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<p>Binder jetting (BJT) suffers from unpredictable shrinkage during a sintering stage, which often causes dimensional inaccuracies in the final parts. This study proposes a framework to predict shrinkage in metal BJT using a representative volume element (RVE) approach. The framework can be utilized in a step-by-step manner as follows: (i) construct the RVE with the powder–binder microstructure and obtain homogenized material properties, (ii) calibrate an equivalent shrinkage-driving boundary condition using a simple reference geometry (a cubic specimen) by matching simulated and measured post-sintering dimensions, and (iii) apply the calibrated condition to arbitrary geometries to predict shrinkage and generate compensation shapes by reversing the loading directions. Using the calibrated model, alphabet-shaped specimens are simulated and validated by 2D profile overlap analysis, showing overlap ratios of 95.8% for A, 91.8% for H, and 90.1% for X. The proposed shrinkage prediction framework can be used as a more user-friendly and accessible method to examine shrinkage behavior, compared with specialized commercial sintering software that requires advanced expertise.</p>

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A Representative Volume Element-Based Approach for Predicting Sintering Shrinkage in Metal Binder Jetting

  • 期刊论文

  • 发表日期：

    2026年4月14日

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  • Seong Je Park,
  • Seungyon Cho,
  • Sangjun Jeon,
  • Seung Ki Moon

摘要

Binder jetting (BJT) suffers from unpredictable shrinkage during a sintering stage, which often causes dimensional inaccuracies in the final parts. This study proposes a framework to predict shrinkage in metal BJT using a representative volume element (RVE) approach. The framework can be utilized in a step-by-step manner as follows: (i) construct the RVE with the powder–binder microstructure and obtain homogenized material properties, (ii) calibrate an equivalent shrinkage-driving boundary condition using a simple reference geometry (a cubic specimen) by matching simulated and measured post-sintering dimensions, and (iii) apply the calibrated condition to arbitrary geometries to predict shrinkage and generate compensation shapes by reversing the loading directions. Using the calibrated model, alphabet-shaped specimens are simulated and validated by 2D profile overlap analysis, showing overlap ratios of 95.8% for A, 91.8% for H, and 90.1% for X. The proposed shrinkage prediction framework can be used as a more user-friendly and accessible method to examine shrinkage behavior, compared with specialized commercial sintering software that requires advanced expertise.