| 金寿松,刘星琪,吴容吉,邢瑞花,王亚良.基于数字孪生的产品生产质量管理方法研究[J].高技术通讯(中文),2022,32(1):101~110 |
| 基于数字孪生的产品生产质量管理方法研究 |
| Product quality management model based on digital twins |
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| DOI：10.3772/j.issn.1002-0470.2022.01.012 |
| 中文关键词: 数据分析； 预测诊断； 数字孪生； 案例推理； 质量管理 |
| 英文关键词: data analysis, predictive diagnostic, digital twins, case-based reasoning, quality management |
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| 摘要点击次数: 1939 |
| 全文下载次数: 1072 |
| 中文摘要: |
| 针对现阶段质量管理过程缺少反馈机制、管理存在滞后性等问题，在传统质量管理模式基础上，提出一种基于数字孪生的产品质量管理方法。构建了物理生产车间、虚拟生产车间、车间质量孪生数据和车间质量管理系统相协同的产品质量数字孪生模型，并对数字孪生模型的运行机制进行了阐述。通过对数据采集融合的方法进行设计形成车间质量孪生数据，并利用灰色预测模型实现对未来质量数据的预测，再通过案例推理模型实现对异常数据的诊断。以齿轮生产过程质量诊断为例，对齿轮加工质量进行分析。最后，搭建了质量管理系统验证了本文方法的可行性及有效性，实现了产品质量的预测诊断功能，提升了产品质量管理的智能化、实时化和可视化，并为大数据下的质量知识挖掘奠定了基础。 |
| 英文摘要: |
| Aiming at the problems such as the lack of feedback mechanism and the lag of management in the current quality management process, a production quality management method based on digital twin is further proposed on the basis of the traditional quality management model. This paper constructs a digital twin model of production quality, which is associated with physical production workshop, virtual production workshop, workshop quality twin data and workshop quality management system, and expounds the operation mechanism of the digital twin model. The method of data acquisition and fusion is used to form the workshop quality twin data, combined with the grey prediction model to predict the future quality data, and then through the case reasoning model the diagnosis of abnormal data is realized. Furthermore, taking the quality diagnosis of gear production process as an example, the gear processing quality is analyzed. Finally, a quality management system is built to verify the feasibility and effectiveness of this method. The proposed method realizes the prediction and diagnosis function of production quality, improves the intelligence, real-time and visualization of production quality management, and lays the foundation for quality knowledge mining under big data. |
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