Probabilistic methodology for predicting the dispersionof residual stresses and Almen intensity considering shot peening process uncertainties

To ensure a high fatigue life and a reduced weight of automotive suspension system components, compressive residual stresses are commonly induced near the surface using many mechanical surface treatments. Among the most preferred techniques, shot peening process presents a high efficiency and a rela...

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Veröffentlicht in:International journal of advanced manufacturing technology 2018-02, Vol.94 (5-8), p.2125-2136
Hauptverfasser: Atig, A., Ben Sghaier, R., Seddik, R., Fathallah, R.
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container_issue 5-8
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container_title International journal of advanced manufacturing technology
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creator Atig, A.
Ben Sghaier, R.
Seddik, R.
Fathallah, R.
description To ensure a high fatigue life and a reduced weight of automotive suspension system components, compressive residual stresses are commonly induced near the surface using many mechanical surface treatments. Among the most preferred techniques, shot peening process presents a high efficiency and a relative low cost. Nevertheless, the employment of such process is generally affected by many sources of variability. Indeed, the experimental residual stress measurements exhibit a significant variation from one component to another and even from different positions on the same component. Therefore, error bars are commonly used to quantify the variability of experimental residual stress measurements. Nevertheless, the majority of predictive approaches of residual stresses induced by shot peening do not consider the effect of the variability of shot peening process parameters. In this study, a probabilistic methodology is applied to evaluate the variability of the induced residual stress profile and the Almen intensity, regarding the scattering of the most significant shot peening process parameters. Furthermore, iso-probabilistic residual stress profile can be utilized to predict the shot peening residual stress profile with a specified probability of appearance.
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subjects Automotive parts
Bars
CAE) and Design
Compressive properties
Computer-Aided Engineering (CAD
Engineering
Fatigue life
Fuel consumption
Industrial and Production Engineering
Mechanical Engineering
Media Management
Original Article
Probabilistic methods
Process parameters
Residual stress
Shot peening
Statistical analysis
Suspension systems
Variability
Weight reduction
title Probabilistic methodology for predicting the dispersionof residual stresses and Almen intensity considering shot peening process uncertainties
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