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Potential use of transesterified vegetable oil blends as base stocks for metalworking fluids and cutting forces prediction using machine learning tool

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Abstract

The majority of lubricants used around the world are mineral oil-based, which causes environmental and health risks. The industry is under pressure to develop eco-friendly and biodegradable lubricants due to poor degradability and the depletion of mineral oil resources. Vegetable oils (VO) are being considered as an alternative source of lubricants due to their biodegradability, renewability, low toxicity, and good lubricating characteristics. The VO also suffers few drawbacks such as limited oxidation stability and poor low-temperature performance. Blending, chemical modification, and additives can improve the oil’s lubricating properties. The objective of the study is to formulate bio-lubricants from vegetable oils such as rice bran oil (RBO), jatropha oil (JO), and a blend of RBO and JO. Transesterification was performed on the vegetable oils, and all samples were assessed for tribological characteristics, oxidative stability, corrosion, and emulsion stability using ASTM and international standards. A lathe machine with a tool dynamometer was used to test the performance of the formulated cutting fluid. Cutting forces were assessed and compared to those of a commercial cutting fluid. Machine learning algorithms were also used to forecast cutting forces, which were then compared to experimental values. The 1:1 ratio of transesterified RBO and JO has shown a better coefficient of friction and superior oxidative stability. Also, the 40% emulsifier in the oil has shown good stability. The cutting forces were found to be lower for wet machining when compared with dry machining and vegetable oil-based cutting fluid has shown similar performance to that of commercial cutting fluid.

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References

  1. Çakīr O, Yardimeden A, Ozben T, Kilickap E (2007) Selection of cutting fluids in machining processes. J Achiev Mater Manuf Eng 25(2):99–102

    Google Scholar 

  2. Shaw C. Action of metal fluids at low speeds * Fluids have been used for over 50 years in connection with metal cutting opera- to achieve one or more of the following purposes. 2, 1958

  3. Pop L, Puşcaş C, Bandur G, Vlase G, Nuţiu R (2008) Basestock oils for lubricants from mixtures of corn oil and synthetic diesters. JAOCS J Am Oil Chem Soc 85(1):71–76. https://doi.org/10.1007/s11746-007-1156-z

    Article  Google Scholar 

  4. Zeman A, Sprengel A, Niedermeier D, Späth M (1995) Biodegradable lubricants—studies on thermo-oxidation of metal-working and hydraulic fluids by differential scanning calorimetry (DSC). Thermochim Acta 268:9–15

    Article  Google Scholar 

  5. Pettersson A (2007) High-performance base fluids for environmentally adapted lubricants. Tribol Int 40(4):638–645. https://doi.org/10.1016/j.triboint.2005.11.016

    Article  Google Scholar 

  6. Erhan SZ, Asadauskas S (2000) Lubricant basestocks from vegetable oils. Ind Crops Prod 11(2–3):277–282. https://doi.org/10.1016/S0926-6690(99)00061-8

    Article  Google Scholar 

  7. de Souza M. Chanes, de Souza Gonçalves J. Fracaro, P. Cézar Gonçalves, S. Yuji Sudo Lutif, and J. de Oliveira Gomes (2018) Use of Jatropha and Moringa oils for lubricants: Metalworking fluids more environmental-friendly. Ind Crops Prod 129, 594–603, 2019, https://doi.org/10.1016/j.indcrop.2018.12.033.

