Analytical modeling of part distortion in metal additive manufacturing

Ning, Jinqiang; Praniewicz, Maxwell; Wang, Wenjia; Dobbs, James; Liang, Steven Y.

doi:10.1007/s00170-020-05065-8

Cited by 48 publications

(18 citation statements)

References 31 publications

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“…The temperature-dependent material properties should be considered in the temperature prediction with consideration of the heat-affected zone produced by previous scans. The part porosity [34,46], residual stress [47] and part distortion [48,49] can be further predicted from the temperature calculation.…”

Section: Resultsmentioning

confidence: 99%

Analytical Thermal Modeling of Powder Bed Metal Additive Manufacturing Considering Powder Size Variation and Packing

et al. 2020

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This work presents a computationally efficient predictive model based on solid heat transfer for temperature profiles in powder bed metal additive manufacturing (PBMAM) considering the heat transfer boundary condition and powder material properties. A point moving heat source model is used for the three-dimensional temperature prediction in an absolute coordinate. The heat loss from convection and radiation is calculated using a heat sink solution with a mathematically discretized boundary considering non-uniform temperatures and heat loss at the boundary. Powder material properties are calculated considering powder size statistical distribution and powder packing. The spatially uniform and temperature-independent material properties are employed in the temperature prediction. The presented model was tested in PBMAM of AlSi10Mg under different process conditions. The calculations of material properties are needed for AlSi10Mg because of the significant difference in thermal conductivity between powder form and solid bulk form. Close agreement is observed upon experimental validation on the molten pool dimensions.

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Section: Resultsmentioning

confidence: 99%

Analytical Thermal Modeling of Powder Bed Metal Additive Manufacturing Considering Powder Size Variation and Packing

et al. 2020

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“…A large thermal gradient caused by repeated rapid heating and solidification results in various defects within the manufactured part. In this context, the high prediction accuracy and computational efficiency allow that presented model be employed for prediction of part porosity [32] and part distortion [33], life-expectancy of a manufactured part, mechanical properties of the produced piece, and process parameter planning based on the given ones. The optimization of process parameters can be achieved with inverse analysis, such as gradient search method and topology optimization [34].…”

Section: Conclusion and Future Outlookmentioning

confidence: 99%

Estimation of clad geometry and corresponding residual stress distribution in laser melting deposition: analytical modeling and experimental correlations

Mahmood

Popescu

Hapenciuc

et al. 2020

Int J Adv Manuf Technol

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Laser melting deposition (LMD) is a promising technology to produce net-shape parts. The deposited layers' characteristics and induced residual stress distribution influence the quality, mechanical, and physical properties of the manufactured parts. In this study, two theoretical models are presented. Initially, the clad geometry of the 1st deposited layer is estimated using the primary process parameters. Then, a hatch distance is used to calculate the re-melting depth and total clad geometry for all the deposited layers. The output of the 1st model is then used as an input in the 2nd model to estimate the residual stress distribution within the substrate and deposited layers. The model, for clad geometry, is validated using published experimental data for the depositions of AISI316L powder debits on AISI321 bulk substrate by the LMD process. For the residual stress distribution model validation, the published experimental results for X-ray diffractometry, in case of AISI4340 steel powder debits depositions on the AISI4140 bulk substrate by the LMD setup, are used. It was found that the current models can estimate the clad geometry and induced residual stress distribution with an accuracy of 10–15 % mean absolute deviation. An optimum selection of hatch distance is necessary for proper energy density utilization and dimensional control stability. The induced residual stress distribution was caused by the heating and cooling mechanisms, which appeared due to rapid heating and moderate cooling, in combination with slow conduction. These phenomena became incrementally iterative with the number of layers to be deposited, thus presenting a direct relationship between the residual stress distribution and the number of layers deposited on the substrate. The proposed models have high computational efficiency without restoring the meshing and iterative calculations. The high prediction accuracy and computational efficiency allow the presented model to investigate further the part distortion, part porosity, life-expectancy and mechanical properties of the part, and process parameter planning.

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“…Finally, it was concluded that the bed pre-heating temperature was the most crucial parameter for reducing the residual stresses, as a 50 °C increase of the pre-heating temperature promoted an approximate 20% decrease of residual stresses, as shown in Figure 15. In another study, Ning et al [118] developed an analytical model that predicts RS and part distortion without the need for any iteration-based simulations or FEM. The inputs for the aforementioned model were the laser parameters, scan parameters, and material parameters, and the thermal model was calculated by a moving point heat source solution along with a heat sink solution.…”

Section: Residual Stressesmentioning

confidence: 99%

“…Finally, in Figure 16 and Figure 17, it is possible to analyze two similar diagrams that explain and summarize the expected mechanical properties and microstructures of as-built and heat-treated EBMed and SLMed Ti-6Al-4V components, respectively. In another study, Ning et al [118] developed an analytical model that predicts RS and part distortion without the need for any iteration-based simulations or FEM. The inputs for the aforementioned model were the laser parameters, scan parameters, and material parameters, and the thermal model was calculated by a moving point heat source solution along with a heat sink solution.…”

Section: Residual Stressesmentioning

confidence: 99%

A Review of Heat Treatments on Improving the Quality and Residual Stresses of the Ti–6Al–4V Parts Produced by Additive Manufacturing

Teixeira

Silva

Ferreira

et al. 2020

Metals

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Additive manufacturing (AM) can be seen as a disruptive process that builds complex components layer upon layer. Two of its distinct technologies are Selective Laser Melting (SLM) and Electron Beam Melting (EBM), which are powder bed fusion processes that create metallic parts with the aid of a beam source. One of the most studied and manufactured superalloys in metal AM is the Ti–6Al–4V, which can be applied in the aerospace field due to its low density and high melting point, and in the biomedical area owing to its high corrosion resistance and excellent biocompatibility when in contact with tissues or bones of the human body. The research novelty of this work is the aggregation of all kinds of data from the last 20 years of investigation about Ti–6Al–4V parts manufactured via SLM and EBM, namely information related to residual stresses (RS), as well as the influence played by different heat treatments in reducing porosity and increasing mechanical properties. Throughout the report, it can be seen that the expected microstructure of the Ti–6Al–4V alloy is different in both manufacturing processes, mainly due to the distinct cooling rates. However, heat treatments can modify the microstructure, reduce RS, and increase the ductility, fatigue life, and hardness of the components. Furthermore, distinct post-treatments can induce compressive RS on the part’s surface, consequently enhancing the fatigue life.

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Analytical modeling of part distortion in metal additive manufacturing

Cited by 48 publications

References 31 publications

Analytical Thermal Modeling of Powder Bed Metal Additive Manufacturing Considering Powder Size Variation and Packing

Analytical Thermal Modeling of Powder Bed Metal Additive Manufacturing Considering Powder Size Variation and Packing

Estimation of clad geometry and corresponding residual stress distribution in laser melting deposition: analytical modeling and experimental correlations

A Review of Heat Treatments on Improving the Quality and Residual Stresses of the Ti–6Al–4V Parts Produced by Additive Manufacturing

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