Parameter Optimization and Machining Performance of Inconel 625 with Nanoparticles Dispersed in Biolubricant

Productivity and cost-effectiveness are essential components of any long-term manufacturing system. While quantity and quality are linked to productivity, the economy focuses on energy-efficient processes that produce a high output-to-input ratio. Hard-to-cut materials have always been difficult to...

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Main Authors: T. Mohanraj, N. Radhika, S. Aswin Nanda, V. Vignesh, B. Jayaraman, K. R. Ratana Selvan, Yesgat Admassu
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Advances in Materials Science and Engineering
Online Access:http://dx.doi.org/10.1155/2022/7210265
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author T. Mohanraj
N. Radhika
S. Aswin Nanda
V. Vignesh
B. Jayaraman
K. R. Ratana Selvan
Yesgat Admassu
author_facet T. Mohanraj
N. Radhika
S. Aswin Nanda
V. Vignesh
B. Jayaraman
K. R. Ratana Selvan
Yesgat Admassu
author_sort T. Mohanraj
collection DOAJ
description Productivity and cost-effectiveness are essential components of any long-term manufacturing system. While quantity and quality are linked to productivity, the economy focuses on energy-efficient processes that produce a high output-to-input ratio. Hard-to-cut materials have always been difficult to machine because of more significant tool wear and power losses. Inconel 625 is a hard material used in aerospace and underwater applications and is milled using biolubricants with nanoparticles. Palm oil is considered a biolubricant, and titanium dioxide (TiO2) and copper oxide (CuO) are selected as nanoparticles. When the combination of biolubricants and nanoparticles is added to the workpiece’s surface, it enhanced some properties while machining. Experiments involving four factors with four levels were carried out using the Taguchi design of experiments (DoE). The feed, depth of cut, speed, and coolant with nanoparticle additives were all factors. The responses were surface roughness, spindle vibration along X, Y, and Z axes, and material removal rate. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was used to alter the multiresponse optimization problem to a single-response optimization problem. The S/N of TOPSIS closeness coefficients was calculated, and the optimal machining conditions were determined. Surface roughness, material removal rate, and spindle vibration were reduced by 3.10%, 6.14%, 7.54% (Vx), and 6.78% (Vz), respectively, due to the TOPSIS optimization.
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spelling doaj-art-c4b43eb6e77f42809e5199f387094d7d2025-08-20T02:18:47ZengWileyAdvances in Materials Science and Engineering1687-84422022-01-01202210.1155/2022/7210265Parameter Optimization and Machining Performance of Inconel 625 with Nanoparticles Dispersed in BiolubricantT. Mohanraj0N. Radhika1S. Aswin Nanda2V. Vignesh3B. Jayaraman4K. R. Ratana Selvan5Yesgat Admassu6Department of Mechanical EngineeringDepartment of Mechanical EngineeringDepartment of Mechanical EngineeringDepartment of Mechanical EngineeringDepartment of Mechanical EngineeringDepartment of Mechanical EngineeringInstitute of Research DevelopmentProductivity and cost-effectiveness are essential components of any long-term manufacturing system. While quantity and quality are linked to productivity, the economy focuses on energy-efficient processes that produce a high output-to-input ratio. Hard-to-cut materials have always been difficult to machine because of more significant tool wear and power losses. Inconel 625 is a hard material used in aerospace and underwater applications and is milled using biolubricants with nanoparticles. Palm oil is considered a biolubricant, and titanium dioxide (TiO2) and copper oxide (CuO) are selected as nanoparticles. When the combination of biolubricants and nanoparticles is added to the workpiece’s surface, it enhanced some properties while machining. Experiments involving four factors with four levels were carried out using the Taguchi design of experiments (DoE). The feed, depth of cut, speed, and coolant with nanoparticle additives were all factors. The responses were surface roughness, spindle vibration along X, Y, and Z axes, and material removal rate. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was used to alter the multiresponse optimization problem to a single-response optimization problem. The S/N of TOPSIS closeness coefficients was calculated, and the optimal machining conditions were determined. Surface roughness, material removal rate, and spindle vibration were reduced by 3.10%, 6.14%, 7.54% (Vx), and 6.78% (Vz), respectively, due to the TOPSIS optimization.http://dx.doi.org/10.1155/2022/7210265
spellingShingle T. Mohanraj
N. Radhika
S. Aswin Nanda
V. Vignesh
B. Jayaraman
K. R. Ratana Selvan
Yesgat Admassu
Parameter Optimization and Machining Performance of Inconel 625 with Nanoparticles Dispersed in Biolubricant
Advances in Materials Science and Engineering
title Parameter Optimization and Machining Performance of Inconel 625 with Nanoparticles Dispersed in Biolubricant
title_full Parameter Optimization and Machining Performance of Inconel 625 with Nanoparticles Dispersed in Biolubricant
title_fullStr Parameter Optimization and Machining Performance of Inconel 625 with Nanoparticles Dispersed in Biolubricant
title_full_unstemmed Parameter Optimization and Machining Performance of Inconel 625 with Nanoparticles Dispersed in Biolubricant
title_short Parameter Optimization and Machining Performance of Inconel 625 with Nanoparticles Dispersed in Biolubricant
title_sort parameter optimization and machining performance of inconel 625 with nanoparticles dispersed in biolubricant
url http://dx.doi.org/10.1155/2022/7210265
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