Projects per year
Personal profile
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 4 Quality Education -
SDG 5 Gender Equality -
SDG 7 Affordable and Clean Energy -
SDG 8 Decent Work and Economic Growth -
SDG 9 Industry, Innovation, and Infrastructure -
SDG 17 Partnerships for the Goals
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Collaborations and top research areas from the last five years
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Projects
- 1 Finished
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人工智慧射出成型多目標品質預測最佳化之研究
Ke, K.-C. (PI)
2022/08/01 → 2023/07/31
Project: Government Ministry › Ministry of Science and Technology
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Investigation and predictive multi-modeling of PVA/PVP-blended nanofiber diameter in electrospinning
Chen, Y. J., Chang, T. L., Wu, Q. X., Ke, K.-C., Chiu, P. S. & Chen, C. T., 2025 Jan, In: International Journal of Advanced Manufacturing Technology. 136, 5, p. 2445-2453 9 p., 103425.Research output: Contribution to journal › Article › peer-review
12 Link opens in a new tab Citations (Scopus) -
Micro-Injection Compression Molding With In-Mold Sensing and Feature Extraction for Predicting Microlens Array Optical Quality
Chou, H. T., Cheng, T. Y., Tsai, Y. Y., Ke, K. C. & Yang, S. Y., 2025 Aug, In: Polymer Engineering and Science. 65, 8, p. 4387-4401 15 p.Research output: Contribution to journal › Article › peer-review
2 Link opens in a new tab Citations (Scopus) -
Cross-machine predictions of the quality of injection-molded parts by combining machine learning, quality indices, and a transfer model
Chang, C. H., Ke, K. C. & Huang, M. S., 2024 Aug, In: International Journal of Advanced Manufacturing Technology. 133, 9-10, p. 4981-4998 18 p.Research output: Contribution to journal › Article › peer-review
8 Link opens in a new tab Citations (Scopus) -
Data-driven quality prediction in injection molding: An autoencoder and machine learning approach
Ke, K. C., Wang, J. C. & Nian, S. C., 2024 Sept, In: Polymer Engineering and Science. 64, 9, p. 4520-4538 19 p.Research output: Contribution to journal › Article › peer-review
11 Link opens in a new tab Citations (Scopus) -
Multi-quality prediction of injection molding parts using a hybrid machine learning model
Ke, K. C., Wu, P. W. & Huang, M. S., 2024 Apr, In: International Journal of Advanced Manufacturing Technology. 131, 11, p. 5511-5525 15 p.Research output: Contribution to journal › Article › peer-review