  8. Ojolo SJ, Amuda MOH, Ogunmola OY, Ononiwu CU (2008) Experimental determination of the effect of some straight biological oils on cutting force during cylindrical turning. Matéria (Rio Janeiro) 13(4):650–663. https://doi.org/10.1590/s1517-70762008000400011

    Article  Google Scholar 

  9. Xavior MA, Adithan M (2009) Determining the influence of cutting fluids on tool wear and surface roughness during turning of AISI 304 austenitic stainless steel. J Mater Process Technol 209(2):900–909. https://doi.org/10.1016/j.jmatprotec.2008.02.068

    Article  Google Scholar 

  10. Kuram E, Ozcelik B, Demirbas E, Şik E (2010) Effects of the cutting fluid types and cutting parameters on surface roughness and thrust force. WCE 2010 - World Congr Eng 2:1312–1315

    Google Scholar 

  11. Lawal SA, Choudhury IA, Nukman Y (2012) Application of vegetable oil-based metalworking fluids in machining ferrous metals - A review. Int J Mach Tools Manuf 52(1):1–12. https://doi.org/10.1016/j.ijmachtools.2011.09.003

    Article  Google Scholar 

  12. Owuna FJ (2020) Stability of vegetable based oils used in the formulation of ecofriendly lubricants–a review. Egypt J Pet

  13. Rani S, Joy ML, Nair KP (2015) Evaluation of physiochemical and tribological properties of rice bran oil - biodegradable and potential base stoke for industrial lubricants. Ind Crops Prod 65:328–333. https://doi.org/10.1016/j.indcrop.2014.12.020

    Article  Google Scholar 

  14. Ait Babahmad R et al (2018) Chemical composition of essential oil of Jatropha curcas L. leaves and its antioxidant and antimicrobial activities. Ind. Crops Prod. 121:405–410. https://doi.org/10.1016/j.indcrop.2018.05.030

    Article  Google Scholar 

  15. Hashempour-Baltork F, Torbati M, Azadmard-Damirchi S, Savage GP (2016) Vegetable oil blending: a review of physicochemical, nutritional and health effects. Trends Food Sci Technol 57:52–58. https://doi.org/10.1016/j.tifs.2016.09.007

    Article  Google Scholar 

  16. De Marco E, Savarese M, Parisini C, Battimo I, Falco S, Sacchi R (2007) Frying performance of a sunflower/palm oil blend in comparison with pure palm oil. Eur J Lipid Sci Technol 109(3):237–246. https://doi.org/10.1002/ejlt.200600192

    Article  Google Scholar 

  17. Farag HA, El-Maghraby A, Taha NA (2011) Optimization of factors affecting esterification of mixed oil with high percentage of free fatty acid. Fuel Process Technol 92(3):507–510. https://doi.org/10.1016/j.fuproc.2010.11.004

    Article  Google Scholar 

  18. Naghshineh M, Ariffin AA, Ghazali HM, Mohammad AS, Mirhosseini H (2010) Effect of saturated/unsaturated fatty acid ratio on physicochemical properties of palm olein-olive oil blend. JAOCS J Am Oil Chem Soc 87(3):255–262. https://doi.org/10.1007/s11746-009-1495-z

    Article  Google Scholar 

  19. Choudhary M, Grover K, Kaur G (2015) Development of rice bran oil blends for quality improvement. Food Chem 173:770–777. https://doi.org/10.1016/j.foodchem.2014.10.051

    Article  Google Scholar 

  20. Sinha S, Agarwal AK (2009) Rice bran oil methyl ester fuelled medium-duty transportation engine: long-term durability and combustion investigations. Int J Veh Des 50(1–4):248–270

    Article  Google Scholar 

  21. Meher LC, Sagar DV, Naik SN (2006) Technical aspects of biodiesel production by transesterification—a review. Renew Sustain energy Rev 10(3):248–268

    Article  Google Scholar 

  22. Sinha S, Agarwal AK, Garg S (2008) Biodiesel development from rice bran oil: transesterification process optimization and fuel characterization. Energy Convers Manag 49(5):1248–1257

    Article  Google Scholar 

  23. Joshi G, Lamba BY, Rawat DS, Mallick S, Murthy KSR (2013) Evaluation of additive effects on oxidation stability of Jatropha curcas biodiesel blends with conventional diesel sold at retail outlets. Ind Eng Chem Res 52(22):7586–7592

    Article  Google Scholar 

  24. Abdullahi UU, Bashi SM, Yunus R, Nurdin A (2004) The potentials of palm oil as a dielectric fluid in PECon 2004. Proceedings. National Power and Energy Conference, 2004, 224–228.

