Intelligent method framework for 3D surface manufacturing in cloud-edge collaboration architecture

IF 2.5 Q2 ENGINEERING, INDUSTRIAL
Hongming Cai, Yanjun Dong, Min Zhu, Pan Hu, Haoyuan Hu, Lihong Jiang
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引用次数: 0

Abstract

Large and complex workpieces are core components in fields, such as aerospace, shipbuilding, and other industrial applications. However, the main challenge of curved plate processing comes from the difficulty in determining the nonlinear rebound features with structural design parameters. An intelligent method framework is proposed for 3D surface manufacturing in cloud-edge collaboration environment. With the construction of an intelligent generation method for machining parameters, a unified data model is effectively integrated with various discrete data, and an intelligent processing mechanism based on 3D point clouds is constructed. In particular, a prediction method for curved panel rebound is constructed to reduce the manual dependency of the manufacturing process. Finally, a related case study is conducted to verify the framework, and the result shows accuracy, interpretability and reusability advantages over other similar methods.

Abstract Image

云边协作架构中的三维表面制造智能方法框架
大型复杂工件是航空航天、造船和其他工业应用领域的核心部件。然而,曲面板加工的主要挑战来自于难以确定非线性回弹特征与结构设计参数。本文提出了云边协作环境下三维曲面制造的智能方法框架。通过构建加工参数智能生成方法,有效整合了各种离散数据的统一数据模型,并构建了基于三维点云的智能加工机制。特别是构建了曲面板回弹预测方法,减少了制造过程中的人工依赖。最后,还进行了相关案例研究来验证该框架,结果表明与其他类似方法相比,该框架具有准确性、可解释性和可重用性等优势。
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来源期刊
IET Collaborative Intelligent Manufacturing
IET Collaborative Intelligent Manufacturing Engineering-Industrial and Manufacturing Engineering
CiteScore
9.10
自引率
2.40%
发文量
25
审稿时长
20 weeks
期刊介绍: IET Collaborative Intelligent Manufacturing is a Gold Open Access journal that focuses on the development of efficient and adaptive production and distribution systems. It aims to meet the ever-changing market demands by publishing original research on methodologies and techniques for the application of intelligence, data science, and emerging information and communication technologies in various aspects of manufacturing, such as design, modeling, simulation, planning, and optimization of products, processes, production, and assembly. The journal is indexed in COMPENDEX (Elsevier), Directory of Open Access Journals (DOAJ), Emerging Sources Citation Index (Clarivate Analytics), INSPEC (IET), SCOPUS (Elsevier) and Web of Science (Clarivate Analytics).
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