2014
DOI: 10.1115/1.4026524
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Effect of Thermal Deformation on Part Errors in Metal Powder Based Additive Manufacturing Processes

Abstract: In metal additive manufacturing (AM) processes, parts are manufactured in layers by sintering or melting metat or metal altoy powder under the effect of a powerful taser or an electron beam. As the laser/electron beam scans the powder bed, it melts the powder in successive tracks which overlap each other. This overlap, called the hatch overlap, results in a continuous cycle of rapid melting and resolidiflcation of the metat. The metting of the metal from powder to liquid and subsequent sotidification causes an… Show more

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Cited by 149 publications
(70 citation statements)
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“…Significant temperature gradients in the part can result in thermal deformation and the inheritance of residual stress [178]. This is due to thermal strains being developed between M a n u s c r i p t successive layers due to anisotropic shrinkage in deposition layers.…”
Section: Bulk Heating and Thermal Cyclingmentioning
confidence: 98%
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“…Significant temperature gradients in the part can result in thermal deformation and the inheritance of residual stress [178]. This is due to thermal strains being developed between M a n u s c r i p t successive layers due to anisotropic shrinkage in deposition layers.…”
Section: Bulk Heating and Thermal Cyclingmentioning
confidence: 98%
“…This is due to thermal strains being developed between M a n u s c r i p t successive layers due to anisotropic shrinkage in deposition layers. This further leads to stress gradients resulting in part warping and distortion [178]. Patel and Patel numerically demonstrated that the height-wise thermal stress is dominant and that the starting point for each new deposition layer has a strong effect on the intensity and distribution of thermal stress [179].…”
Section: Bulk Heating and Thermal Cyclingmentioning
confidence: 99%
“…Therefore, we adopt an alternative model studies in Ref. [8] gi(0,ro(9)) = )Vo + JVo«>s(20) (7) A Bayesian procedure was implemented to draw inferences on all parameters P0,P l ,a,b, and a. We calculated the posterior dis tribution of the parameters by Markov Chain Monte Carlo (MCMC) and summarized the marginal posteriors by taking the mean, median, standard deviation, and 2.5% and 97.5% quantiles of the posterior draws in Table 4.…”
Section: Statistical Modeling Strategymentioning
confidence: 99%
“…Despite these promising features, dimensional accuracy control remains a major bottleneck for the application of 3D printing in direct manufacturing [6][7][8][9]. Shape deviations of AM built prod ucts can be attributed to multiple variation sources.…”
Section: Introductionmentioning
confidence: 99%
“…In some of the recent additive manufacturing research, the effects of interpass idle time [4], heat transfer rate [5], and slice thickness [6] on thermal stresses and part distortions were investigated. However, due to water's high latent heat, the small difference between solidus and ambient temperatures, and the variety of paste materials in the FEF process, the consequence of selected improper process parameters is amplified.…”
Section: Introductionmentioning
confidence: 99%