Much textual engineering knowledge is captured in tables, particularly in spreadsheets and in documents such as equipment manuals. To leverage the benefits of artificial intelligence, industry must find ways to extract the data and relationships captured in these tables. This paper demonstrates the application of an ontological approach to make the classes and relations held in spreadsheet tables explicit. Ontologies offer a pathway because they use formal descriptions to define machine-interpretable definitions of shared concepts and relations between concepts. We illustrate this with two case studies on a failure modes and effects analysis (FMEA) table. Our examples demonstrate how the relationship between rows and columns in a table can be represented in logic for FMEA entries, thereby allowing the same ontology to ingest instance data from the IEC 60812:2006 FMEA Standard and a real industrial FMEA. We give relationships in the FMEA and asset hierarchy spreadsheets an explicit representation, so that OWL-DL reasoning can infer final failure effects at the system level from component failures. The prototype ontologies described in this paper are modular and aligned to a top level ontology, and hence can be applied to other use cases. Our contribution is showing that engineers can make data captured in commonly used spreadsheet tables machine readable using a FMEA ontology.

许多文本工程知识都记录在表格中，特别是在电子表格和设备手册等文档中。为了利用人工智能的优势，行业必须找到提取这些表中捕获的数据和关系的方法。本文展示了本体论方法的应用，使电子表格表中的类和关系变得明确。本体提供了一条途径，因为它们使用形式描述来定义共享概念和概念之间关系的机器可解释定义。我们通过关于失效模式和影响分析 (FMEA) 表的两个案例研究来说明这一点。我们的示例演示了如何在 FMEA 条目的逻辑中表示表中行和列之间的关系，从而允许相同的本体从 IEC 60812:2006 FMEA 标准和真正的工业 FMEA 中提取实例数据。我们给 FMEA 和资产层次电子表格中的关系一个明确的表示，以便 OWL-DL 推理可以从组件故障推断系统级别的最终故障影响。本文中描述的原型本体是模块化的，并与顶级本体保持一致，因此可以应用于其他用例。我们的贡献表明，工程师可以使用 FMEA 本体使在常用电子表格表中捕获的数据机器可读。本文中描述的原型本体是模块化的，并与顶级本体保持一致，因此可以应用于其他用例。我们的贡献表明，工程师可以使用 FMEA 本体使在常用电子表格表中捕获的数据机器可读。本文中描述的原型本体是模块化的，并与顶级本体保持一致，因此可以应用于其他用例。我们的贡献表明，工程师可以使用 FMEA 本体使在常用电子表格表中捕获的数据机器可读。