Cryogenic and conventional machining using CVD-coated inserts to improve the surface characteristics of low-carbon steel alloy E350

The present study evaluates the effectiveness of dry and cryogenic machining environments while face milling carbon steel alloy E350, considering the surface integrity (SI) characteristics. The tests are performed using CVD-coated carbide inserts at three levels of cutting speed (150, 225, and 300 m...

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Main Authors: Sagar Vijayendra, Vikas Marakini, Raghavendra Pai K., Srinivasa Pai P., Gururaj Bolar
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Cogent Engineering
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Online Access:https://www.tandfonline.com/doi/10.1080/23311916.2025.2525442
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author Sagar Vijayendra
Vikas Marakini
Raghavendra Pai K.
Srinivasa Pai P.
Gururaj Bolar
author_facet Sagar Vijayendra
Vikas Marakini
Raghavendra Pai K.
Srinivasa Pai P.
Gururaj Bolar
author_sort Sagar Vijayendra
collection DOAJ
description The present study evaluates the effectiveness of dry and cryogenic machining environments while face milling carbon steel alloy E350, considering the surface integrity (SI) characteristics. The tests are performed using CVD-coated carbide inserts at three levels of cutting speed (150, 225, and 300 m/min), feed (0.05, 0.1, and 0.15 mm/tooth), and depth of cut (0.5, 1.0, and 1.5 mm). The primary SI features, roughness and microhardness, are evaluated. Furthermore, multi-criteria decision-making (MCDM) methods are employed to determine the best conditions for milling E350 alloy. Milling under cryogenic conditions reduced the roughness by 17% while increasing the microhardness by 14%, compared to dry milling conditions. The cutting speed significantly impacted the surface microhardness (92.2% – dry, 95.3% – cryogenic), and the feed had a greater impact on surface roughness (53.3% – dry, 67.5% – cryogenic). Furthermore, X-ray diffraction (XRD) pattern comparison provided more evidence for different levels of work hardening in milled surfaces compared to the polished as-cast material surface. Evaluation based on Distance from Average Solution (EDAS) and Grey Relational Analysis (GRA) methods showed identical outcomes, with optimal milling conditions for improved SI pegged at a cutting speed of 150 m/min, depth of cut of 1.5 mm, and feed of 0.05 mm/teeth.
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spelling doaj-art-dc97cd7d5ead43fcab6928faaa9e280d2025-08-20T03:28:28ZengTaylor & Francis GroupCogent Engineering2331-19162025-12-0112110.1080/23311916.2025.2525442Cryogenic and conventional machining using CVD-coated inserts to improve the surface characteristics of low-carbon steel alloy E350Sagar Vijayendra0Vikas Marakini1Raghavendra Pai K.2Srinivasa Pai P.3Gururaj Bolar4Department of Mechanical Engineering, Nitte (Deemed to be University), NMAM Institute of Technology (NMAMIT), Nitte, IndiaDepartment of Mechanical Engineering, Nitte (Deemed to be University), NMAM Institute of Technology (NMAMIT), Nitte, IndiaDepartment of Mechanical Engineering, Nitte (Deemed to be University), NMAM Institute of Technology (NMAMIT), Nitte, IndiaDepartment of Mechanical Engineering, Nitte (Deemed to be University), NMAM Institute of Technology (NMAMIT), Nitte, IndiaDepartment of Mechanical and Industrial Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, IndiaThe present study evaluates the effectiveness of dry and cryogenic machining environments while face milling carbon steel alloy E350, considering the surface integrity (SI) characteristics. The tests are performed using CVD-coated carbide inserts at three levels of cutting speed (150, 225, and 300 m/min), feed (0.05, 0.1, and 0.15 mm/tooth), and depth of cut (0.5, 1.0, and 1.5 mm). The primary SI features, roughness and microhardness, are evaluated. Furthermore, multi-criteria decision-making (MCDM) methods are employed to determine the best conditions for milling E350 alloy. Milling under cryogenic conditions reduced the roughness by 17% while increasing the microhardness by 14%, compared to dry milling conditions. The cutting speed significantly impacted the surface microhardness (92.2% – dry, 95.3% – cryogenic), and the feed had a greater impact on surface roughness (53.3% – dry, 67.5% – cryogenic). Furthermore, X-ray diffraction (XRD) pattern comparison provided more evidence for different levels of work hardening in milled surfaces compared to the polished as-cast material surface. Evaluation based on Distance from Average Solution (EDAS) and Grey Relational Analysis (GRA) methods showed identical outcomes, with optimal milling conditions for improved SI pegged at a cutting speed of 150 m/min, depth of cut of 1.5 mm, and feed of 0.05 mm/teeth.https://www.tandfonline.com/doi/10.1080/23311916.2025.2525442Low-carbon steelcryogenic millingroughnessmicrohardnessoptimizationMechanical Engineering Design
spellingShingle Sagar Vijayendra
Vikas Marakini
Raghavendra Pai K.
Srinivasa Pai P.
Gururaj Bolar
Cryogenic and conventional machining using CVD-coated inserts to improve the surface characteristics of low-carbon steel alloy E350
Cogent Engineering
Low-carbon steel
cryogenic milling
roughness
microhardness
optimization
Mechanical Engineering Design
title Cryogenic and conventional machining using CVD-coated inserts to improve the surface characteristics of low-carbon steel alloy E350
title_full Cryogenic and conventional machining using CVD-coated inserts to improve the surface characteristics of low-carbon steel alloy E350
title_fullStr Cryogenic and conventional machining using CVD-coated inserts to improve the surface characteristics of low-carbon steel alloy E350
title_full_unstemmed Cryogenic and conventional machining using CVD-coated inserts to improve the surface characteristics of low-carbon steel alloy E350
title_short Cryogenic and conventional machining using CVD-coated inserts to improve the surface characteristics of low-carbon steel alloy E350
title_sort cryogenic and conventional machining using cvd coated inserts to improve the surface characteristics of low carbon steel alloy e350
topic Low-carbon steel
cryogenic milling
roughness
microhardness
optimization
Mechanical Engineering Design
url https://www.tandfonline.com/doi/10.1080/23311916.2025.2525442
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