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Data-efficient prediction of wax pattern cooling time using a simplified thermal approach for rapid tooling applications.

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Title: Data-efficient prediction of wax pattern cooling time using a simplified thermal approach for rapid tooling applications.
Authors: Kuo, Chil-Chyuan1,2,3,4 (AUTHOR) jacksonk@mail.mcut.edu.tw, Lin, Pin-Han1 (AUTHOR), Chen, Ren-Hao1 (AUTHOR), Li, Ting-Wei1 (AUTHOR), Farooqui, Armaan1,5 (AUTHOR), Huang, Song-Hua6 (AUTHOR)
Source: International Journal of Advanced Manufacturing Technology. Nov2025, Vol. 141 Issue 5/6, p3375-3396. 22p.
Subjects: Rapid tooling, Prediction models, Thermal analysis, Sustainability, Energy consumption, Simulation methods & models, Injection molding
Abstract: Numerical simulations enhance injection molding by predicting cooling time, reducing costs, and improving quality. However, mesh resolution and modeling assumptions affect accuracy. This study implements a thickness-based correction mechanism to speed up the simulation of cooling time in low-pressure wax injection molding. The method aims to create a prediction model that balances fast computation with accurate results. A corrected simulation-based model for accurate and sustainable prediction of wax pattern cooling time in low-pressure injection molding using rapid tooling is presented. The corrected cooling time can be calculated from the heat content using the proposed equation with a coefficient of determination of about 0.99601. The proposed method achieved prediction accuracies of 91.19% and 93.16% for the cooling time of wax patterns. It also improved the efficiency of obtaining cooling times for golf club heads and piston components to 94.34% and 94.49%, respectively. Compared to the traditional method, the proposed prediction method in this study can reduce the power consumption and carbon emissions of the golf club head and piston components by approximately 94% and 94.5%, respectively. This demonstrates the sustainable potential of high-efficiency simulation and green manufacturing. These results confirm that the proposed method provides a good balance between accuracy and efficiency. In addition, it helps reduce carbon emissions and improve energy use. This demonstrates its strong potential for practical and sustainable applications. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Advanced Manufacturing Technology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 189391290
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Data-efficient prediction of wax pattern cooling time using a simplified thermal approach for rapid tooling applications.
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  Data: <searchLink fieldCode="AR" term="%22Kuo%2C+Chil-Chyuan%22">Kuo, Chil-Chyuan</searchLink><relatesTo>1,2,3,4</relatesTo> (AUTHOR)<i> jacksonk@mail.mcut.edu.tw</i><br /><searchLink fieldCode="AR" term="%22Lin%2C+Pin-Han%22">Lin, Pin-Han</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chen%2C+Ren-Hao%22">Chen, Ren-Hao</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Ting-Wei%22">Li, Ting-Wei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Farooqui%2C+Armaan%22">Farooqui, Armaan</searchLink><relatesTo>1,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Huang%2C+Song-Hua%22">Huang, Song-Hua</searchLink><relatesTo>6</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Advanced+Manufacturing+Technology%22">International Journal of Advanced Manufacturing Technology</searchLink>. Nov2025, Vol. 141 Issue 5/6, p3375-3396. 22p.
– Name: Subject
  Label: Subjects
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  Data: <searchLink fieldCode="DE" term="%22Rapid+tooling%22">Rapid tooling</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction+models%22">Prediction models</searchLink><br /><searchLink fieldCode="DE" term="%22Thermal+analysis%22">Thermal analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Sustainability%22">Sustainability</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+methods+%26+models%22">Simulation methods & models</searchLink><br /><searchLink fieldCode="DE" term="%22Injection+molding%22">Injection molding</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Numerical simulations enhance injection molding by predicting cooling time, reducing costs, and improving quality. However, mesh resolution and modeling assumptions affect accuracy. This study implements a thickness-based correction mechanism to speed up the simulation of cooling time in low-pressure wax injection molding. The method aims to create a prediction model that balances fast computation with accurate results. A corrected simulation-based model for accurate and sustainable prediction of wax pattern cooling time in low-pressure injection molding using rapid tooling is presented. The corrected cooling time can be calculated from the heat content using the proposed equation with a coefficient of determination of about 0.99601. The proposed method achieved prediction accuracies of 91.19% and 93.16% for the cooling time of wax patterns. It also improved the efficiency of obtaining cooling times for golf club heads and piston components to 94.34% and 94.49%, respectively. Compared to the traditional method, the proposed prediction method in this study can reduce the power consumption and carbon emissions of the golf club head and piston components by approximately 94% and 94.5%, respectively. This demonstrates the sustainable potential of high-efficiency simulation and green manufacturing. These results confirm that the proposed method provides a good balance between accuracy and efficiency. In addition, it helps reduce carbon emissions and improve energy use. This demonstrates its strong potential for practical and sustainable applications. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Advanced Manufacturing Technology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s00170-025-16766-3
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      – Code: eng
        Text: English
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        PageCount: 22
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      – SubjectFull: Rapid tooling
        Type: general
      – SubjectFull: Prediction models
        Type: general
      – SubjectFull: Thermal analysis
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      – SubjectFull: Energy consumption
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      – SubjectFull: Simulation methods & models
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      – SubjectFull: Injection molding
        Type: general
    Titles:
      – TitleFull: Data-efficient prediction of wax pattern cooling time using a simplified thermal approach for rapid tooling applications.
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            NameFull: Kuo, Chil-Chyuan
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              Text: Nov2025
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              Y: 2025
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