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Smart additive manufacturing: Current artificial intelligenceenabled methods and future perspectives

Science China(Technological Sciences) 2020年第9期63卷 1600-1611页

作者： WANG YuanBin ZHENG Pai PENG Tao YANG HuaYong ZOU Jun State Key Laboratory of Fluid Power and Mechatronic systems Zhejiang UniversityHangzhou 310027China departmen of ilndustrial and systems engineering The Hong Kong Polyechnic UniversityKowloonHong Kong 999077China

Additive manufacturing(AM) has been increasingly used in production. Because of its rapid growth, the efficiency and robustness of AM-based product development processes should be improved. Artificial intelligence(AI) is a powerful tool that has outperformed humans in numerous complex tasks. AI-enabled intelligent agents can reduce the workforce required to scale up AM production and achieve higher resource utilization efficiency. This study provides an introduction of AI techniques. Then,the current development of AI-enabled AM product development is investigated. Existing intelligent agents are used for problems in product design, process design and production stages. Based on the review, current research gaps and future research directions are identified. To guide future development of more efficient and comprehensive intelligent agents, a smart AM framework based on cloud-edge computing is proposed. Global consideration can be realized in the cloud environment, and a fast response can be achieved at the edge nodes.

关键词： additive manufacturing artificial intelligence product development cloud-edge computing

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ROBUSTNESS ANALYSIS OF LEADER-FOLLOWER CONSENSUS

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Journal of systems Science & Complexity 2009年第2期22卷 186-206页

作者： Jinzhi WANG Ying TAN · Iven MAREELS State Key Laboratory for Turbulence and Complex System and department of Mechanics and Aerospace Engi-neering College of Engineering Peking University Beijing 100871 China. departmen~ of Electrical and Electronic engineering University of Melbourne Melbourne VIC. 3010 Aus-tralia.

In this paper,robustness properties of the leader-follower consensus are *** of presentation,the attention is focused on a group of continuous-time first-order dynamicagents with a time-invariant communication topology in the presence of communication *** orderto evaluate the robustness of leader-follower consensus,two robustness measures are proposed:the L_2gain of the error vector to the state of the network and the worst case L_2 gain at a *** L_2 gain of the error vector to the state of the network is widely used in robust control design andanalysis,the worst case L_2 gain at a node is less conservative with respect to the number of nodes inthe *** is thus suggested that the worst case L_2 gain at a node is used when the robustnessof consensus is *** analysis and simulation results show that these two measuresare sensitive to the communication *** general,the 'optimal' communication topology thatcan achieve most robust performance with respect to either of the proposed robustness measures isdifficult to characterize and/or *** the in-degree of each follower is one,it is shown thatboth measures reach a minimum when the leader can communicate to each node in the network.

关键词： Communication errors leader-follower consensus robustness.

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