Abstract
Automated condition monitoring of active components of a system can improve the cost-efficiency of preventive and corrective maintenance and the availability of the production system. The validity, reliability and correct interpretation of the signals obtained from the condition monitoring instrumentation is important for the realisation of the potential benefits. The utilisation of experts in the interpretation of the condition monitoring signals is therefore crucial.
In the paper, a stopping time model is formulated, where experts' judgements on the remaining operating time of a component, given an indication of incipient failure, are utilised to arrive at optimal operational maintenance decisions. Optimality is defined in the sense of maximising expected utility. An expert model is also formulated, which utilises percentile information elicited from the experts. The modelling framework allows for the testing of different modelling assumptions which affect the decision outcomes.
In the paper, a stopping time model is formulated, where experts' judgements on the remaining operating time of a component, given an indication of incipient failure, are utilised to arrive at optimal operational maintenance decisions. Optimality is defined in the sense of maximising expected utility. An expert model is also formulated, which utilises percentile information elicited from the experts. The modelling framework allows for the testing of different modelling assumptions which affect the decision outcomes.
| Original language | English |
|---|---|
| Pages (from-to) | 319-325 |
| Journal | Reliability Engineering and System Safety |
| Volume | 76 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2002 |
| MoE publication type | A1 Journal article-refereed |
Keywords
- condition monitoring
- stopping time optimisation model
- expert judgement
- predictive maintenance