報 告 人：Panpan Hu，VanJee Wuhan Research Institute
報告題目：Research and Development of Lidar and Its Applications
內容簡介：In recent years, with the continuous development of Lidar technology and products, its application value has been more emphasized in the fields of mobile robots, intelligent traffic perception, and automatic drives. This report summarizes and introduces the technical principle, development history, technical form, and product category of Lidar, and analyzes the specific requirements and current technical level of Lidar according to different application fields. In addition, in the form of cases, the report also focuses on the introduction of global awareness of intelligent transportation solutions based on Lidar.
報告人簡介：Panpan Hu is a Senior Engineer, the Chief Engineer of Laser technology of Vanjee Technology, and the President of Vanjee Wuhan Research Institute. He received his Ph.D. degree in Optical Engineering from Huazhong University of Science and Technology, Wuhan, China. He is also an expert in the Science and Technology Expert Database of Ministry of Communications, a member of the second Session of the Electronic Optical System Sub-Technical Committee of the National Optical and Photonics Standardization Technical Committee (TC103SC6), a member of the National Optical Radiation Safety and Laser Equipment Standardization Committee (TC284), an expert in the “Zhongguancun Standard” think tank, an expert in the expert database of Hubei Science and Technology Department, and an artificial intelligence expert of Wuhan Economy and Information Technology Bureau. He was elected into the ninth batch of Wuhan City "3551" Optical Valley Talent Program. His work was selected for the 2019 Major Scientific and Technological Innovation Database of Transportation of Ministry of Communications. In 2020, he won the sixth Beijing Invention Patent Award. He is currently involved in the preparation of one international standard and one national standard. In the past five years, he has authorized more than 50 invention patents and published 4 papers.
報 告 人：Ying Shi，Zhejiang Supcon Technology Co., Ltd
報告題目：Practice Study on Industrial Internet in Process Industry
內容簡介：Industrial Internet is aimed at the digitalization, networking, and intelligence needs of the manufacturing industry, building a data platform based on massive data collection, aggregation, and analysis. At the same time, Industrial Internet supports the ubiquitous connection of manufacturing resources, elastic supply, and efficient configuration in enterprise operations. This report focuses on the practical application of Industrial Internet platforms combined with continuous production and high-security integration in process industries, achieving the ultimate goal of improving safety, quality, efficiency, and environmental protection in process intelligent factories.
報告人簡介：Ying Shi is the President Assistant of Zhejiang Supcon Technology Co., Ltd. and the President of the New Business Incubation Department. As a technical leader, he has received the second prize of Zhejiang Provincial Science and Technology Progress Award, the second prize of Hangzhou Science and Technology Progress Award, and has been selected as a “131” young talent in Hangzhou. He has been granted 9 invention patents and participated in 2 key research and development projects of the Ministry of Science and Technology.
報 告 人：Tao Ren，WISDRI Engineering & Research Incorporation Ltd.
報告題目：WISDRI’s iBF Solution Promotes BLAST Furnace’s Digital Transformation
內容簡介：Steel enterprises play a vital role in China’s economy, but are also one of the main sources of carbon emissions. Blast furnaces, featuring high yield and high volume, reduction of carbon emissions of blast furnaces is a key branch of carbon neutrality. On the other hand, blast furnaces are labeled with the "black box" characteristics of high temperature, high pressure, sealing, and continuous production, and internal information is extremely scarce, making it difficult to implement synchronous monitoring. While maintaining stable and high production, how to reduce energy consumption has always been a global challenge. At present, the informatization, intelligence, and unmanned operation of blast furnaces are recognized as the key to solving the above problems.
Based on the demand for transparency in blast furnace production and the intelligent perception core, an intelligent blast furnace solution has been gradually constructed by WISDRI Corporation Ltd., Which actualized in six steps: less production personnel, intelligent management, transparency inside the furnace, prompt warning, comprehensive evaluation, and standardized guidance. Specific measures such as real-time monitoring of key areas through intelligent monitoring instruments, analysis on the mechanism and big data information of blast furnace status, and accurate analysis and judgment of blast furnace status based on expert rules. Helping blast furnace production to operate reasonably, scientifically, and effectively, ultimately achieve indicators optimization and management improvement, and accomplish the goals of blast furnace safety, efficiency, longevity, and green.
These achievements have made us the leader and the carbon neutrality practitioner of the ironmaking industry.
報告人簡介：Tao Ren is a Senior Engineer, and the Deputy Chief Engineer of the Intelligent Manufacturing Division of WISDRI Engineering and Research Inc. Ltd. He graduated in Control Theory and Control Engineering from HUST. His main research directions include industrial informatization and industrial intelligence.
