Prioritising maintenance work is crucial with limited resources, time, and budget. At Woodside, traditional A/B/C equipment classification proved insufficient for managing failure risk across our global fleet of over half a million assets, lacking precision to identify truly critical equipment.

Our solution was developing a dynamic, data-driven Equipment Criticality Analysis (ECA) program that:

• Evaluates equipment based on 14 key parameters, assigning a score out of 100
• Integrates with real-time data sources to automatically adjust criticality as conditions change
• Has successfully analyzed over 200,000 pieces of equipment
• Transitioned from static to dynamic analysis, ensuring ongoing relevance
• Reduced overall maintenance hours while maintaining operational safety
• Optimised resource allocation through improved prioritization
• Generated cost savings amounting to hundreds of thousands of dollars