Dr. Adnan Saifan, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences., China
Dr. Adnan Saifan is a PhD candidate in Mechanical Manufacturing and Automation at the University of Chinese Academy of Sciences, Beijing, China, and Ningbo Institute of Materials Technology and Engineering. His research focuses on robotic surface processing technologies, including ultrasonic multi-needle peen forming. He holds a Masterโs in Mechanical Engineering from Hohai University, China, and a Bachelorโs from Sana’a University, Yemen. Dr. Saifanโs work is highly regarded, with several published papers in international journals and patents in the field of advanced manufacturing technologies. He is proficient in wear and corrosion analysis, additive manufacturing, and robotic systems.
Publication Profile
Google Scholar
Education & Qualifications ๐
Dr. Adnan Saifan holds a PhD in Mechanical Manufacturing and Automation from the University of Chinese Academy of Sciences and Ningbo Institute of Materials Technology and Engineering, China (2021-2025), focusing on robotic ultrasonic multi-needle peen forming technology. He earned a Master of Engineering (MEng) in Mechanical Engineering from Hohai University, Nanjing, China (2018-2021), with a thesis on automatic welding systems for boiler tube wall cladding. Dr. Saifan also holds a BSc in Mechanical Engineering from Sana’a University, Yemen (2011-2016), and various diplomas in Chinese Language, Computer Skills, and English. ๐๐
Work Experience & Projects ๐ผ
Dr. Adnan Saifan is currently a Doctoral Researcher at the University of Chinese Academy of Sciences and Ningbo Institute of Materials Technology & Engineering (2021โPresent), working on robotic ultrasonic shot peening for shape correction. Prior to this, he worked as a Mechanical Engineer at Suzhou Hailu Heavy Industry Co., Ltd., China (2019-2021), and as an intern at Mettler-Toledo, China (2019-2020), contributing to projects like the Saudi Arabia Railway Infrastructure. He also gained research experience at Hohai University (2018-2021), designing an automatic welding robot, and held various engineering roles in Yemen. ๐ ๏ธ๐
Honors & Awards ๐
Dr. Adnan Saifan has received numerous honors for his outstanding academic and research achievements. In 2023, he was recognized as the Outstanding International Student at Ningbo Institute of Materials Technology and Engineering and won the Silver Award at the Ningbo Graduate Academic Festival. He also received Honor Certificates from the Ministry of Higher Education-Yemen and the Yemeni Student Union of China. Additional accolades include the 2022 Outstanding Volunteer Award from the University of Chinese Academy of Sciences, the ANSO Scholarship for Young Talents, and several other scholarships and awards for excellence in research and contributions. ๐๐๐
Research Interests ๐ฌ
Dr. Adnan Saifan’s research interests focus on a wide range of topics within Mechanical Manufacturing and Automation, including Robotics, Additive Manufacturing, and Digital Twin technologies. His work also covers areas like Surface Mechanical Treatment, Material Processing, and Peen Forming, with a focus on Plastic Deformation and Welding. He is particularly interested in studying Wear and Mechanical Properties of materials, utilizing Finite Element (FE) Analysis and Optimization techniques. Additionally, Dr. Saifan applies Design of Experiment (DoE) methodologies to improve manufacturing processes and material performance. ๐ ๏ธ๐ค๐ง
Publication Top Notes ๐
- “Influence of post-weld heat treatment on microstructure and toughness properties of 13MnNiMoR high strength low alloy steel weld joint” – Cited by: 5, Year: 2021
- “Development of an automatic welding system for the boiler tube walls weld overlay” – Cited by: 3, Year: 2020
- “Data-driven modeling and optimization of a robotized multi-needle ultrasonic peen-forming process for 2024-T3 aluminum alloy” – Cited by: 1, Year: 2024
- “Seam tracking control for weld cladding of boiler tubes in thermal power plants” – Cited by: 1, Year: 2024
- “Enhancing microstructure and mechanical performance of 6061-T4 aluminum alloy through robotic ultrasonic multi-needle peening” – ย Year: 2024
- “Data-Driven Modelling of Robotized Ultrasonic Multi-Needle Peen-Forming Process on Aluminum Alloy 2024-T3” Year: 2024