Making efficiency measurable through integrated quality and prevention planning
A large number of assets and components must be maintained preventively—within a limited budget. Previously, prioritization was carried out without knowledge of the specific probability of failure for each asset and without a systematic comparison of the impact of measures. We have developed a model for quality-optimized budget allocation that integrates load indicators, failure histories, and system relevance, derives failure forecasts and impact analyses for each measure, and generates a neutral proposal for measures with maximum prevention efficiency.
Challenge
Initial Situation: A very large number of assets and components that are to be maintained preventively in order to minimize future disruptions.
Problem: Limited budgets necessitate prioritization of relevant assets and measures.
Requirement: Optimal allocation of limited budgets to assets and measures with the highest prevention efficiency.
Approach
1
Definition of objectives, criteria, schedule, and budgets for prevention planning
2
Development and coordination of preventive measures, including costs
3
Determination of the operational importance of assets based on load, past disruptions, and system relevance
4
Conducting failure forecasts
5
Conducting impact analyses (measures per failure forecast)
6
Derivation of a proposed measure with maximum prevention efficiency
Result
Neutral proposals for measures and recommendations for action for planners and top management
Ensuring optimized prevention planning—adaptable to different budget sizes
Shared knowledge of specific failure probabilities in the near future for each asset and component
Coordinated asset priorities for over 20,000 assets
"Finally, we know the impact of the measures in advance and can use the funds in a targeted manner."
Areas of Application
The approach is aimed at infrastructure operators with large, decentralized asset portfolios who have previously planned their prevention measures based on experience or rigid cycles.
It is relevant whenever limited budgets require impact-maximizing prioritization and a model-based procedure is sought that can be used across trades and regions and integrated into existing planning processes.