Condition indices and performance of the assets
Previous work on condition indices is mainly focused on assets and components used in electricity networks and infrastructure. However, several health index approaches have been developed over the years for industrial assets as well which are combining a number of information sources. These have aimed at quantifying the health of a complex asset to provide an integrated view of the assets’ condition. These approaches aims at supporting the more long-term decision-making, for instance optimizing the replacement strategies. In addition, there is a variety of condition monitoring techniques, which provide an important source of failure-mode specific information. This is important for shorter-term action points.
Hierarchic approach for asset condition and performance management
Asset condition and performance management and related performance metrics and indices can be managed as different layers and through a hierarchical approach. Here we propose a balanced collection of key performance indicators for asset performance management, where health and condition indices would be part of the holistic approach.
- Holistic performance of asset management: for instance a metrics combining unavailability costs, maintenance costs and investment costs
- Maintenance organization performance: leading, lagging and forecasting indicators for measuring the performance, e.g. the maintenance costs and availability performance of the production systems
- Site and production line specific performance: e.g. overall equipment efficiency (OEE)
- Equipment and asset specific performance and health: e.g. the asset or component specific health indices where the required information items are consolidated, e.g. age, expected reliability over lifetime, use profile and load factor, environment factor and understanding of the failure modes and mechanisms as well as their effects on system performance (criticality) and lifecycle costs and profits.
Altogether, there is a need for solutions that would integrate asset information to provide managers and maintenance staff with a clear view on focus areas and emerging risks. Both short-term and long-term aspects should be covered so that daily maintenance activities are supported by information on risks of critical failures and maintenance investment planning is provided with adequate insight of the status, performance and remaining lifetime of the asset.
In SEED we aim to develop a concept for condition index of the critical assets by collecting and refining the data from relevant sources and by calibrating the assessment with tacit knowledge. We believe that in this way we can take steps towards business-driven maintenance.