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RESEARCH PRODUCT
Influence of material properties variability on springback and thinning in sheet stamping processes: a stochastic analysis
Laura MarrettaRosa Di Lorenzosubject
EngineeringSpringbackbusiness.industryStochastic processMechanical EngineeringSheet stampingAutomotive industryProcess designStructural engineeringStampingStochastic material variabilityIndustrial and Manufacturing EngineeringFinite element methodComputer Science ApplicationsControl and Systems EngineeringRobustness (computer science)Process optimizationMaterial propertiesbusinessThinningSettore ING-IND/16 - Tecnologie E Sistemi Di LavorazioneSoftwaredescription
A very critical issue for stamping operations is the improvement of process robustness. The reliability of final results, in fact, strongly depends on the intrinsic variability due to stochastic behavior of many parameters, namely, operative ones and material properties. A given process performance may undergo a variation around the value which would be obtained neglecting stochastic behaviors of the operative or material parameters (i.e., considering a deterministic parameters behavior). Such variation introduces a significant source of uncertainty within the process design: a possible consequence may be the rejection of some stamped parts. In this paper, reliability analyses aimed to evidence and quantify the effects of material coil-to-coil variations on springback and thinning phenomena is proposed. In particular, an aluminum alloy typical of automotive applications was considered and an S-shaped U-channel process was investigated. The stochastic analysis was performed within several operative windows at the varying of restraining forces. Formerly, a sensitivity analysis was carried out in order to evaluate the single effect of each selected material parameter and to screen the most influent ones. Subsequently, a finite element method-response surface methodology-Monte Carlo simulation-integrated approach was implemented to quantify such effects. The proposed methodology provides the possibility to powerfully analyze material variability effect on the final process quality, assisting the designer in a subsequent process optimization.
year | journal | country | edition | language |
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2010-04-11 |