An ontology for reasoning over engineering textual data stored in FMEA spreadsheet tables

Melinda Hodkiewicz, Johan W. Klüwer, Caitlin Woods, Thomas Smoker, Emily Low

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)


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.

Original languageEnglish
Article number103496
JournalComputers in Industry
Publication statusPublished - Oct 2021


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