Skip to main content
SpringerLink
Log in

The effects of minimum quantity lubrication parameters on the lubrication efficiency in the turning of plastic mold steel

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

Abstract

This study aims to investigate the impact of parameters associated with minimum quantity lubrication (MQL) in CNC turning of DIN 1.2738 plastic mold steel. The independent parameters considered include flow rate (\({F}_{r}\)), nozzle distance (\({N}_{d}\)), and nozzle angle (\({N}_{a}\)), with the objective of ensuring effective lubrication. The study focuses on evaluating surface roughness, cutting temperature, and specific cutting energy (SCE) to assess machinability. Experiments were conducted using coated carbide inserts SNMG 120,412-km and a commercially available vegetable oil-based cutting fluid, Eraoil KT/2000. Constant cutting parameters, such as cutting speed (220 m/min), feed rate (0.05 mm/rev), depth of cut (0.5 mm), nose radius (1.2 mm), working pressure (0.5 MPa), and nozzle radius (1 mm), were maintained. The methodology employed various analytical approaches, including analysis of variance (ANOVA), response surface methodology (RSM), gray relational analysis (GRA), and desirability function (DF). The results indicate that the MQL system effectively provided lubrication over a short nozzle distance of 10 mm by employing a high flow rate of 51 ml/h and a significant nozzle angle of 60°. These conditions resulted in satisfactory performance for machinability-related parameters. Consequently, surface roughness (\({R}_{a}\)) remained between 0.15 and 0.18 μm, cutting temperature (\({T}_{c}\)) ranged from 130 to 135 °C, and SCE consumption (\({E}_{cs}\)) was reduced to 3.37 J/mm3.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Data availability

Not applicable.

Code availability

Not applicable.

References

  1. Zhang X, Lu Z, Peng Z et al (2018) Development of a tool-workpiece thermocouple system for comparative study of the cutting temperature when high-speed ultrasonic vibration cutting Ti-6Al-4V alloys with and without cutting fluids. Int J Adv Manuf Technol 96:237–246. https://doi.org/10.1007/s00170-018-1600-2

    Article  Google Scholar 

  2. Revuru RS, Posinasetti NR, VSN V et al (2017) Application of cutting fluids in machining of titanium alloys—a review. Int J Adv Manuf Technol 91:2477–2498. https://doi.org/10.1007/s00170-016-9883-7

    Article  Google Scholar 

  3. Talon AG, Lopes JC, Sato BK et al (2020) Grinding performance of hardened steel: a study about the application of different cutting fluids with corrosion inhibitor. Int J Adv Manuf Technol 108:2741–2754. https://doi.org/10.1007/s00170-020-05598-y

    Article  Google Scholar 

  4. Adil A, Baig T, Jamil F et al (2023) Nanoparticle-based cutting fluids in drilling: a recent review. Int J Adv Manuf Technol. https://doi.org/10.1007/s00170-023-11048-2

    Article  Google Scholar 

  5. Jia DZ, Zhang YB, Li CH et al (2022) Lubrication-enhanced mechanisms of titanium alloy grinding using lecithin biolubricant. Tribol Int 169:107461. https://doi.org/10.1016/j.triboint.2022.107461

    Article  Google Scholar 

  6. Shokrani A, Dhokia V, Newman ST (2012) Environmentally conscious machining of difficult-to-machine materials with regard to cutting fluids. Int J Mach Tool Manuf 57:83–101. https://doi.org/10.1016/j.ijmachtools.2012.02.002

    Article  Google Scholar 

  7. Xu WH, Li CH, Zhang YB et al (2022) Electrostatic atomization minimum quantity lubrication machining: from mechanism to application. Int J Extrem Manuf 4:042003. https://doi.org/10.1088/2631-7990/ac9652

    Article  Google Scholar 

  8. Zhang X, Li C, Zhou Z et al (2023) Vegetable Oil-based nanolubricants in Machining: from Physicochemical properties to Application. Chin J Mech Eng 36:76. https://doi.org/10.1186/s10033-023-00895-5

