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Experimental Investigations and Selection of Solid Lubricant Assisted Lubrication Strategy in Machining with the Use of PROMETHEE

  • M. A. MakhesanaEmail author
  • K. M. Patel
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 949)

Abstract

Manufacturing sector is always looking to find out an alternative in order to develop sustainable process. Machining plays a very important role in today’s manufacturing sector. In order to avoid the problems caused by heat generated in machining, conventional coolant has been applied. The large quantity of these fluids causes environmental damage and also adding total production cost. In this context, the present work focuses on application of minimum quantity lubrication combined with the solid lubricants. Performance of calcium fluoride and molybdenum disulphide as solid lubricant is assessed with different concentration and particle size mixed with SAE 40 oil on response parameters like surface roughness, power consumption, chip-tool interface temperature and flank wear. In order to select best suitable lubricating combination, PROMETHEE a multiple attribute decision-making method is applied. Comparison of results revealed the effectiveness of calcium fluoride as solid lubricant over other machining conditions and minimum quantity lubrication (MQL). Ranking available from the PROMETHEE can be considered as feasible lubrication alternative in machining as compared to conventional fluid cooling. The results of the work will be useful to explore the possibility to consider the solid lubricants as an efficient alternative to cutting fluids.

Keywords

Multiple attribute decision making PROMETHEE MQL Solid lubricants 

References

  1. 1.
    Pusavec, F., Krajnik, P., Kopac, J.: Transitioning to sustainable production- Part I: application on machining technologies. J. Clean. Prod. 18, 174–184 (2010)CrossRefGoogle Scholar
  2. 2.
    Klocke, F., Beck, T., Eisenblätter, G., Fritsch, R., Lung D. and Pöhls, M.: Applications of minimal quantity lubrication (MQL) in cutting and grinding. In: Proceedings of the 12th International Colloquium Industrial and Automotive Lubrification. Technische Akademie, Esslingen (2000)Google Scholar
  3. 3.
    Hafenbraedl, D., Malkin S.: Technology environmentally correct for intern cylindrical grinding. Mach. Metals Mag., 40–55 (2001)Google Scholar
  4. 4.
    da Silva, L.R., Bianchi, E.C., Catai, R.E., Fusse, R.Y., França, T.V., Aguiar, P.R.: Analysis of surface integrity for minimum quantity lubricant-MQL in grinding. Int. J. Mach. Tools Manuf. 47, 412–418 (2007)CrossRefGoogle Scholar
  5. 5.
    Reddy, N.S.K., Rao, P.V.: Experimental investigation to study the effect of solid lubricants on cutting forces and surface quality in end milling. Int. J. Mach. Tools Manuf. 46, 189–198 (2006)CrossRefGoogle Scholar
  6. 6.
    Vamsi Krishna, P., Srikant, R.R., Rao, D.N.: Experimental investigation to study the performance of solid lubricants in turning of AISI1040 steel. IMechE Part J: J. Eng. Tribol. 224, 1273–1281 (2010)CrossRefGoogle Scholar
  7. 7.
    Varadarajan, M.A.S., Philip, P.K., Ramamoorthy, B.: Investigations on hard turning with minimal cutting fluid application (HTMF) and its comparison with dry and wet turning. Int. J. Mach. Tools Manuf. 42, 193–200 (2002)CrossRefGoogle Scholar
  8. 8.
    Rahman, M.M., Senthil Kumar, A., Salam, M.U.: Experimental evaluation on the effect of minimal quantities of lubricant in milling. Int. J. Mach. Tools Manuf. 42, 539–547 (2002)CrossRefGoogle Scholar
  9. 9.
    Dilbagh Singh, M., Rao, P.V.: Performance improvement of hard turning with solid lubricants. Int. J. Adv. Manuf. Technol. 38, 529–535 (2008)CrossRefGoogle Scholar
  10. 10.
    Reddy, N.S.K., Rao, P.V.: Performance improvement of end milling using graphite as a solid lubricant. Mater. Manuf. Processes 20, 673–686 (2005)CrossRefGoogle Scholar
  11. 11.
    Rao, R.V.: Decision making in the manufacturing environment using graph theory and fuzzy multiple attribute decision making methods. Springer-Verlag, London (2007)zbMATHGoogle Scholar
  12. 12.
    Rao, R.V., Patel, B.K.: Decision making in the manufacturing environment using an improved PROMETHEE method. Int. J. Prod. Res., 1–18 (2009).  https://doi.org/10.1080/00207540903049415CrossRefGoogle Scholar
  13. 13.
    Cavalcante C.A.V., De Almeida, A.T.: A multi-criteria decision-aiding model using PROMETHEE III for preventive maintenance planning under uncertain conditions. J. Qual. Maintenance Eng. 13(4), 385–397 (2007)CrossRefGoogle Scholar
  14. 14.
    Anand, G., Kodali, R.: Selection of lean manufacturing systems using the PROMETHEE. J. Model. Manag. 3(1), 40–70 (2008)CrossRefGoogle Scholar
  15. 15.
    Brans, J.P., Mareschal, B., Vincke, P.: PROMETHEE: a new family of outranking methods in multicriteria analysis. Proc. Oper. Res. 84, 477–490 (1984)Google Scholar
  16. 16.
    Behzadian, M., Kazemzadeh, R.B., Albadvi, A., Aghdasi, M.: PROMETHEE: a comprehensive literature review on methodologies and applications. Eur. J. Oper. Res. 200(1), 198–215 (2009)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Mechanical Engineering Department, Institute of TechnologyNirma UniversityAhmedabadIndia

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