Analysis of Cutting Forces Response to Machining Parameters Under Dry and Wet Machining Conditions in X5CrNi18-10 Turning

The shift toward digital and smart manufacturing requires an accurate prediction of cutting behavior, such as cutting forces. Controlling cutting forces in machining is important for maintaining product quality, particularly in steels such as X5CrNi18-10. This steel has high toughness, which resists cutting, thereby increasing overall cutting forces. Proper selection of machining parameters and conditions can help reduce cutting forces during machining. Several studies have been dedicated to understanding the influence of cutting parameters on cutting forces. However, limited attention is given to the influence of the cutting conditions on cutting forces. The primary objective of this study is to understand the behavior of cutting forces in chromium-nickel alloy steel by varying machining parameters, specifically cutting conditions (dry and wet), using a full factorial (31 × 22) design of experiments (DoE). The secondary objective is to develop a multilinear regression model to predict cutting forces. The root mean square (RMS) values of the cutting force components were calculated from the acquired data and analyzed using OriginPro 2025b. In addition, this study analyzes the effects of cutting parameters and cutting forces on root mean square (RMS) surface roughness (Rq) to understand their impact on quality using the AltiSurf 520 profilometer. The results suggest a significant effect of the selected machining parameters and conditions on cutting force reduction and on improved surface quality when cutting forces are low. This research provides a valuable insight into optimizing the machining process for hard steels.

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Publication Details

Journal
Eng—Advances in Engineering
Published
2026-01-08
DOI
https://doi.org/10.3390/eng7010033
Citations
1
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
19.05
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article

Analysis of Cutting Forces Response to Machining Parameters Under Dry and Wet Machining Conditions in X5CrNi18-10 Turning

Csaba Felho, Daynier Rolando Delgado Sobrino, Tanuj Namboodri
1 citations
Eng—Advances in Engineering
Advanced machining processes and optimization
19.05
article

Analysis of Cutting Forces Response to Machining Parameters Under Dry and Wet Machining Conditions in X5CrNi18-10 Turning

Csaba Felho, Daynier Rolando Delgado Sobrino, Tanuj Namboodri
article en
1 citations

Abstract

The shift toward digital and smart manufacturing requires an accurate prediction of cutting behavior, such as cutting forces. Controlling cutting forces in machining is important for maintaining product quality, particularly in steels such as X5CrNi18-10. This steel has high toughness, which resists cutting, thereby increasing overall cutting forces. Proper selection of machining parameters and conditions can help reduce cutting forces during machining. Several studies have been dedicated to understanding the influence of cutting parameters on cutting forces. However, limited attention is given to the influence of the cutting conditions on cutting forces. The primary objective of this study is to understand the behavior of cutting forces in chromium-nickel alloy steel by varying machining parameters, specifically cutting conditions (dry and wet), using a full factorial (31 × 22) design of experiments (DoE). The secondary objective is to develop a multilinear regression model to predict cutting forces. The root mean square (RMS) values of the cutting force components were calculated from the acquired data and analyzed using OriginPro 2025b. In addition, this study analyzes the effects of cutting parameters and cutting forces on root mean square (RMS) surface roughness (Rq) to understand their impact on quality using the AltiSurf 520 profilometer. The results suggest a significant effect of the selected machining parameters and conditions on cutting force reduction and on improved surface quality when cutting forces are low. This research provides a valuable insight into optimizing the machining process for hard steels.

Eng—Advances in EngineeringVol. 7(1)
Slovak University of Technology in Bratislava (SK), University of Miskolc (HU)
Openalex Percentile: Top 3%
Advanced machining processes and optimization
19.05
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