    Article  Google Scholar 

  9. Javaroni RL, Lopes JC, Sato BK et al (2019) Minimum quantity of lubrication (MQL) as an eco-friendly alternative to the cutting fluids in advanced ceramics grinding. Int J Adv Manuf Technol 103:2809–2819. https://doi.org/10.1007/s00170-019-03697-z

    Article  Google Scholar 

  10. Hamran NN, Ghani JA, Ramli R, Haron CC (2020) A review on the recent development of minimum quantity lubrication for sustainable machining. J Clean Prod 268:1–18. https://doi.org/10.1016/j.jclepro.2020.122165

    Article  Google Scholar 

  11. Amiril SAS, Rahim EA, Syahrullail S (2017) A review on ionic liquids as sustainable lubricants in manufacturing and engineering: recent research, performance, and applications. J Clean Prod 168:1571–1589. https://doi.org/10.1016/j.jclepro.2017.03.197

    Article  Google Scholar 

  12. Wang X, Li C, Zhang Y et al (2020) Vegetable oil-based nanofluid minimum quantity lubrication turning: academic review and perspectives. J Manuf Process 59:76–97. https://doi.org/10.1016/J.JMAPRO.2020.09.044

    Article  Google Scholar 

  13. Costello S, Friesen MC, Christiani DC, Eisena EA (2011) Metalworking fluids and malignant melanoma in autoworkers. Epidemiology 22(1):90–97. https://doi.org/10.1097/EDE.0b013e3181fce4b8

    Article  Google Scholar 

  14. Chinchanikar S, Kore SS, Hujare P (2021) A review on nanofluids in minimum quantity lubrication machining. J Manuf Process 68:56–70. https://doi.org/10.1016/j.jmapro.2021.05.028

    Article  Google Scholar 

  15. Sharma AK, Tiwari AK, Dixit AR (2016) Effects of minimum quantity lubrication (MQL) in machining processes using conventional and nanofluid-based cutting fluids: a comprehensive review. J Clean Prod 127:1–18. https://doi.org/10.1016/j.jclepro.2016.03.146

    Article  Google Scholar 

  16. Virdi RL, Pal A, Chatha SS et al (2023) A review on minimum quantity lubrication technique application and challenges in grinding process using environment-friendly nanofluids. J Braz Soc Mech Sci Eng 45:238. https://doi.org/10.1007/s40430-023-04159-0

    Article  Google Scholar 

  17. Benedicto E, Rubio EM, Aubouy L et al (2021) Formulation of sustainable water-based cutting fuids with polyol esters for machining titanium alloys. Metals 11(5). https://doi.org/10.3390/met11050773

  18. Özakin B (2023) A comparative study of the selection of cutting fluids used in machining processes by multi criteria decision making (MCDM) methods. Sādhanā 48, 204. https://doi.org/10.1007/s12046-023-02265-2

  19. Wang X, Song Y, Li C et al (2023) Nanofluids application in machining: a comprehensive review. Int J Adv Manuf Technol. https://doi.org/10.1007/s00170-022-10767-2

    Article  Google Scholar 

  20. Rao RV, Gandhi OP (2022) Digraph and matrix method for the selection, identification and comparison of metal-cutting fluids. Proc Inst Mech Eng J Eng Tribol 51:8947–8959. https://doi.org/10.1243/1350650011541710

    Article  Google Scholar 

  21. Wu X, Li C, Zhou Z et al (2021) Circulating purification of cutting fluid: an overview. Int J Adv Manuf Technol 117:2565–2600. https://doi.org/10.1007/s00170-021-07854-1

    Article  Google Scholar 

  22. Fayiga AO, Ipinmoroti MO, Chirenje T (2018) Environmental pollution in Africa. Environ Dev Sustain 20:41–73. https://doi.org/10.1007/s10668-016-9894-4

