An Intelligent Quality Control Method for Manufacturing Processes Based on a Human–Cyber–Physical Knowledge Graph

IF 10.1 1区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY Engineering Pub Date : 2024-10-01 DOI:10.1016/j.eng.2024.03.022
Shilong Wang , Jinhan Yang , Bo Yang , Dong Li , Ling Kang
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Abstract

Quality management is a constant and significant concern in enterprises. Effective determination of correct solutions for comprehensive problems helps avoid increased backtesting costs. This study proposes an intelligent quality control method for manufacturing processes based on a human–cyber–physical (HCP) knowledge graph, which is a systematic method that encompasses the following elements: data management and classification based on HCP ternary data, HCP ontology construction, knowledge extraction for constructing an HCP knowledge graph, and comprehensive application of quality control based on HCP knowledge. The proposed method implements case retrieval, automatic analysis, and assisted decision making based on an HCP knowledge graph, enabling quality monitoring, inspection, diagnosis, and maintenance strategies for quality control. In practical applications, the proposed modular and hierarchical HCP ontology exhibits significant superiority in terms of shareability and reusability of the acquired knowledge. Moreover, the HCP knowledge graph deeply integrates the provided HCP data and effectively supports comprehensive decision making. The proposed method was implemented in cases involving an automotive production line and a gear manufacturing process, and the effectiveness of the method was verified by the application system deployed. Furthermore, the proposed method can be extended to other manufacturing process quality control tasks.
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基于人-网络-物理知识图谱的制造过程智能质量控制方法
质量管理是企业持续关注的重要问题。有效确定综合问题的正确解决方案有助于避免增加回测成本。本研究提出了一种基于人-机-物(HCP)知识图谱的制造过程智能质量控制方法,该方法是一种系统化的方法,包含以下要素:基于 HCP 三元数据的数据管理与分类、HCP 本体构建、构建 HCP 知识图谱的知识提取以及基于 HCP 知识的质量控制综合应用。所提出的方法实现了基于 HCP 知识图谱的病例检索、自动分析和辅助决策,实现了质量监控、检验、诊断和维护的质量控制策略。在实际应用中,所提出的模块化分层 HCP 本体在知识的可共享性和可重用性方面表现出明显的优势。此外,HCP 知识图谱还能深度整合所提供的 HCP 数据,有效支持综合决策。所提出的方法在涉及汽车生产线和齿轮制造过程的案例中得到了实施,所部署的应用系统也验证了该方法的有效性。此外,所提出的方法还可以扩展到其他制造过程质量控制任务中。
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来源期刊
Engineering
Engineering Environmental Science-Environmental Engineering
自引率
1.60%
发文量
335
审稿时长
35 days
期刊介绍: Engineering, an international open-access journal initiated by the Chinese Academy of Engineering (CAE) in 2015, serves as a distinguished platform for disseminating cutting-edge advancements in engineering R&D, sharing major research outputs, and highlighting key achievements worldwide. The journal's objectives encompass reporting progress in engineering science, fostering discussions on hot topics, addressing areas of interest, challenges, and prospects in engineering development, while considering human and environmental well-being and ethics in engineering. It aims to inspire breakthroughs and innovations with profound economic and social significance, propelling them to advanced international standards and transforming them into a new productive force. Ultimately, this endeavor seeks to bring about positive changes globally, benefit humanity, and shape a new future.
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