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<p>This work presents an experimental workflow coupled with statistical tools to optimize L-DED processing parameters to build defect-free AlSi10Mg multilayer parts. Experimental steps included the quantitative evaluation of single beads, single layers, and multilayers to define L-DED processing windows. Regression and desirability functions, together with multi-objective Bayesian optimization, were used to optimize the main L-DED process parameters to meet target single-layer features. The systematic collection of reliable experimental data was critical to the success of the optimization models, and a detailed methodology is provided. The proposed workflow enabled the production of crack- and macroporosity-free multilayer parts with high geometrical accuracy and metallurgical bond integrity, achieving densities from 99.55% to 99.80% and deposition efficiencies between 87 and 97%, significantly exceeding previously reported values. This work provides practical guidelines to evaluate the outcomes of the AM L-DED process and obtain multilayer AlSi10Mg parts free from deleterious defects.</p>

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Gaussian process regression for optimizing L-DED processing parameters in AlSi10Mg additive manufacturing

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月31日

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  • Jurandir Marcos Sá de Sousa,
  • Henrique Santos Ferreira,
  • Anselmo Thiesen,
  • Marcos Vinicius Bento,
  • William Mendes de Farias,
  • Priscila Maria Barra Ferreira,
  • Mustafa Awd,
  • Evgeniya Kabliman,
  • Alexandre Pinhel Soares,
  • Juliane Ribeiro da Cruz

摘要

This work presents an experimental workflow coupled with statistical tools to optimize L-DED processing parameters to build defect-free AlSi10Mg multilayer parts. Experimental steps included the quantitative evaluation of single beads, single layers, and multilayers to define L-DED processing windows. Regression and desirability functions, together with multi-objective Bayesian optimization, were used to optimize the main L-DED process parameters to meet target single-layer features. The systematic collection of reliable experimental data was critical to the success of the optimization models, and a detailed methodology is provided. The proposed workflow enabled the production of crack- and macroporosity-free multilayer parts with high geometrical accuracy and metallurgical bond integrity, achieving densities from 99.55% to 99.80% and deposition efficiencies between 87 and 97%, significantly exceeding previously reported values. This work provides practical guidelines to evaluate the outcomes of the AM L-DED process and obtain multilayer AlSi10Mg parts free from deleterious defects.