the EU, ITMS code 26220220103.

Author information

Authors and Affiliations

Authors

Contributions

Methodology and data curation, ĽS; formal analysis, JP; design and performance of the experiments, ĽS and IČ; writing—original draft preparation, ĽS; project administration, ĽS and JP; funding acquisition and resources, ĽS. All the authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Ľuboslav Straka.

Ethics declarations

Ethics approval

This work does not contain any ethical issues or personal information.

Consent to participate

No human or animal was involved in this work; thus, no consent was required.

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

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Straka, Ľ., Piteľ, J. & Čorný, I. Influence of the main technological parameters and material properties of the workpiece on the geometrical accuracy of the machined surface at wedm. Int J Adv Manuf Technol 115, 3065–3087 (2021). https://doi.org/10.1007/s00170-021-07313-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-021-07313-x

Keywords

Navigation