Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/100765
Author(s): Catarina Castro
Carlos Alberto Conceição António
Luísa Costa Sousa
Title: Accounting uncertainties in the optimal design of multi-stage hot forging
Issue Date: 2008
Abstract: Today, most of product designs employ sophisticated computer models and finite element analysis in their design. Most of thesemodels are based on physical models without taking into account the uncertainties that occur during manufacturing. Forging is anindustrial process extensively used in metal forming. Process uncertainties can cause defective parts and so incorporating uncertaintyanalysis on an optimization model will diminish rejected parts. On one hand a very narrow tolerance on the process parameterswould increase productions costs and on the other hand large tolerances would induce a high percentage of part rejection. Thus,controlling the tolerance limits on the process parameters would lead to an improvement on the product quality and to a reduction ofthe production costs of hot forged parts.Using a finite element thermal mechanical analysis coupled with a genetic algorithm an optimisation method has been developed forshape design of multi-stage forging processes. The design objective is to optimise the pre-form die shape and the initial temperatureof the billet in order to make the achieved final forging product to approach the desired one as much as possible. The computationalefficiency of the method simulating two-stage hot forging processes has been demonstrated earlier. The main purposes of this workare to identify, quantify and control uncertainties during the forming process based on a reasonable number of data sets acquired witha finite element analysis computer model. Initial temperature of the billet, friction between dies and billet and variations in theforging set up together with cooling rate are the main factors affecting the final part dimensions. Considering temperatures andfriction to be random variables, an attempt is made to fit a reasonable probability distribution to the different data sets. The analysisof the parameters uncertainties on the optimal pre-form die shape will drive to the robust design of the forging parameters.
Subject: Engenharia
Engineering
URI: https://repositorio-aberto.up.pt/handle/10216/100765
Source: EngOpt 2008 - International Conference on Engineering Optimization
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: restrictedAccess
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

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