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<p>Four-dimensional (4D) printing of shape memory polymers like polylactic acid (PLA) enables smart devices; however, accurately predicting their deformation value remains a challenge due to the complex influence of printing parameters. This study investigates the effects and interactions of three key printing parameters—extrusion width, printing speed, and layer height—on the deformation value behavior of 4D-printed PLA. A Central Composite Design (CCD) guided the experimental design, and Response Surface Methodology (RSM) was used to develop a predictive regression model. Results revealed that extrusion width was the most significant factor (34.2% contribution). An optimal parameter combination (extrusion width: 0.4&#xa0;mm, speed: 107.68&#xa0;mm/s, layer height: 0.107&#xa0;mm) was identified, achieving a deformation value of 49.62&#xa0;mm with a negligible 0.57% error from the model's prediction. This work provides a validated framework for optimizing 4D printing parameters, advancing the development of programmable smart structures for biomedical and aerospace applications.</p>

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Experimental Study of the Effects of Extrusion Width, Layer Height, and Printing Speed on Deformation Value in 4D-Printed Polylactic Acid Rectangular Specimens

  • 期刊论文

  • 发表日期：

    2025年10月31日

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  • Behnam Akhoundi

摘要

Four-dimensional (4D) printing of shape memory polymers like polylactic acid (PLA) enables smart devices; however, accurately predicting their deformation value remains a challenge due to the complex influence of printing parameters. This study investigates the effects and interactions of three key printing parameters—extrusion width, printing speed, and layer height—on the deformation value behavior of 4D-printed PLA. A Central Composite Design (CCD) guided the experimental design, and Response Surface Methodology (RSM) was used to develop a predictive regression model. Results revealed that extrusion width was the most significant factor (34.2% contribution). An optimal parameter combination (extrusion width: 0.4 mm, speed: 107.68 mm/s, layer height: 0.107 mm) was identified, achieving a deformation value of 49.62 mm with a negligible 0.57% error from the model's prediction. This work provides a validated framework for optimizing 4D printing parameters, advancing the development of programmable smart structures for biomedical and aerospace applications.