Optimizing Injection Molding Tool Design with Additive Manufacturing: A Focus on Thermal Performance and Process Efficiency

Injection molding plays a pivotal role in modern manufacturing, enabling the mass production of complex components with high precision. However, traditional tooling methods often face challenges related to thermal management, design constraints, and material efficiency. This study examines the use of additive manufacturing (AM) in the development and optimization of injection molding tools to overcome these limitations. A novel prototype was fabricated using AM techniques, incorporating integrated cooling channels and optimized lattice structures to enhance thermal performance and simplify the manufacturing process. Experimental validation demonstrated the prototype's effective integration into a vacuum-assisted resin transfer molding (VA-LRTM) system without requiring modifications to existing tooling setups. The results showed significant improvements in temperature regulation, reduced cycle times, and consistent mechanical properties of the molded components compared to conventional approaches. By reducing the number of tool components and eliminating the need for support structures during manufacturing, AM also minimized material waste and post-processing requirements. This research highlights the transformative potential of additive manufacturing in injection molding tool design, offering increased flexibility, cost efficiency, and enhanced functionality to meet the evolving demands of modern industrial applications.

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Publication Details

Journal
Materials
Published
2025-01-27
DOI
https://doi.org/10.3390/ma18030571
Citations
3
Primary Topic
Injection Molding Process and Properties
Type
article
Field-Weighted Citation Impact
2.14

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article

Optimizing Injection Molding Tool Design with Additive Manufacturing: A Focus on Thermal Performance and Process Efficiency

Deviprasad Chalicheemalapalli Jayasankar, Thomas Tröster, Thorsten Marten
3 citations
Materials
Injection Molding Process and Properties
2.14
article

Optimizing Injection Molding Tool Design with Additive Manufacturing: A Focus on Thermal Performance and Process Efficiency

Deviprasad Chalicheemalapalli Jayasankar, Thomas Tröster, Thorsten Marten
article en
3 citations

Abstract

Injection molding plays a pivotal role in modern manufacturing, enabling the mass production of complex components with high precision. However, traditional tooling methods often face challenges related to thermal management, design constraints, and material efficiency. This study examines the use of additive manufacturing (AM) in the development and optimization of injection molding tools to overcome these limitations. A novel prototype was fabricated using AM techniques, incorporating integrated cooling channels and optimized lattice structures to enhance thermal performance and simplify the manufacturing process. Experimental validation demonstrated the prototype's effective integration into a vacuum-assisted resin transfer molding (VA-LRTM) system without requiring modifications to existing tooling setups. The results showed significant improvements in temperature regulation, reduced cycle times, and consistent mechanical properties of the molded components compared to conventional approaches. By reducing the number of tool components and eliminating the need for support structures during manufacturing, AM also minimized material waste and post-processing requirements. This research highlights the transformative potential of additive manufacturing in injection molding tool design, offering increased flexibility, cost efficiency, and enhanced functionality to meet the evolving demands of modern industrial applications.

MaterialsVol. 18(3)
Paderborn University (DE)
Universität Paderborn
Openalex Percentile: Top 16%
Injection Molding Process and Properties
2.14
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Optimizing Injection Molding Tool Design with Additive Manufacturing: A Focus on Thermal Performance and Process Efficiency — Deviprasad Chalicheemalapalli Jayasankar, Thomas Tröster, et al. · Materials (2025) | TGRS Research Map | TGRS