報 告 人：Pengwei Tian，Alibaba Cloud
報告題目：Data Intelligence for Industrial Manufacturing: Practice Sharing
內容簡介：Data technology with artificial intelligence on top has been upgrading industrial manufacturing in the recent 10+ years, in both production and overall delivery process. The presentation will focus on the practice of research, development, and application of data intelligence solutions in industrial manufacturing, around multiple crucial topics like quality, production, energy, etc. with concrete technical use cases and lessons learned. The presentation aims to deliver some understanding and patterns from a practice point of view regarding how data intelligence benefits industrial manufacturing upgrading with added value.
報告人簡介：Pengwei Tian is the Senior Technical Expert and responsible for R&D of discrete manufacturing at Alibaba Cloud. Prior to his current post, he was Head of Research Group Data Analytics and AI at Siemens Technology China. Dr. Tian Peng Wei received his Ph.D. degree from Tsinghua University and has 10+ years of R&D experience in data and AI technology for industries, with solutions widely applied cross industrial verticals incl. manufacturing, energy & power, smart city, etc.
報 告 人：Pei Huang，e-works Ltd
報告題目：Trends and Practice of Digital Transformation in Chinese Manufacturing Sector
內容簡介：In this talk, I will introduce digital transformation models for manufacturing, data-driven X IIoT platform, big data analysis, and AI applications. Digital twin applications and going beyond: particularly on the digital transformation strategy toward building a digital ecosystem.
報告人簡介：Pei Huang is the CEO and editor-in-chief of e-works, Ltd. Dr. Huang is a member of the Chinese National Intelligent Manufacturing Expert Committee. He has 32 years experience of doing research, consulting, and training in the intelligent manufacturing area, and has been actively engaged in international cooperation in the intelligent manufacturing area. Dr. Huang started up e-works in 2002, which grows into a leading platform that links manufacturing enterprises, solution providers, and academia. Dr. Huang obtained his Ph.D. degree in mechanical engineering from Huazhong University of Science and Technology, Wuhan, China, in 1997. He got a senior management certificate from Rensselaer Polytechnic Institute, Troy, NY, in 2001.
報 告 人：Honglin Li，Dongfeng Motors
報告題目：Exploration of the Connected Collaborative Perception and Decision-Making Based on C-V2X in Dongfeng Motors
內容簡介：Intelligent connected vehicles refer to a new generation of intelligent vehicles equipped with advanced onboard sensing, decision-making planning and control, execution, and other devices, and integrating modern communication and network technology, enabling vehicles to have a complex environmental perception, intelligent decision-making and control functions, and can comprehensively achieve safety, energy conservation, environmental protection, and comfortable driving. From the perspective of perception and decision-making planning control carriers, intelligent connected vehicles can be divided into autonomous intelligent vehicles and connected vehicles. Among them, the perception and decision-making planning control carrier of autonomous intelligent vehicles is vehicles, while the perception or decision-making planning control carrier of connected vehicles is composed of vehicles and roadside equipment. The onboard perception unit of autonomous intelligent vehicles has many recognition limitations in blind spots, lane recognition under adverse weather conditions, beyond the line of sight perception, traffic signal recognition, and traffic guidance, which pose certain traffic safety hazards to intelligent driving vehicles. However, roadside intelligent terminals can compensate for the perception and planning control limitations of autonomous intelligent vehicles, forming a combination of autonomous and networked vehicle road coordination solutions, Thus improving traffic safety and improving traffic efficiency.
This presentation introduces Dongfeng Motor's practice in the field of vehicle road collaboration, including system architecture design for different application scenarios, achieving target-level integration between vehicle and road ends in the designed system architecture, and mainly solving difficulties such as target spatiotemporal synchronization and fusion spatial compensation. After completing the generation of collaborative perception targets, we attempt to reconstruct traffic environment information and achieve vehicle decision planning and control in various scenarios through reinforcement learning to complete vehicle traffic tasks.
報告人簡介：Honglin Li is the Chairman of the Intelligent Connected Vehicles Professional Technical Committee of DFM, the chief engineer of intelligent technology, and the pilot of the AI platform of DFM Technology Centre. With 20 years of working experience in the automotive industry, he has successively engaged in vehicle architecture design and intelligent driving system integration, and led the development of intelligent driving systems for multiple vehicles. Currently, he is engaged in research and engineering applications of V2X, and artificial intelligence, and serves as: an expert in the coordination of international standards and regulations of UN WP.29 GRVA; part-time doctoral supervisor for the professional degree of Wuhan University of Technology; managing director of IEEE PES Electric Vehicle Charging and Discharging Technology Subcommittee; committee member of Chinese Association for Artificial Intelligence.