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Predictive modeling of porosity in AlSi10Mg alloy fabricated by laser powder bed fusion: A comparative study with RSM, ANN, FL, and ANFIS

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Abstract

The laser powder bed fusion (LPBF) process is commonly used in additive manufacturing (AM) to produce integrated parts from metallic powder. However, this process can result porosity in fabricated components due to gas bubbles or lack of fusion. In this study, four different methods (response surface methodology, artificial neural network, fuzzy logic, and adaptive-network-based fuzzy inference system (ANFIS)) were employed to predict the correlation between process parameters and porosity levels in AlSi10Mg alloy produced by the LPBF process. The ANFIS method utilizes fuzzy rules and artificial neural networks to predict the impact of process parameters, such as island size, hatch space, scan speed, and laser power on porosity levels. The results shows that the laser power and scan speed have a significant effect on the volume of porosity, while the influence of island size and hatch space were slighter in the LPBF process of AlSi10Mg alloy. Furthermore, the ANFIS model demonstrates an excellent fitting parameter with an R2 value of more than 0.99 for the total data and an RMSE of about 0.67 for the output. This result indicates that the ANFIS method is the best model among all the methods tested in accurately predicting the process target. The success of the ANFIS method in this study suggests that it is a robust and reliable technique for predicting porosity levels in the LPBF process.

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Authors and Affiliations

  1. Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran

    Ahmad Memaran Babakan & Mohammad Davoodi

  2. Department of Mechanical Engineering, Amirkabir University of Technology, Tehran, Iran

    Majid Shafaie

  3. Department of Mechanical, Industrial & Manufacturing Engineering, The University of Toledo, Toledo, OH, USA

    Mohsen Sarparast & Hongyan Zhang

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  1. Ahmad Memaran Babakan
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  2. Mohammad Davoodi
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  3. Majid Shafaie
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Correspondence to Mohsen Sarparast.

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Babakan, A.M., Davoodi, M., Shafaie, M. et al. Predictive modeling of porosity in AlSi10Mg alloy fabricated by laser powder bed fusion: A comparative study with RSM, ANN, FL, and ANFIS. Int J Adv Manuf Technol 129, 1097–1108 (2023). https://doi.org/10.1007/s00170-023-12333-w

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