    Article  Google Scholar 

  23. Yildirim CV, Sarikaya M, Kivak T, Sirin S (2019) The effect of addition of hBN nanoparticles to nanofluid-MQL on tool wear patterns, tool life, roughness and temperature in turning of Ni-based Inconel 625. Tribol Int 134:443–456. https://doi.org/10.1016/j.triboint.2019.02.027

    Article  Google Scholar 

  24. Derani MN, Ratnam MM (2021) The use of tool flank wear and average roughness in assessing effectiveness of vegetable oils as cutting fluids during turning—a critical review. Int J Adv Manuf Technol 112:1841–1871. https://doi.org/10.1007/s00170-020-06490-5

    Article  Google Scholar 

  25. Kuram E, Ozcelik B, Demirbas E (2013) Environmentally friendly machining: Vegetable Based cutting fluids. In: Davim J (ed) Green Manufacturing Processes and Systems. Materials forming, Machining and Tribology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33792-5_2

    Chapter  Google Scholar 

  26. Sarikaya M, Gullu A (2014) Taguchi design and response surface methodology based analysis of machining parameters in CNC turning under MQL. J Clean Prod 65:604–616. https://doi.org/10.1016/j.jclepro.2013.08.040

    Article  Google Scholar 

  27. Hybska H, Mitterpach J, Samesova D et al (2018) Assessment of ecotoxicological properties of oils in water. Arch Environ Prot 44(4):31–37. https://doi.org/10.24425/aep.2018.122300

    Article  Google Scholar 

  28. Cetin MH, Ozcelik B, Kuram E, Demirbas E (2011) Evaluation of vegetable based cutting fluids with extreme pressure and cutting parameters in turning of AISI 304L by Taguchi method. J Clean Prod 19(17–18):2049–2056. https://doi.org/10.1016/j.jclepro.2011.07.013

    Article  Google Scholar 

  29. Li M, Yu TB, Yang L et al (2019) Parameter optimization during minimum quantity lubrication milling of TC4 alloy with graphene-dispersed vegetable-oil-based cutting fluid. J Clean Prod 209:1508–1522. https://doi.org/10.1016/j.jclepro.2018.11.147

    Article  Google Scholar 

  30. Lawal SA, Choudhury IA, Nukman Y (2014) Evaluation of vegetable and mineral oil-in-water emulsion cutting fluids in turning AISI 4340 steel with coated carbide tools. J Clean Prod 66:610–618. https://doi.org/10.1016/j.jclepro.2013.11.066

    Article  Google Scholar 

  31. Dabi M, Saha UK (2019) Application potential of vegetable oils as alternative to diesel fuels in compression ignition engines: a review. J Energy Inst 92(6):1710–1726. https://doi.org/10.1016/j.joei.2019.01.003

    Article  Google Scholar 

  32. Murillo G, Sun J, Ali SS et al (2018) Evaluation of the kinematic viscosity in biodiesel production with waste vegetable oil, ultrasonic irradiation and enzymatic catalysis: a comparative study in two-reactors. Fuel 227:448–456. https://doi.org/10.1016/j.fuel.2018.04.119

    Article  Google Scholar 

  33. Kaur A, Singh B, Kaur A et al (2019) Chemical, thermal, rheological and FTIR studies of vegetable oils and their effect on eggless muffin characteristics. J Food Process Preserv 43(7):e13978. https://doi.org/10.1111/jfpp.13978

    Article  Google Scholar 

  34. Lv T, Huang S, Hu X et al (2018) Tribological and machining characteristics of a minimum quantity lubrication (MQL) technology using GO/SiO2 hybrid nanoparticle water-based lubricants as cutting fluids. Int J Adv Manuf Technol 96:2931–2942. https://doi.org/10.1007/s00170-018-1725-3

