Prof. Xiaofang Yuan
College of electrical and information engineering ,Hunan University ,China
Experience: Dr. Xiaofang Yuan is a Professor in the Department of Electrical and Information Engineering at Hunan University. He has been a member of Chinese society of Mechanical Engineering, China Society of automation, and Chinese society of artificial intelligence. His research area includes intelligent control theory and application, electric vehicle control, robot drive control. His research has been funded by NNSF of China, Key R & D plan of the Ministry of science and technology, etc. He received the national science and technology progress award, and 6 provincial science and technology awards. He has published over 60 papers.
Speech Title：3D Map-based Path Planning for Autonomous Vehicles
In the traditional vehicle area, energy-based motion control technology and battery technology are usually employed to solve the energy-saving problem for vehicles. Our research proposes a new solution from the perspective of path planning. For vehicles traveling on the complex 3D terrains, the energy consumption of up-slope is far greater than that of the flat road and down-slope. To realize this, a path with a good trade-off between the energy consumption and distance would be the expected route for electric vehicle and mining transportation. A novel multi-objective path planning method is investigated to solve this problem for EV and mining truck. The simulation experiments prove that the proposed method can generate an optimal path which saves much energy in comparison with the path provided by the distance-based method.
Prof. Caixu Yue
School of Mechanical and Power Engineering, Harbin University of Science and Technology ,China
Experience: Professor Caixu Yue, Ph.D. tutor of Harbin University of Science and Technology, Vice-President of School of Mechanical and Power Engineering, Deputy Director of National & Local United Engineering Lab, 'Young Scholar' of Longjiang Scholar and Provincial Youth Fund recipient. His acquired his doctor’s degree from Harbin University of Science and Technology in 2013. His main research interesting focus on metal cutting, tool design and intelligent manufacturing process. He presided over more than 10 projects such as the National Key R & D Program of China and the National Natural Science Foundation of China. He has published more than 70 academic papers (including 70 SCI/EI papers and 2 “ESI” papers), and has got two science and technology awards, 7 invention patents and 1 software copyright.
Speech Title: Design and intelligent management for complex cutting tool
Tool is the "tooth" of the machine tool, and is one of the most active factors in the cutting process. Its state directly affects the processing quality and efficiency of the workpiece. Because the traditional highly customized tool design cycle is long and the efficiency is low, in order to design the tool quickly and accurately, a customer demand oriented "shape property use" integrated design platform for complex tools has been independently developed based on geometric and physical multi-source information fusion technology. The platform combines UG, ABAQUS, MySQL and other software together to realize tool parametric design, cutting process finite element simulation, cloud database management and tool optimization and evaluation functions, which shortens the tool design cycle by 40% and provides guidance for tool design theory and practical application. At the same time, a real-time perception system of multi-source information in the machining process under changing service conditions is built, a research on NC equipment and status traceability strategy based on functional requirements and data drive is proposed, and a cloud data sharing platform for the full life cycle information of complex tool design manufacturing application and the status of NC equipment is established, which realizes the construction of cutting big data cloud platform and the management of feature information. For typical equipment manufacturing enterprises, technical achievements can improve tool life, reduce inventory, reduce tool design cycle, and reduce losses caused by tool failures.
Assoc. Prof. Chinedum Okwudire
University of Michigan, America
Experience: Chinedum (Chi) Okwudire is an associate professor of Mechanical Engineering and Miller Faculty Scholar at the University of Michigan, where he also serves as the Special Assistant to the Dean for Manufacturing. His research is focused on exploiting knowledge at the intersection of machine design, control and computing to boost the performance of manufacturing automation systems at low cost. Chi has received a number of awards including the NSF CAREER Award; SME Outstanding Young Manufacturing Engineer Award; and UC Berkeley’s Russell Severance Springer Visiting Professorship. He was recently selected by SME as one of the 25 leaders transforming manufacturing. He has co-authored a number of best-paper-award-winning papers in the areas of manufacturing automation, control and mechatronics.
Speech Title: Toward Intelligent Process Control in LPBF Additive Manufacturing
Laser powder bed fusion (LPBF) additive manufacturing (AM) is gaining traction in a variety of high-value industries, like aerospace, biomedical and automotive. However, it suffers from lots of quality issues that are currently mitigated using trial-and-error or heuristic approaches, which are inflexible, non-scalable, and diminish the potential of AM. The idea of an “intelligent controller” that automatically determines optimal process parameters using physics-based and data-driven models has been proposed as a promising alternative to the status quo. In this talk, I will share some of our early work on SmartScan, an intelligent control algorithm for mitigating hot spots, residual stress and distortion in LPBF via online optimization of laser scan sequence using physics-based and data-driven models. A preliminary version of SmartScan has been applied to laser scanning of 316L stainless steel plates on single and dual-laser systems leading to about 50% reduction in distortion in each case. Ongoing work is focused on enabling SmartScan to be used for printing of full 3D parts, with fracture-prone metals and alloys
Assoc. Prof. NOUR FATHI SHEHATA ATTIA
Chemistry Division, National Institute of Standards (NIS), Egypt
Experience: Prof. Dr. Nour F. Attia is associate professor at chemistry division, National Institute of standards (NIS). Dr. Attia’s research contributions in the field of nanochemistry, energy storage, water treatments, gas separation, flame retardancy, sensors and greenhouse gases capture. Prof. Attia published more than 69 international papers in high impact factor journals and presented in more than 40 in international conferences. Additionally, Dr. Nour published 6 international patents (2 USA and 4 Korean) and two Egyptian patents were recently filled. He has been awarded several national and international prizes such as State Prize, National Institute of Standards Prize, Medal of Excellence from the first class from President of the Republic 2020 and Obada-Prize. Recently, he has been elected as a member of the Egyptian Young Academy of Sciences for 2021-2024. Moreover, he recently selected as Member of National Committee of New and Advanced Materials 2022-2025.
Speech Title: Hydrogen Energy as Clean Energy Source: Storage Media Challenges
Abstract: Cleaner production process in conjunction with sustainability is the main requirement for clean and cost-effective industrial process. Rapid depletion of fossil fuels and the associated extensive releases of harmful gases have led to energy supply and environmental pollution crises. Therefore, the implementation of renewable energy technologies such as the use of hydrogen as a clean and renewable alternative energy carrier for fuel cell vehicles is a matter of greater urgency . However, the development of safe, efficient, and convenient storage media remains a technical dilemma for its commercialization. To this end, in this talk energy crisis, hydrogen energy production, storage and commercialization promises and limitations will be discussed.