Projects per year
Personal profile
Education
- 1987 PhD, Mechanical Engineering, National Cheng Kung University
Research Interests
- AI Ship
- CAD/CAM
- Fluid Mechanics
Experience
- 1983/08 ~ 1988/07 Lecturer, Department of Naval Architecture and Marine Engineering, National Cheng Kung University
- 1988/08 ~ 1993/07 Associate Professor, Department of Naval Architecture and Marine Engineering, National Cheng Kung University
- 1993/08 ~ present Professor, Department of Systems and Naval Mechatronic Engineering, National Cheng Kung University
- 1994/08 ~ 1997/07 Chairman, Department of Naval Architecture and Marine Engineering, National Cheng Kung University
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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Collaborations and top research areas from the last five years
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Projects
- 38 Finished
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Marine big data analysis of ships for the energy efficiency changes of the hull and maintenance evaluation based on the ISO 19030 standard
Shaw, H. J. & Lin, C. K., 2021 Jul 15, In: Ocean Engineering. 232, 108953.Research output: Contribution to journal › Article › peer-review
12 Citations (Scopus) -
To Enhance the Display Factory’s Flexibility of Material Management by Applying TRIZ
Huang, W. C. & Shaw, H. J., 2021, In: International Journal of Systematic Innovation. 6, 3, p. 53-62 10 p.Research output: Contribution to journal › Article › peer-review
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以大數據分析建立船殼退化狀況的預測模型
Translated title of the contribution :ESTABLISHING A PREDICTION MODEL OF HULL DEGRADATION USING BIG DATA ANALYSIS Research output: Contribution to journal › Article › peer-review
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應用能效指標及統計方法進行船舶能效分析之研究
Translated title of the contribution :STUDY ON THE APPLICATION OF ENERGY EFFICIENCY INDICATORS AND STATISTICAL METHODS FOR SHIP ENERGY EFFICIENCY ANALYSIS Research output: Contribution to journal › Article › peer-review
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應用船舶大數據預測油耗之研究
Translated title of the contribution :STUDY ON PREDICTION OF MARINE FUEL CONSUMPTION WITH BIG DATA Research output: Contribution to journal › Article › peer-review