Integrating condition-based monitoring with process sensors information for operation and maintenance in a functional modeling framework

Jing Wu*, Xinxin Zhang

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Safe operations and adequate maintenance are two main means to achieve reliable production and reduce downtime of a plant. While the tasks of operations and maintenance are carried out by two different groups of staff, as a result, the close relationship between the two tasks is split. In this paper, this challenge is handled by a proposed integrated functional modeling framework. In this framework, the Multilevel Flow Modeling (MFM) method with its cause-consequence reasoning rules is used. Condition-based monitoring is a well-accepted strategy for predictive maintenance and fault detection based on measurements is a well-developed technology for operation support. Information fusion including monitoring conditions of assets and process sensors information for both operation and maintenance in the same modeling framework is desired. The qualitative relationship distribution between operations and maintenance can be established based on the function states of the system. In addition, these relationships are visible for both groups of staff. As a result, the detected information in the early stage of the development of the unpleasant scenarios is used to improve their situation awareness, so that the undesired emergency shutdown from both perspectives of operation and maintenance is prevented. Consequently, it can reduce production loss. A case study of operations and maintenance of a seawater injection system is carried out and shows the industrial applicability of the proposed framework. The case study strongly reveals that there is a highly close relation between operation and maintenance for ensuring the system working properly. It demonstrates that the proposed integrated framework is not only able to support operational tasks but also for the maintenance tasks by including relevant maintenance information of the system. The results show that it can potentially help with decreasing downtime of the system.

Original languageEnglish
JournalProceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
Volume238
Issue number3
Number of pages21
ISSN1748-006X
DOIs
Publication statusPublished - 2024
Event31st European Safety and Reliability Conference - Angers, France
Duration: 19 Sept 202123 Sept 2021
Conference number: 31

Conference

Conference31st European Safety and Reliability Conference
Number31
Country/TerritoryFrance
CityAngers
Period19/09/202123/09/2021

Keywords

  • decision-making
  • Functional modeling
  • Maintenance
  • Operation
  • Process systems engineering
  • Safety

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