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Formation of Compressive Residual Stress by Face Milling Steel AISI 1045
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Abstract

     Machining residual stresses correlate very closely with the cutting parameters and the tool geometries. This research work aims to investigate the effect of cutting speed, feed rate and depth of cut on the surface residual stress of steel AISI 1045 after face milling operation. After each milling test, the residual stress on the surface of the workpiece was measured by using X-ray diffraction technique. Design of Experiment (DOE) software was employed using the response surface methodology (RSM) technique with a central composite rotatable design to build a mathematical model to determine the relationship between the input variables and the response. The results showed that both the feed rate and the cutting speed are the significant factors controlling the surface residual stress, while the depth of cut had no influence. A quadratic empirical model was developed with a 95% confidence level, and a good agreement was found between the experimental and predicted results. A numerical optimization was then conducted through DOE program to find the optimum surface residual stress at the optimum cutting parameters, depending on the maximum desirability obtained. The optimum compressive surface residual stress (-224.361 MPa) was found at cutting speed of 69.2 m/min, feed rate of 0.4 m/min and depth of cut of 0.4 mm.

Keywords: Face milling, Cutting parameters, Steel AISI 1045, Residual stresses, XRD; DOE, RSM, Modeling and Numerical optimization.

 

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Publication Date
Wed Nov 01 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
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Publication Date
Thu Dec 24 2020
Journal Name
Advances In Civil Engineering
Analytical study on torsional behavior of concrete beams strengthened with fiber reinforced polymer laminates using softened truss model
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Fri Jan 01 2021
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Microchemical Journal
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Thu Feb 01 2024
Journal Name
Structures
Accelerating reliability analysis of deteriorated simply supported concrete beam with a newly developed approach: MCS, FORM and ANN
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Reliability analysis methods are used to evaluate the safety of reinforced concrete structures by evaluating the limit state function 𝑔(𝑋𝑖). For implicit limit state function and nonlinear analysis , an advanced reliability analysis methods are needed. Monte Carlo simulation (MCS) can be used in this case however, as the number of input variables increases, the time required for MCS also increases, making it a time consuming method especially for complex problems with implicit performance functions. In such cases, MCS-based FORM (First Order Reliability Method) and Artificial Neural Network-based FORM (ANN FORM) have been proposed as alternatives. However, it is important to note that both MCS-FORM and ANN-FORM can also be time-con

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Tue Sep 01 2015
Journal Name
Journal Of Engineering
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Wed Apr 01 2020
Journal Name
Groundwater For Sustainable Development
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Wed Jan 01 2014
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Publication Date
Tue Jun 01 2021
Journal Name
Journal Of Petroleum Exploration And Production Technology
Incremental and acceleration production estimation and their effect on optimization of well infill locations in tight gas reservoirs
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