学术报告通知:Smart Manufacturing with a Decentralized and Distributed Regime

发布者:姚晟靖发布时间:2024-04-08浏览次数:10


报告时间:48日周一下午13:00

报告地点:先进制造大楼103会议室

报告题目:Smart Manufacturing with a Decentralized and Distributed Regime

报告人:Xun Xu教授

Chair Professor of Smart Manufacturing, University of Auckland (New Zealand)

  

报告人简介

Xun W. Xu is a professor of Smart Manufacturing at the Department of Mechanical and Mechatronics Engineering, The University of Auckland. He has been working in the field of intelligent manufacturing solutions for over 30 years. Dr. Xu is an internationally recognized expert in smart manufacturing systems, STEP-NC, cloud-based manufacturing and IoT-enabled manufacturing. He serves as an Associate Editor and member of the Editorial Board of a number of international journals and has published over 430 research papers. Dr. Xu is the Director of the Laboratory for Industry 4.0 Smart Manufacturing Systems (LISMS), the only Laboratory for Industry 4.0 in New Zealand. His current research focus is on Industry 4.0 technologies, e.g. smart factories, digital twins, and cloud manufacturing. Dr. Xu is a Fellow of the American Society for Mechanical Engineers (ASME) and Engineering New Zealand (EngNZ). He was recognized by the Web of Science as a Clarivate™ Highly Cited Researcher in 2020. In the same year, he was named among of the “20 Most Influential Professors in Smart Manufacturing” by the Society of Manufacturing Engineers (SME). Dr. Xu is now on the Board of Directors of the North American Manufacturing Research Institution of SME (NAMRI/SME) and NAMRI Scientific Committee Chair-Elect.

  

报告摘要

In an effort to take on the unprecedented challenges of volatile global demand, together with the mandate of sustainable digital transformation, manufacturing systems need to be robust, agile, and smart with sometimes extreme ASAP-delivery capabilities. Contemporary digital capabilities and advances over widespread networks promise new ways of meeting the challenges. These capabilities are for example high-power computation, cloud and edge computing services, and lower-cost sensing, many of which have been captured in Industry 4.0 in the form of the Industrial Internet, Cyber-physical Production Systems, and Digital Twins. This talk intends to address manufacturing control and manufacturing intelligence in a distributed and decentralised manner for smart manufacturing where distributed and autonomously acting components, machines, service robots, and other systems work collectively to give adaptability, flexibility, and even self-healing and self-learning characteristics. The concept and related enabling technologies also contribute to a factory-factory co-manufacturing paradigm, i.e. cloud manufacturing. Distributed control of manufacturing equipment at the field level is a challenge; so is distributed decision-making and intelligence for a manufacturing system. When machine control with real-time requirements is distributed among the network-connected nodes, what machining error does the control architecture induce, and how to quantify the error? When a disturbance occurs in a manufacturing system where multiple facilities are present, how does the system adapt to the disturbance for continued production? These are some of the questions that this talk intends to shed light on some possible solutions.