Comparative Analysis of Surface Roughness and Tool Wear under Dry, MQL, and Cryogenic Machining Conditions in Invar 36 Turning Operations

Invar 36 alloy is known for its exceptional stability, presents challenges due to its tendency to heat up while machining which can result in deformation and decreased precision. This investigation presents a comparative study of surface roughness and tool wear performance during dry, Minimum Quantity Lubrication (MQL) (using canola oil) and cryogenic (LN2) machining of Invar 36 alloy. The changes in surface roughness and tool flank wear with respect to varying feed rate have been evaluated. The results demonstrated that increasing feed rates resulted in rougher surfaces and higher tool wear. Compared to dry machining, MQL machining significantly reduced the surface roughness and tool wear by 14.31 % and 24.33 %, respectively. However, cryogenic machining performed exceptionally with a 20.6 % reduction in surface roughness and a 37.12 % reduction in tool wear based on number passes. Hence this work contributed to identifying suitable machining parameters along with a proper cooling technique for improving the tool life and surface finish during machining of Invar 36 alloy. Major Findings: According to this research, cryogenic machining reduced tool wear by up to 37.12% and surface roughness by 20.60% when compared to dry machining. Cryogenic machining has shown considerable advantages in turning operations, including longer tool life, higher surface roughness, making it a preferable cooling approach for machining of difficult to machine materials such as INVAR 36.

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Publication Details

Journal
Journal of Mines Metals and Fuels
Published
2025-04-16
DOI
https://doi.org/10.18311/jmmf/2025/47546
Citations
1
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
0.71
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article

Comparative Analysis of Surface Roughness and Tool Wear under Dry, MQL, and Cryogenic Machining Conditions in Invar 36 Turning Operations

Vikas Marakini, Lawrence D’Souza, P. Srinivasa Pai, Grynal D’Mello et al.
1 citations
Journal of Mines Metals and Fuels
Advanced machining processes and optimization
0.71
article

Comparative Analysis of Surface Roughness and Tool Wear under Dry, MQL, and Cryogenic Machining Conditions in Invar 36 Turning Operations

Vikas Marakini, Lawrence D’Souza, P. Srinivasa Pai, Grynal D’Mello, Smitha Shetty, Ashray, Elrick Winston Dsouza, Vivan Mendonca
article en
1 citations

Abstract

Invar 36 alloy is known for its exceptional stability, presents challenges due to its tendency to heat up while machining which can result in deformation and decreased precision. This investigation presents a comparative study of surface roughness and tool wear performance during dry, Minimum Quantity Lubrication (MQL) (using canola oil) and cryogenic (LN2) machining of Invar 36 alloy. The changes in surface roughness and tool flank wear with respect to varying feed rate have been evaluated. The results demonstrated that increasing feed rates resulted in rougher surfaces and higher tool wear. Compared to dry machining, MQL machining significantly reduced the surface roughness and tool wear by 14.31 % and 24.33 %, respectively. However, cryogenic machining performed exceptionally with a 20.6 % reduction in surface roughness and a 37.12 % reduction in tool wear based on number passes. Hence this work contributed to identifying suitable machining parameters along with a proper cooling technique for improving the tool life and surface finish during machining of Invar 36 alloy. Major Findings: According to this research, cryogenic machining reduced tool wear by up to 37.12% and surface roughness by 20.60% when compared to dry machining. Cryogenic machining has shown considerable advantages in turning operations, including longer tool life, higher surface roughness, making it a preferable cooling approach for machining of difficult to machine materials such as INVAR 36.

Journal of Mines Metals and Fuels
Openalex Percentile: Top 34%
Advanced machining processes and optimization
0.71
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