Minimizing residual stresses in AISI 1045 steel through optimization of cutting parameters: A particle swarm optimization approach

This study deals with the effect of machining parameters on residual stresses caused during the end milling of AISI 1045 steel. A new tool insert was used for each trial, and residual stresses were measured on the machined surface after a single pass. From this analysis, it could be found that the increase of residual stresses becomes more tensile in nature because cutting speed and feed rate also go up along with increasing temperatures but compressive stress in cuts that require a larger depth. According to Taguchi's design of experiments, optimized cut parameters will show a decrease in the occurrence of residual stresses. Regression analysis showed that the cutting parameters explained 84% of the residual stress variation, with the feed rate being the most significant parameter ( P-value = 0.004). Optimization was done using particle swarm optimization which resulted in the optimal values which are as follows. A spindle speed of 710 r/min, feed rate, of 80 mm/min, and depth of cut, of 0.2 mm, which leads to a minimum residual stress of 203.73 MPa (compressive). This work can be considered as a framework for the prediction and optimization of machining parameters.

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Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering
Published
2025-02-16
DOI
https://doi.org/10.1177/09544089251318779
Primary Topic
Advanced machining processes and optimization
Type
article
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article

Minimizing residual stresses in AISI 1045 steel through optimization of cutting parameters: A particle swarm optimization approach

K. Marimuthu, M. Venkata Roshan, M. Thenarasu, Gudlanarva Sri Kurumurthy
Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering
Advanced machining processes and optimization
article

Minimizing residual stresses in AISI 1045 steel through optimization of cutting parameters: A particle swarm optimization approach

K. Marimuthu, M. Venkata Roshan, M. Thenarasu, Gudlanarva Sri Kurumurthy
article en

Abstract

This study deals with the effect of machining parameters on residual stresses caused during the end milling of AISI 1045 steel. A new tool insert was used for each trial, and residual stresses were measured on the machined surface after a single pass. From this analysis, it could be found that the increase of residual stresses becomes more tensile in nature because cutting speed and feed rate also go up along with increasing temperatures but compressive stress in cuts that require a larger depth. According to Taguchi's design of experiments, optimized cut parameters will show a decrease in the occurrence of residual stresses. Regression analysis showed that the cutting parameters explained 84% of the residual stress variation, with the feed rate being the most significant parameter ( P-value = 0.004). Optimization was done using particle swarm optimization which resulted in the optimal values which are as follows. A spindle speed of 710 r/min, feed rate, of 80 mm/min, and depth of cut, of 0.2 mm, which leads to a minimum residual stress of 203.73 MPa (compressive). This work can be considered as a framework for the prediction and optimization of machining parameters.

Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering
Amrita Vishwa Vidyapeetham (IN), Eindhoven University of Technology (NL)
Openalex Percentile: Top 97%
Advanced machining processes and optimization
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Minimizing residual stresses in AISI 1045 steel through optimization of cutting parameters: A particle swarm optimization approach — K. Marimuthu, M. Venkata Roshan, et al. · Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering (2025) | TGRS Research Map | TGRS