    Article  Google Scholar 

  35. Padhan S, Wagri NK, Dash L et al (2023) Investigation on Surface Integrity in Hard turning of AISI 4140 steel with SPPP-AlTiSiN coated Carbide Insert under Nano-MQL. Lubricants 11(2):49. https://doi.org/10.3390/lubricants11020049

    Article  Google Scholar 

  36. Ji X (2023) Minimum quantity lubrication machining: process analysis and analytical modeling. ISBN 978-981-19-7087-0 (eBook). https://doi.org/10.1007/978-981-19-7087-0

  37. Pervaiz S, Rashid A, Deiab I et al (2016) An experimental investigation on effect of minimum quantity cooling lubrication (MQCL) in machining titanium alloy (Ti6Al4V). Int J Adv Manuf Technol 87(5–8):1371–1386. https://doi.org/10.1007/s00170-016-8969-6

    Article  Google Scholar 

  38. Touggui Y, Uysal A, Emiroglu U et al (2021) Evaluation of MQL performances using various nanofluids in turning of AISI 304 stainless steel. Int J Adv Manuf Technol 115:3983–3997. https://doi.org/10.1007/s00170-021-07448-x

    Article  Google Scholar 

  39. Laouissi A, Nouioua M, Yallese MA et al (2021) Machinability study and ANN-MOALO-based multi-response optimization during eco-friendly machining of EN-GJL-250 cast iron. Int J Adv Manuf Technol 117:1179–1192. https://doi.org/10.1007/s00170-021-07759-z

    Article  Google Scholar 

  40. Tawakoli T, Hadad MJ, Sadeghi MH (2010) Influence of oil mist parameters on minimum quantity lubrication–MQL grinding process. Int J Mach Tool Manuf 50(6):521–531. https://doi.org/10.1016/j.ijmachtools.2010.03.005

    Article  Google Scholar 

  41. Mallick R, Khatai S, Kumar R et al (2023) Comparison of single nozzle and dual nozzle MQL performance in hardened steel turning: a case study. Materials Today: Proceedings. https://doi.org/10.1016/j.matpr.2023.10.022

  42. Jadhav PA, Deivanathan R (2021) Numerical analysis of the effect of air pressure and oil flow rate on droplet size and tool temperature in MQL machining. Materials Today: Proceedings 38:2499–2505. https://doi.org/10.1016/j.matpr.2020.07.518

  43. Standards committee tools and clamping devices (FWS) working committee (2011) DIN 69090-1 MQL Maching Technology-Part 1. Terms and Definitions (Article), DIN 69090-1:2011-12

  44. Walker T (2013) The MQL handbook–a guide to machining with minimum quantity lubrication. 1-616-949-0853, Unist, Inc. V1.0.3

  45. Hamdi A, Yapan YF, Uysal A, Merghache SM (2024) Investigation of MQL and CNC turning parameters on the machinability of unreinforced polypropylene: study of surface roughness, temperature, and specific cutting energy. Int J Adv Manuf Technol 130:717–730. https://doi.org/10.1007/s00170-023-12761-8

    Article  Google Scholar 

  46. Řehoř J, Fulemová J, Kutlwašer J et al (2023) ANOVA analysis for estimating the accuracy and surface roughness of precisely drilled holes of steel 42CrMo4 QT. Int J Adv Manuf Technol 126:675–695. https://doi.org/10.1007/s00170-023-11115-8

    Article  Google Scholar 

  47. Swain S, Panigrahi I, Sahoo AK et al (2020) Effect of Tool Vibration on Flank wear and surface roughness during high-speed machining of 1040 steel. J Fail Anal Preven 20:976–994. https://doi.org/10.1007/s11668-020-00905-x

    Article  Google Scholar 

  48. Ünüvar A, Koyunbakan M, Bagci M (2022) Optimization and effects of machining parameters on delamination in drilling of pure and Al2O3/SiO2-added GFRP composites. Int J Adv Manuf Technol 119:657–675. https://doi.org/10.1007/s00170-021-08258-x

