Previous research has investigated how automated annotation and technical language processing of maintenance work orders can support maintenance decisions for different types of equipment, e.g., Sexton et al. (2018) and Brundage et al. (2021). The objective of this paper is to investigate how technical language processing can be utilized for efficient and automated classification of failure events for safety critical equipment on petroleum facilities (e.g., gas detectors and shutdown valves). For such equipment, maintenance decisions are heavily influenced by the consequence of a failure, e.g., if the failure is classified as critical or degraded, or dangerous or safe.
To explore the possibilities for automated classification of failure events, the paper will first present the fundamental concept hierarchy needed during annotation of safety critical equipment on petroleum facilities. This hierarchy is based on previous work where taxonomies from the ISO 14224:2016 standard (ISO 14224, (2016)) have been operationalised and detailed for safety critical equipment. The concept hierarchy is tested by a group of experts on a set of notifications to ensure that it is fit for purpose. The results from the test group are then used to refine the concept hierarchy before a larger group of persons, having different roles in the petroleum industry, is engaged in the entity typing of notifications. This entity typing will then provide the basis for mapping informal technical language to a computable format. By combining this knowledge with available structured information, such as failure mode and detection method, it is expected that an automated, standardised, and more efficient classification of failure events will be possible. Our database of several thousand manually classified notifications collected during the last decade, will finally enable us to evaluate the performance of the automated classification.
How to Cite
Technical language processing, Entity typing, Safety critical equipment
Brundage, M., Sexton, T., Hodkiewicz, M., Dima, A., Lukens, S. (2021). Technical Language Processing: Unlocking Maintenance Knowledge, Manufacturing Letters, Volume 27, January 2021, Pages 42-46.
NS-EN ISO 14224:2016. Petroleum, petrochemical and natural gas industries - Collection and exchange of reliability and maintenance data for equipment (ISO 14224:2016, Corrected version 2016-10-01)
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