Prof. Kap-Hwan Kim
Ocean College of Zhejiang University, China
Fellow of the Korean Academy of Science and Technology
Title of the Keynote Speech:
Smart design and operation of port container terminals
Bio:
Kap-Hwan Kim is working at Ocean College of Zhejiang University. Before joining to Zhejiang University, he had worked at the Department of Industrial Engineering of Pusan National University. He studied at the Seoul National University (Bachelor) and the Korea Advanced Institute of Science and Technology (Master, Ph.D.). He was the director of the Institute of Logistics Innovation and Networking at Pusan National University and the president of the Korean Institute of Industrial Engineers. He is a fellow of the Korean Academy of Science and Technology. His research is focused on the design and operational problems of container terminals. He published many papers at international journals such as OR Spectrum, Flexible Services and Manufacturing Journal, Transportation Science, Transportation Research B, Transportation Research E, European journal of Operational Research, and so on.
Abstract:
A smart port leverages innovative technologies and data-driven solutions to enhance port operations, management, and safety. With rapid technological innovations spurred by the Fourth Industrial Revolution (Industry 4.0), seaports are under pressure to transform their operations to handle traffic flows more efficiently. The concept of a smart port involves integrating digital technologies, automating processes, and enhancing visibility across end-to-end port operations without human intervention. The integration of algorithms with practical knowledge is crucial for smart container terminal operations. Researchers continue to bridge the gap between optimization models and real-world practices, ensuring efficient and safe port operations.
Prof. Norhazilan Md Noor
Universiti Teknologi Malaysia, Malaysia
Editor-in-Chief of the Malaysian Journal of Civil Engineering and the ASEAN Engineering Journal
Title of the Keynote Speech:
FUTURE CONCEPT OF GPT-DRIVEN RISK ASSESSMENT TOOL FOR OFFSHORE PIPELINE INTEGRITY
Bio:
An accomplished academician with more than two decades of experience in teaching, research, and administration. Possess excellent skills in managing organizations, including human resources, strategic planning, academic quality, and assets and facilities. Responsible for leading global networking efforts to enhance the faculty and university’s visibility, particularly in the ASEAN region. Additionally, play a crucial role in establishing a research domain focused on Reliability Engineering, which will support future research activities in line with IR 4.0.
Research Experience:
Currently holding the position of Professor at the Faculty of Civil Engineering, Universiti Teknologi Malaysia and specializes in pipeline integrity and has expertise in various areas such as structure reliability, and risk assessment. Serve as the Editor-in-Chief of the Malaysian Journal of Civil Engineering and the ASEAN Engineering Journal, and also hold the position of section editor for Jurnal Teknologi. Published over 200 articles, journals and conference proceedings with multiple awards for best publications. Possess extensive experience in global networking and have contributed to several world university ranking exercises, including the ASEAN University Network (AUN/SEED.net), the Erasmus+ project funded by the European Union, Tuning Academy, and the ISO Technical Committee of Offshore Structures (NSC H/TC 9 and TC 67/ SC 7). Actively involved in developing solutions for the oil and gas industry and marine port, with a primary focus on the reliability and risk management of deteriorating pipelines and marine infrastructure. The major project involves working on a probabilistic-based assessment framework and Digital Twin technology for marine infrastructure.
Abstract:
The assessment of offshore pipeline integrity against various degradation mechanisms is crucial for ensuring the long-term safety of subsea infrastructure. Traditional risk assessment methods, though effective, face a great challenge to deal with the complexity of various degradation mechanisms such as free spanning, internal corrosion, impact of dropped objects and many more. This will give rise to an idea for an innovative pipeline risk assessment tool powered by Generative Pre-trained Transformers (GPT), a type of large language model (LLM), designed to complement existing methodologies and provide a more comprehensive and rapid evaluation of pipeline risk with less human intervention. This innovative tool will harness the power of GPT to transform the system into a case-study-oriented system that utilizes unstructured textual evidence to assess the risk of deteriorating pipeline. The proposed system can be trained on extensive textual data such as technical reports, news articles, internal documents, etc. to improve the decision-making process. By analyzing diverse textual data sources, the GPT-driven system can simulate various pipeline condition including combined degradation scenario and deliver detailed outcome of the remaining capacity and risk profile of offshore pipelines. This will lead to a potential integration with digital twin systems which allows for a dynamic and real-time risk assessment framework. The GPT-driven tool’s advanced analytical capabilities could help digital twins, which are virtual replicas of physical assets, to monitor continuously and manage risks more effectively by tapping into enormous textual data that has been underutilized in the decision-making process. The objective of this integration is to transform decision-making processes, enabling timely interventions and optimized maintenance strategies that enhance operational safety and efficiency of the pipeline. The interaction between engineers and the proposed system will mimic human-to-human interaction and making it possible for the engineer to provide input through textual information for a quick response to the risk of pipeline failure. Although this system is still in the conceptual phase, its impact on the future of offshore pipeline risk management would be significant.
Prof. Wei-Cheng Wang
Department of Aeronautics and Astronautics,
National Cheng Kung University, Taiwan
Title of the Keynote Speech:
The development of Sustainable Aviation Fuel (SAF)
Bio:
Prof. Wei-Cheng Wang obtained his Ph.D. in North Carolina State University, NC, USA. After doctoral degree, he worked as a researcher in National Renewable Energy Laboratory (NREL), CO, USA for 2 years. In 2014, he joined the Department of Aeronautics and Astronautics, National Cheng Kung University, Taiwan. The research interests of Prof. Wang are fuel and combustion, and his research goal is to promote Fly Net Zero.
Abstract:
For the purpose of “Fly Net Zero”, sustainable aviation fuel (SAF) has been applied as an important fuel blend in most of the airline companies for reducing carbon emission. In this presentation, we are looking at the three most significant steps for developing SAF: fuel production process, engine combustion examinations, and process evaluations. Through the hydro-processing process, the SAF which meets all the specifications of jet fuel was produced. The combustion examinations, including ignition behaviors, laminar flame speed, and soot formation, were performed for the produced SAF. The SAF production process was evaluated in terms of energy, economy, and environment, for the purpose of being toward sustainability.