    Article  Google Scholar 

  49. Nawaz Y, Maqsood S, Naeem K et al (2020) Parametric optimization of material removal rate, surface roughness, and kerf width in high-speed wire electric discharge machining (HS-WEDM) of DC53 die steel. Int J Adv Manuf Technol 107:3231–3245. https://doi.org/10.1007/s00170-020-05175-3

    Article  Google Scholar 

  50. Ahmed W, Hegab H, Mohany A et al (2021) On machining hardened steel AISI 4140 with self-propelled rotary tools: experimental investigation and analysis. Int J Adv Manuf Technol 113:3163–3176. https://doi.org/10.1007/s00170-021-06827-8

    Article  Google Scholar 

  51. Usluer E, Emiroğlu U, Yapan YF et al (2023) Investigation on the effect of hybrid nanofluid in MQL condition in orthogonal turning and a sustainability assessment. Sustainable Mater Technol 36:e00618. https://doi.org/10.1016/j.susmat.2023.e00618

    Article  Google Scholar 

  52. Zhang W, Liu D, Zhang Y et al (2023) Experimental study on the machining performance of nickel-based superalloy GH4169 milled by AWJ. Int J Adv Manuf Technol 129:1175–1188. https://doi.org/10.1007/s00170-023-12327-8

    Article  Google Scholar 

  53. Li CH, Li JY, Wang S, Zhang Q (2013) Modeling and numerical simulation of the grinding temperature feld with nanoparticle jet of MQL. Adv Mech Eng 5:986984. https://doi.org/10.1155/2013/986984

    Article  Google Scholar 

  54. Davim JP, Sreejith PS, Silva J (2007) Turning of brasses using minimum quantity of lubricant (MQL) and flooded lubricant conditions. Mater Manuf Process 22(1):45–50. https://doi.org/10.1080/10426910601015881

    Article  Google Scholar 

  55. Dada M, Popoola P, Mathe N et al (2020) Parametric optimization of laser deposited high entropy alloys using response surface methodology (RSM). Int J Adv Manuf Technol 109:2719–2732. https://doi.org/10.1007/s00170-020-05781-1

    Article  Google Scholar 

  56. Aklilu EG (2021) Modeling and optimization of pectin extraction from banana peel using artificial neural networks (ANNs) and response surface methodology (RSM). Food Measure 15:2759–2773. https://doi.org/10.1007/s11694-021-00852-7

    Article  Google Scholar 

  57. Trifunović M, Madić M, Janković P et al (2021) Investigation of cutting and specific cutting energy in turning of POM-C using a PCD tool: analysis and some optimization aspects. J Clean Prod 303:127043. https://doi.org/10.1016/j.jclepro.2021.127043

    Article  Google Scholar 

  58. Hamdi A, Yapan YF, Uysal A, Abderazek H (2023) Multi-objective analysis and optimization of energy aspects during dry and MQL turning of unreinforced polypropylene (PP): an approach based on ANOVA, ANN, MOWCA, and MOALO. Int J Adv Manuf Technol 128:4933–4950. https://doi.org/10.1007/s00170-023-12205-3

    Article  Google Scholar 

  59. Hamdi A, Merghache SM (2023) Application of artificial neural networks (ANN) and gray relational analysis (GRA) to modeling and optimization of the material ratio curve parameters when turning hard steel. Int J Adv Manuf Technol 124:3657–3670. https://doi.org/10.1007/s00170-023-10833-3

    Article  Google Scholar 

  60. Pandey PK, Singh M, Rathi R et al (2023) Analysis and optimization of welding techniques for austenitic stainless steel using grey relational analysis. Int J Interact Des Manuf. https://doi.org/10.1007/s12008-023-01445-y

    Article  Google Scholar 

  61. Abifarin JK (2021) Taguchi grey relational analysis on the mechanical properties of natural hydroxyapatite: effect of sintering parameters. Int J Adv Manuf Technol 117:49–57. https://doi.org/10.1007/s00170-021-07288-9

