Minimum quantity blended bio-lubricants for sustainable machining of superalloy: An MCDM model-based study

Author:

Sen Binayak12ORCID,Kothapalli Sunil Kumar3ORCID,Kumar Raman45ORCID,C Manjunath6ORCID,Abdullah Irsyad7,Singh Gurpartap8ORCID,Santhosh A. Johnson9ORCID

Affiliation:

1. Centre for Computational Modeling, Chennai Institute of Technology 1 , Chennai 600069 Tamil Nadu, India

2. Department of Mechanical Engineering, Chennai Institute of Technology 2 , Chennai 600069 Tamil Nadu, India

3. Department of Mechanical Engineering, SRKR Engineering College 3 , Bhimavaram, Andhra Pradesh 534204, India

4. School of Mechanical Engineering, Rayat Bahra University 4 , Kharar, Punjab 140103, India

5. Faculty of Engineering, Sohar University 5 , P.O. Box 44, Sohar PCI 311, Oman

6. School of Engineering and Technology, JAIN (Deemed to be University) 6 , Bangalore, Karnataka, India

7. Management and Science University 7 , Shah Alam Selangor, Malaysia

8. Department of Mechanical Engineering, Chandigarh Engineering College, Chandigarh Group of Colleges 8 , Jhanjeri, Mohali, Punjab 140307, India

9. Faculty of Mechanical Engineering, Jimma Institute of Technology 9 , Jimma University, Jimma, Ethiopia

Abstract

The imperative shift toward sustainability has driven contemporary scholars to explore the lubricating and cooling properties of vegetable oils in traditional metal-cutting processes. Palm oil, as an environmentally conscious derivative, emerges as a preferable option for the base fluid in Minimum Quantity Lubrication (MQL). However, its high viscosity impedes fluidity, limiting industrial applicability. In contrast, sunflower oil offers superior lubricating qualities and flowability. Consequently, efforts have been directed toward enhancing the lubricating efficacy of palm oil. Six blends of palm and sunflower oils (ranging from 1:0.5 to 1:3) were utilized as MQL fluids, followed by evaluations of machining outcomes, including average surface roughness, specific cutting energy, and tool wear. In addition, an integrated Shannon’s Entropy-based Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) framework was employed to determine the optimal volume ratio of the palm–sunflower oil blend. The TOPSIS analysis confirmed that the 1:2 ratio yielded the most favorable outcomes. Subsequent comparative analysis demonstrated that this optimal blend resulted in reductions of 16.79% and 14.92% in surface roughness, 11.82% and 10.98% in specific cutting energy, and 10.19% and 8.45% in tool wear compared to pure palm and sunflower oil media, respectively. Finally, sustainability assessments of various cooling media revealed that a minimal quantity of the blended bio-lubricant-based medium outperforms both compressed air and flooded media.

Funder

Center for Nonlinear Systems, Chennai Institute of Technology

Publisher

AIP Publishing

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