  25. Owuna FJ et al (2020) Chemical modification of vegetable oils for the production of biolubricants using trimethylolpropane: a review. Egypt J Pet 29(1):75–82

    Article  Google Scholar 

  26. Elmelawy MS, El-Meligy A, Mawgoud HA, Morshedy AS, Hanafy SA, El-sayed IE (2021) Synthesis and kinetics study of trimethylolpropane fatty acid triester from oleic acid methyl ester as potential biolubricant. Biomass Convers Biorefinery, https://doi.org/10.1007/s13399-020-01220-z.

  27. Zulkifli NWM, Kalam MA, Masjuki HH, Shahabuddin M, Yunus R (2013) Wear prevention characteristics of a palm oil-based TMP (trimethylolpropane) ester as an engine lubricant. Energy 54:167–173

    Article  Google Scholar 

  28. Jurkovic Z, Cukor G, Brezocnik M, Brajkovic T (2018) A comparison of machine learning methods for cutting parameters prediction in high speed turning process. J Intell Manuf 29(8):1683–1693

    Article  Google Scholar 

  29. D. Cica, B. Sredanovic, S. Tesic, and D. Kramar (2020) Predictive modeling of turning operations under different cooling/lubricating conditions for sustainable manufacturing with machine learning techniques. Appl Comput. Informatics

  30. Hashemitaheri M, Mekarthy SMR, Cherukuri H (2020) Prediction of specific cutting forces and maximum tool temperatures in orthogonal machining by support vector and Gaussian process regression methods. Procedia Manuf 48:1000–1008

    Article  Google Scholar 

  31. Leung DYC, Wu X, Leung MKH (2010) A review on biodiesel production using catalyzed transesterification. Appl Energy 87(4):1083–1095

    Article  Google Scholar 

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Acknowledgements

The first author “E. Sneha” would also like to acknowledge AICTE-NDF for providing a Ph.D. fellowship. The authors would also like to acknowledge YK Laboratories, Hyderabad, for providing organic emulsifier (under patent) and Care Keralam, Thrissur, for the evaluation of the fatty acid composition.

Funding

The corresponding author received financial support from Kerala State Council for Science, Technology, and Environment [KSCSTE], Kerala, India.

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Authors and Affiliations

  1. Advanced Tribology Research Centre, Department of Mechanical Engineering, College of Engineering Trivandrum, Thiruvananthapuram, Kerala, India

    Sneha Edla, Abhijith Krishna, G. V. S. Karthik, M. Muhammed Arif & S. Rani

  2. APJ Abdul Kalam Technological University, Thiruvananthapuram, Kerala, India

    Sneha Edla, Abhijith Krishna, G. V. S. Karthik & S. Rani

  3. Department of Chemistry, College of Engineering Trivandrum, Thiruvananthapuram, Kerala, India

    M. Muhammed Arif

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  1. Sneha Edla
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  2. Abhijith Krishna
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  3. G. V. S. Karthik
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  4. M. Muhammed Arif
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  5. S. Rani
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Contributions

Conceptualization: Sneha Edla.

Methodology: Sneha Edla and G V S Karthik.

Investigation: Sneha Edla, G V S Karthik, and Abhijith Krishna.

Writing—original draft preparation: Sneha Edla.

Writing—review and editing: Abhijith Krishna and Rani S.

Supervision: M Muhammed Arif and Rani S.

Corresponding author

Correspondence to S. Rani.

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Edla, S., Krishna, A., Karthik, G.V.S. et al. Potential use of transesterified vegetable oil blends as base stocks for metalworking fluids and cutting forces prediction using machine learning tool. Biomass Conv. Bioref. 13, 10665–10676 (2023). https://doi.org/10.1007/s13399-021-01952-6

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  • DOI: https://doi.org/10.1007/s13399-021-01952-6

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