汇报题目：参加The 33rd CIRP Design Conference国际会议回国报告
汇报时间：2023年6月3日上午8：00
汇报地点：创新港校区2号巨构5-162会议室
汇报人：徐青峰
会议名称：The 33rd CIRP Design Conference
会议时间：2023年5月17日—2023年5月19日
会议地点：澳大利亚悉尼
会议简介：Theme: "Grand Challenges in Engineering Design". The global society is facing a grand challenge, which is to meet current and future material needs of its growing populations, while staying within the environmental limits of our planet. In the meantime, society is experiencing rapid development of technologies such as Artificial Intelligence, Digitalisation and Servicetization of economies. As a result, the conference theme is identified as “Grand Challenges in Engineering Design” to address these challenges. These challenges also create unique opportunities for the design community to work towards developing innovative solutions and cutting-edge research in engineering design, Therefore, it is the aim of the conference to create a platform for the exchange of ideas and to investigate the role of engineering design in addressing these challenges by using innovative design thinking. With the strong support and participation of the global design community, an exciting conference program has been put together with four keynote speeches from industry and academia, and 200 technical presentations. These presentations cover a wide spectrum of topics on different facets of engineering design, such as design theory, design methodology, artificial intelligence, digital twin, product service system, product development, design for manufacturing, case studies, and more. The accepted papers that are presented successfully will be published as a part of the conference proceedings in Procedia CIRP.
参会论文信息：
Title：A Data and Knowledge-driven framework of the intelligent process design for special-shaped features of complex aviation parts
Author：Qingfeng Xu, Guanghui Zhoua, Chao Zhang, Fengtian Chang, Yan Cao
Abstract：While the safety and reliability of aviation equipment are directly determined by the performance of complex aviation parts, these kinds of components still contain lots of special-shaped features, which refer to the machining features that need to be completed by unique process and non-standard cutting tools. In addition, the traditional process design of special-shaped features of complex aviation parts (SFCAP) heavily relies on manual experience, which leads to low machining efficiency and unstable machining quality. To solve this problem, this paper takes SFCAP as the study object and proposes a framework of intelligent process design, which can effectively guarantee the processing quality to support the performance of complex aviation equipment by realizing active adaptive adjustment, rapid iteration, and upgrading of process planning based on the machining data and relative knowledge. Four key-enabling technologies are set forth to support the design, which include the special-shaped feature-process knowledge mapping model, 3D feature recognition and geometric parameter extraction, knowledge uncertainty-based evaluation, and digital twin-based verification and optimization. What’s more, the benefits and challenges of the design are analyzed, and the contribution and deficiencies are given at the end of this paper.
