Interoperable information modelling leveraging asset administration shell and large language model for quality control toward zero defect manufacturing

IF 12.2 1区 工程技术 Q1 ENGINEERING, INDUSTRIAL
Dachuan Shi , Philipp Liedl , Thomas Bauernhansl
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引用次数: 0

Abstract

In the era of Industry 4.0, Zero Defect Manufacturing (ZDM) has emerged as a prominent strategy for quality improvement, emphasizing data-driven approaches for defect prediction, prevention, and mitigation. The success of ZDM heavily depends on the availability and quality of data typically collected from diverse and heterogeneous sources during production and quality control, presenting challenges in data interoperability. Addressing this, we introduce a novel approach leveraging Asset Administration Shell (AAS) and Large Language Models (LLMs) for creating interoperable information models that incorporate semantic contextual information to enhance the interoperability of data integration in the quality control process. AAS, initiated by German industry stakeholders, shows a significant advancement in information modeling, blending ontology and digital twin concepts for the virtual representation of assets. In this work, we develop a systematic, use-case-driven methodology for AAS-based information modeling. This methodology guides the design and implementation of AAS models, ensuring model properties are presented in a unified structure and reference external standardized vocabularies to maintain consistency across different systems. To automate this referencing process, we propose a novel LLM-based algorithm to semantically search model properties within a standardized vocabulary repository. This algorithm significantly reduces manual intervention in model development. A case study in the injection molding domain demonstrates the practical application of our approach, showcasing the integration and linking of product quality and machine process data with the help of the developed AAS models. Statistical evaluation of our LLM-based semantic search algorithm confirms its efficacy in enhancing data interoperability. This methodology offers a scalable and adaptable solution for various industrial use cases, promoting widespread data interoperability in the context of Industry 4.0.
利用资产管理外壳和大型语言模型建立可互操作的信息模型,进行质量控制,实现零缺陷制造
在工业 4.0 时代,"零缺陷制造"(Zero Defect Manufacturing,ZDM)已成为质量改进的一项重要战略,它强调以数据为驱动的缺陷预测、预防和缓解方法。ZDM 的成功在很大程度上取决于数据的可用性和质量,这些数据通常是在生产和质量控制过程中从不同的异构来源收集的,这给数据互操作性带来了挑战。为此,我们引入了一种新方法,利用资产管理外壳(AAS)和大型语言模型(LLM)创建可互操作的信息模型,其中包含语义上下文信息,以增强质量控制过程中数据集成的互操作性。由德国行业利益相关者发起的 AAS 在信息建模方面取得了重大进展,它将本体和数字孪生概念融合在一起,实现了资产的虚拟表示。在这项工作中,我们为基于 AAS 的信息建模开发了一种系统的、以用例为导向的方法。该方法可指导 AAS 模型的设计和实施,确保模型属性以统一的结构呈现,并参考外部标准化词汇表,以保持不同系统间的一致性。为了使这一引用过程自动化,我们提出了一种基于 LLM 的新算法,在标准化词汇库中对模型属性进行语义搜索。该算法大大减少了模型开发过程中的人工干预。注塑成型领域的一个案例研究展示了我们的方法的实际应用,展示了在所开发的 AAS 模型的帮助下,产品质量和机器过程数据的集成和链接。对我们基于 LLM 的语义搜索算法的统计评估证实了它在增强数据互操作性方面的功效。这种方法为各种工业用例提供了可扩展、可调整的解决方案,促进了工业 4.0 背景下数据互操作性的普及。
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来源期刊
Journal of Manufacturing Systems
Journal of Manufacturing Systems 工程技术-工程:工业
CiteScore
23.30
自引率
13.20%
发文量
216
审稿时长
25 days
期刊介绍: The Journal of Manufacturing Systems is dedicated to showcasing cutting-edge fundamental and applied research in manufacturing at the systems level. Encompassing products, equipment, people, information, control, and support functions, manufacturing systems play a pivotal role in the economical and competitive development, production, delivery, and total lifecycle of products, meeting market and societal needs. With a commitment to publishing archival scholarly literature, the journal strives to advance the state of the art in manufacturing systems and foster innovation in crafting efficient, robust, and sustainable manufacturing systems. The focus extends from equipment-level considerations to the broader scope of the extended enterprise. The Journal welcomes research addressing challenges across various scales, including nano, micro, and macro-scale manufacturing, and spanning diverse sectors such as aerospace, automotive, energy, and medical device manufacturing.
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