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<p>Additive manufacturing (AM), particularly Laser Powder Bed Fusion (L-PBF), has transformed mold and core fabrication in foundry applications by enabling complex geometries, rapid prototyping, and patternless production. Despite these advancements, the consistent achievement of high-dimensional accuracy, mechanical strength, and surface integrity in sand-based AM remains challenging due to intricate thermal–process parameter interactions. To address these issues, the present study aims to optimize the process parameters of an indigenously developed Sand-based Additive Manufacturing (SAAM) apparatus based on a flying-optics CO<sub>2</sub> laser for fabricating sand molds without conventional tooling. Four key parameters: laser power, layer thickness, scan speed, and overlap were analyzed for their influence on dimensional accuracy (diameter and height), compressive strength, surface porosity, and areal surface roughness. A Central Composite Design (CCD) under Response Surface Methodology (RSM) was used for modelling, followed by single- and multi-objective optimization using the Teaching Learning-Based Optimization (TLBO) algorithm. The regression models showed high predictive accuracy (R² &gt;96% for all responses), while the optimized process parameters yielded less than 4.24% deviation between predicted and experimental outcomes. The multi-objective optimization produced an optimal parameter set (t = 0.3946&#xa0;mm, <i>P</i> = 14.94&#xa0;W, v = 64.84&#xa0;mm/s, W = 19.52%) that enhanced mold quality and structural integrity, enabling the successful patternless casting of A356 aluminium alloy. Overall, this work provides an experimentally validated framework for parameter optimization in SAAM, highlighting its industrial potential for cost-effective, high-precision, and sustainable mold fabrication.</p>

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Additive manufacturing of patternless sand molds via laser powder bed fusion process: parametric analysis, performance characterization, and optimization

  • 期刊论文

  • 发表日期：

    2025年11月13日

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  • Yogesh Patil,
  • Swarup S. Deshmukh

摘要

Additive manufacturing (AM), particularly Laser Powder Bed Fusion (L-PBF), has transformed mold and core fabrication in foundry applications by enabling complex geometries, rapid prototyping, and patternless production. Despite these advancements, the consistent achievement of high-dimensional accuracy, mechanical strength, and surface integrity in sand-based AM remains challenging due to intricate thermal–process parameter interactions. To address these issues, the present study aims to optimize the process parameters of an indigenously developed Sand-based Additive Manufacturing (SAAM) apparatus based on a flying-optics CO2 laser for fabricating sand molds without conventional tooling. Four key parameters: laser power, layer thickness, scan speed, and overlap were analyzed for their influence on dimensional accuracy (diameter and height), compressive strength, surface porosity, and areal surface roughness. A Central Composite Design (CCD) under Response Surface Methodology (RSM) was used for modelling, followed by single- and multi-objective optimization using the Teaching Learning-Based Optimization (TLBO) algorithm. The regression models showed high predictive accuracy (R² >96% for all responses), while the optimized process parameters yielded less than 4.24% deviation between predicted and experimental outcomes. The multi-objective optimization produced an optimal parameter set (t = 0.3946 mm, P = 14.94 W, v = 64.84 mm/s, W = 19.52%) that enhanced mold quality and structural integrity, enabling the successful patternless casting of A356 aluminium alloy. Overall, this work provides an experimentally validated framework for parameter optimization in SAAM, highlighting its industrial potential for cost-effective, high-precision, and sustainable mold fabrication.