Dynamic Criticality-Based Maintenance

Research overview

There’s an increasing need in the industry to prioritize maintenance activities  and investments based on the criticality and associated risk of assets. A review of industry and literature show that:

 

  • Current criticality analysis techniques  consider criticality as more or less a static quantity that is not updated with sufficient frequency as the operating environment changes.
  • There’s need to continuously monitor, review and update the criticality of assets to ensure maintenance objectives for the assets are aligned to business needs.

Research objectives

  • Identify factors that affect, and influences changes to, an asset’s criticality.
  • Develop a technique to monitor, identify and detect changes in criticality.
  • Develop a business process for updating asset criticality in a company.
  • Use real-time criticality for making optimum maintenance decisions.

Technical approach

Data collection: Integrated information system

  • Dynamic linkage of remote data sources using data fusion as an integration model
  • Data retrieval architecture using standardized request for text and numbers

Model Buildings: multi-stage model for

Criticality factor data; dynamic analysis of criticality; linking maintenance decision & performance to asset criticality. MCDM for factor weightings.

 

Maintenance Planning

Dynamically generate optimal maintenance plans for the system considering individual asset criticality and system service level requirements.

 

Outputs

  • A novel rational working procedure/model for criticality-based maintenance.
  • A quantitative tool for updating criticality and providing information for optimal maintenance decisions for the assets in the  company.

Benefits

  • Real-time criticality could ensure limited maintenance resources are spent on the most criticality assets.
  • Maintenance decisions can be made with current, not historical, data. Decision makers have better visibility over the system.
  • Maintenance objectives are properly aligned to business objectives.

Acknowledgement to the Petroleum Technology Development Fund.

 

Supervisor

Dr Ajith Parlikad

Share This