
pmid: 38707300
pmc: PMC11068625
Résumé Cette étude présente une méthodologie pour optimiser les paramètres clés d'une imprimante à modélisation par dépôt fondu (FDM) afin de minimiser la consommation d'énergie (EC) tout en dépassant un seuil de résistance à la traction (TS) spécifié. En utilisant la conception d'expériences (DoE) avec l'analyse de Taguchi et de surface de réponse, nous identifions les paramètres influents affectant TS et EC. Un modèle d'optimisation multiobjectif non linéaire à nombres entiers mixtes est ensuite utilisé pour équilibrer TS et EC, ce qui permet d'obtenir des valeurs de paramètres optimales. La validation à l'aide d'échantillons fabriqués démontre moins de 5% d'erreur dans la résistance à la traction et moins de 2% d'erreur dans la consommation d'énergie, confirmant l'efficacité de la méthodologie proposée.
Resumen Este estudio presenta una metodología para optimizar los parámetros clave de una impresora de modelado por deposición fundida (FDM) para minimizar el consumo de energía (EC) mientras se excede un umbral de resistencia a la tracción (TS) especificado. Empleando el diseño de experimentos (DoE) con Taguchi y el análisis de la superficie de respuesta, identificamos los parámetros influyentes que afectan a TS y EC. A continuación, se utiliza un modelo de optimización multiobjetivo no lineal de enteros mixtos para equilibrar TS y EC, lo que da como resultado valores de parámetros óptimos. La validación utilizando muestras fabricadas demuestra menos del 5% de error en la resistencia a la tracción y menos del 2% de error en el consumo de energía, lo que confirma la eficacia de la metodología propuesta.
Abstract This study presents a methodology for optimizing key parameters of a fused deposition modeling (FDM) printer to minimize energy consumption (EC) while exceeding a specified tensile strength (TS) threshold. Employing Design of Experiments (DoE) with Taguchi and Response Surface analysis, we identify influential parameters affecting TS and EC. A Mixed-Integer Nonlinear Multi-Objective Optimization model is then utilized to balance TS and EC, resulting in optimal parameter values. Validation using fabricated specimens demonstrates less than 5% error in Tensile Strength and less than 2% error in Energy Consumption, confirming the efficacy of the proposed methodology.
الملخص تقدم هذه الدراسة منهجية لتحسين المعلمات الرئيسية لطابعة نمذجة الترسيب المنصهر لتقليل استهلاك الطاقة مع تجاوز عتبة مقاومة الشد المحددة. باستخدام تصميم التجارب (DoE) مع تحليل تاغوشي والاستجابة السطحية، نحدد المعلمات المؤثرة التي تؤثر على TS و EC. ثم يتم استخدام نموذج تحسين متعدد الأهداف غير خطي مختلط العدد لموازنة TS و EC، مما يؤدي إلى قيم المعلمات المثلى. يوضح التحقق باستخدام عينات ملفقة خطأ أقل من 5 ٪ في قوة الشد وخطأ أقل من 2 ٪ في استهلاك الطاقة، مما يؤكد فعالية المنهجية المقترحة.
Design for Manufacture and Assembly in Manufacturing, Composite material, Science (General), Taguchi design, Additive manufacturing, FOS: Mechanical engineering, Structural engineering, Quantum mechanics, Industrial and Manufacturing Engineering, Nonlinear Multi-objective optimization, Q1-390, Mechanical Performance, Engineering, Nonlinear programming, FOS: Mathematics, H1-99, Design for Manufacture, Physics, Mathematical optimization, Statistics, Integer programming, 3D printing, Building and Construction, Additive Manufacturing and 3D Printing Technologies, Computer science, Materials science, Mechanical engineering, 3D Concrete Printing Technology, Programming language, Social sciences (General), Energy consumption, Ultimate tensile strength, Electrical engineering, Automotive Engineering, Physical Sciences, Nonlinear system, Process engineering, Integer (computer science), Energy (signal processing), Design of experiments, Mathematics, Response surface design, Research Article
Design for Manufacture and Assembly in Manufacturing, Composite material, Science (General), Taguchi design, Additive manufacturing, FOS: Mechanical engineering, Structural engineering, Quantum mechanics, Industrial and Manufacturing Engineering, Nonlinear Multi-objective optimization, Q1-390, Mechanical Performance, Engineering, Nonlinear programming, FOS: Mathematics, H1-99, Design for Manufacture, Physics, Mathematical optimization, Statistics, Integer programming, 3D printing, Building and Construction, Additive Manufacturing and 3D Printing Technologies, Computer science, Materials science, Mechanical engineering, 3D Concrete Printing Technology, Programming language, Social sciences (General), Energy consumption, Ultimate tensile strength, Electrical engineering, Automotive Engineering, Physical Sciences, Nonlinear system, Process engineering, Integer (computer science), Energy (signal processing), Design of experiments, Mathematics, Response surface design, Research Article
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| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