    Article  Google Scholar 

  62. Ali S, Pervaiz S (2023) Machinability analysis of AZ31 magnesium alloys using the Taguchi gray relational analysis. Int J Adv Manuf Technol 126:4171–4190. https://doi.org/10.1007/s00170-023-11354-9

    Article  Google Scholar 

  63. Chen T, Zhu Y, Xi X et al (2021) Process parameter optimization and surface integrity evolution in the high-speed grinding of TiAl intermetallics based on grey relational analysis method. Int J Adv Manuf Technol 117:2895–2908. https://doi.org/10.1007/s00170-021-07882-x

    Article  Google Scholar 

  64. Benkhelifa O, Cherfia A, Nouioua M (2022) Modeling and multi-response optimization of cutting parameters in turning of AISI 316L using RSM and desirability function approach. Int J Adv Manuf Technol 122:1987–2002. https://doi.org/10.1007/s00170-022-10044-2

    Article  Google Scholar 

  65. Kar SK, Mishra PK, Sahu AK et al (2023) Multi-objective optimization of wire-EDM of Inconel 625 by using desirability function approach. Int J Interact Des Manuf 17:931–938. https://doi.org/10.1007/s12008-022-01184-6

    Article  Google Scholar 

  66. Zhao D, Bezgans Y, Vdonin N et al (2021) The use of TOPSIS-based-desirability function approach to optimize the balances among mechanical performances, energy consumption, and production efficiency of the arc welding process. Int J Adv Manuf Technol 112:3545–3559. https://doi.org/10.1007/s00170-021-06601-w

    Article  Google Scholar 

  67. Uysal A (2016) Investigation of flank wear in MQL milling of ferritic stainless steel by using nano graphene reinforced vegetable cutting fluid. Indus Lub Tribology 68(4):446–451. https://doi.org/10.1108/ILT-10-2015-0141

    Article  MathSciNet  Google Scholar 

  68. Uysal A (2017) An experimental study on cutting temperature and burr in milling of ferritic stainless steel under MQL using nano graphene reinforced cutting fluid. Adv Mat Pro 2(9):560–563. https://doi.org/10.5185/amp.2017/038

    Article  Google Scholar 

Download references

Acknowledgements

This work was carried out in the LIMMaS laboratory (Tissemsilt University, Algeria) in collaboration with the YTU MASSUS Research Group (Yildiz Technical University, Istanbul, Türkiye).

Funding

The present research received funding from the General Directorate of Scientific Research and Technological Development (DGRSDT), Algerian Ministry of Higher education and Scientific Research (MESRS) under the PRFU research project A11N01UN380120220002.

Author information

Authors and Affiliations

  1. Laboratory of Mechanical Engineering, Materials and Structures, Tissemsilt University, Tissemsilt, 38000, Algeria

    Amine Hamdi & Sidi Mohammed Merghache

  2. Department of Mechanical Engineering, Yildiz Technical University, Beşiktaş, Istanbul, 34349, Turkey

    Yusuf Furkan Yapan & Alper Uysal

Authors
  1. Amine Hamdi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yusuf Furkan Yapan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Alper Uysal
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sidi Mohammed Merghache
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the study conception, material preparation, and data analysis. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Amine Hamdi.

Ethics declarations

Ethics approval

I certify that the paper follows the ethical rules of good scientific practice mentioned in the “Ethical Responsibilities of Authors” of the journal.

Consent to participate

Not applicable

Conflict of interest

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

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hamdi, A., Yapan, Y.F., Uysal, A. et al. The effects of minimum quantity lubrication parameters on the lubrication efficiency in the turning of plastic mold steel. Int J Adv Manuf Technol (2024). https://doi.org/10.1007/s00170-024-13706-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00170-024-13706-5

Keywords

Search

Navigation