使用语义Web技术促进制造领域特定数据模型的设计

Václav Jirkovský, O. Šebek, Petr Kadera, Pavel Burget, Sönke Knoch, Tilman Becker
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引用次数: 3

摘要

现代制造业面临着集成来自不同来源/领域的数据模型的挑战,当特定领域的数据模型由不同的用户设计并以不同的格式存储时,这些数据模型可能在语义和技术上有所不同。本文介绍了一种利用语义web技术促进特定领域数据模型设计的方法。在这种方法中,管理生产所需的所有信息(包括产品的描述、生产中涉及的过程、现有资源及其规范)都在本体中捕获。提出的产品、过程和资源(PPR)本体定义了生产的基本概念,可以很容易地应用于任意领域。以简单的卡车机器人装配为例,说明了PPR本体的应用。以本体的形式捕获知识提供了使用支持工具的优势,例如用于一致性检查的推理器或用于信息提取的查询语言。本文演示了利用SQWRL在特定元素属性之间的语义匹配的基础上搜索适合操作给定卡车零件的资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Facilitation of Domain-Specific Data Models Design using Semantic Web Technologies for Manufacturing
Modern manufacturing faces a challenge of integrating data models from various sources/domains which may differ both semantically and technically when particular domain specific data models are designed by different users and stored in different formats. This paper introduces an approach for facilitating the design of domain-specific data models using semantic web technologies. In this approach, all the information required for managing the production (including a description of a product, processes involved in the production, and existing resources and their specifications) is captured in an ontology. The proposed Product, Process, and Resource (PPR) ontology defines fundamental conceptualization of the production that can be easily applied to the arbitrary domain. Application of the PPR ontology is demonstrated in the case of simple truck assembling by means of robots. Capturing the knowledge in the form of ontology provides the advantage of employing supporting tools such as reasoners for consistency checking or query languages for information extraction. The paper demonstrates the utilization of SQWRL for searching resources suitable to manipulate given truck parts on the basis of semantic matching between properties of particular elements.
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