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Effective machining parameter selection through fuzzy AHP-TOPSIS for 3D finish milling of Ti6Al4V

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Abstract

Ti6Al4V is a Hard-to-Shear material in the Automobile, Aerospace, Marine, and Biomedical implant industries. The difficulties in the shearing arise from metallurgical phase alterations under insufficient lubrication and cooling during Ti6Al4V machining. This article wisely investigated 3D finish milling using different Computer-Aided Machining (CAM) strategies with cooling approaches followed by Taguchi Design of Experiments. The performance was evaluated in terms of Surface integrity, Flank, and Crater wear. The Fuzzy Analytic Hierarchy Process establishes the weights by extent analysis, and furthermore, Technique for Order of Preference by Similarity to Ideal Solution decides the optimum levels of process parameters. The optimized process parameters like Cutting speed (40 m/min), Axial Depth of Cut (0.3 mm), and Feed rate (101.92 mm/min) with Graphene Oxide Nanoparticles + 15% concentrated wet lubrication (Hybrid Flood Coolant) are applied through the Streamline CAM strategy with PVD-TiAlN coated cutting tool. These yielded process parameters exhibit excellent performance in finish milling than the other combinations of parameters. Analysis of Variance evaluates the influences of process parameters on experimental performances. Finally, optimized process parameters were applied to 3D milling of Ti6Al4V bracket through Streamline CAM strategy, which sequels the lower Crater and Flank wear with 0.132 microns surface integrity.

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Abbreviations

Ti6Al4V:

Titanium alloy grade 5

W′:

Unnormalized weight vector

GON:

Graphene oxide nanoparticles

dˊA i :

Degree of possibility

BCC:

Body-centered cubic

MQL:

Minimum quantity lubrication

3D:

Three dimensional

DOC:

Depth of cut

CAM:

Computer-aided machining

DOE:

Design of experiment

AHP:

Analytic hierarchy process

HCP:

Hexagonal closed packed

HCPPVD:

Physical vapor deposition

LCO2/LCO2 :

Liquid carbon dioxide

CVD:

Chemical vapor deposition

LN2:

Liquid nitrogen

TOPSIS:

Technique for order performance by similarity to ideal solution

Si :

Synthetic extent

CNC:

Computerized numerical control

MRR:

Material removal rate

K:

Convex fuzzy number

W:

Normalized weight vector

VB :

Flank wear width

KB :

Crater wear width

Expon.:

Exponential trend line

Ra:

Average surface roughness value

Avg.:

Average

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Acknowledgements

Authors would acknowledge the kind support of Supra Techno Services, Authorized Distributors for Seco Tools India Ltd. Pune and also thanks to the Department of Mechanical Engineering, Institute of Engineering, Bhujbal Knowledge City, Adgaon, Nashik, to carry out this article.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Sardar Patel College of Engineering, Andheri, Mumbai, 400058, India

    Amit S. Patil & Kiran S. Bhole

  2. Department of Mechanical Engineering, Lokmanya Tilak College of Engineering, Kopar Khairane, Navi Mumbai, 400709, India

    V. K. Sunnapwar

  3. Department of Computer Sciences and Engineering, Institute of Advanced Research, The University for Innovation, Gandhinagar, Gujarat, 382426, India

    Ankit D. Oza

  4. Department of Mechanical Engineering, Datta Meghe College of Engineering, Navi Mumbai, 400708, India

    S. M. Shinde

  5. Department of Mechanical Engineering, Sree Vidyanikethan Engineering College (Autonomous), Tirupathi, Andhra Pradesh, 517102, India

    R. Ramesh

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Patil, A.S., Sunnapwar, V.K., Bhole, K.S. et al. Effective machining parameter selection through fuzzy AHP-TOPSIS for 3D finish milling of Ti6Al4V. Int J Interact Des Manuf (2022). https://doi.org/10.1007/s12008-022-00993-z

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