A novel framework for online decision-making and feedback optimization of complex products process parameter based on edge-cloud collaboration

Digital Twin Pub Date : 2022-09-22 DOI:10.12688/digitaltwin.17682.1

chong han, Guanghui Zhou, Chao Zhang, yongrui yu, D. ma

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引用次数: 1

Abstract

Background: Intelligent manufacturing is perceived as a manufacturing mode with powerful learning and cognitive capabilities empowered by information technologies such as the internet of things, edge computing, and cloud computing. The mode can be used to address the problems of low intelligence and poor timeliness of traditional process planning. Methods: The framework includes the multi-objective process planning method based on real-time data, and the process closed-loop optimization mechanism of “cloud-based theoretical process planning plus edge MEC (multi-access edge computing) side online simulation verification and real-time feedback adjustment”, which realizes online process planning and iterative optimization in mass customization. Results: The feasibility of the online analysis method for thin-walled part milling deformation is verified by taking the finishing process of aerospace thin-walled parts as an example. The experimental results show that the simulation time on the single analysis step is reduced from 6s to 1s, and the accuracy rate is 86.9%. Conclusions: A new intelligent process planning theoretical framework integrating with online process planning and autonomous collaborative control, namely, digital twin and multi-access edge computing process planning (DT-MEC-PP) is proposed in this paper.

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基于边缘云协同的复杂产品工艺参数在线决策与反馈优化新框架

背景:智能制造被认为是在物联网、边缘计算、云计算等信息技术的支持下，具有强大学习和认知能力的制造模式。该模型可以解决传统工艺规划智能程度低、时效性差的问题。方法:该框架包括基于实时数据的多目标工艺规划方法，以及“基于云的理论工艺规划+边缘MEC(多访问边缘计算)侧在线仿真验证和实时反馈调整”的工艺闭环优化机制，实现大规模定制中的在线工艺规划和迭代优化。结果:以航空航天薄壁件精加工过程为例，验证了薄壁件铣削变形在线分析方法的可行性。实验结果表明，单步分析的仿真时间由原来的6秒缩短到15秒，准确率达到86.9%。结论:本文提出了一种集成在线工艺规划和自主协同控制的新型智能工艺规划理论框架，即数字孪生和多访问边缘计算工艺规划(DT-MEC-PP)。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Digital Twin digital twin technologies-

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期刊介绍： Digital Twin is a rapid multidisciplinary open access publishing platform for state-of-the-art, basic, scientific and applied research on digital twin technologies. Digital Twin covers all areas related digital twin technologies, including broad fields such as smart manufacturing, civil and industrial engineering, healthcare, agriculture, and many others. The platform is open to submissions from researchers, practitioners and experts, and all articles will benefit from open peer review.  The aim of Digital Twin is to advance the state-of-the-art in digital twin research and encourage innovation by highlighting efficient, robust and sustainable multidisciplinary applications across a variety of fields. Challenges can be addressed using theoretical, methodological, and technological approaches. The scope of Digital Twin includes, but is not limited to, the following areas:  ● Digital twin concepts, architecture, and frameworks ● Digital twin theory and method ● Digital twin key technologies and tools ● Digital twin applications and case studies ● Digital twin implementation ● Digital twin services ● Digital twin security ● Digital twin standards Digital twin also focuses on applications within and across broad sectors including: ● Smart manufacturing ● Aviation and aerospace ● Smart cities and construction ● Healthcare and medicine ● Robotics ● Shipping, vehicles and railways ● Industrial engineering and engineering management ● Agriculture ● Mining ● Power, energy and environment Digital Twin features a range of article types including research articles, case studies, method articles, study protocols, software tools, systematic reviews, data notes, brief reports, and opinion articles.