The Challenge
Our client manages oil and gas operations around the world. They have standardized on Maximo 7 as their Enterprise Asset Management (EAM) platform. Like many asset-intensive organizations, our client implemented an EAM tool to gain visibility and control over capital equipment to optimize maintenance strategies, reduce operating costs, and better manage their workforce and spare parts inventories. Achieving the benefits of an EAM tool relies on a complete and detailed Master Equipment List (MEL), populated with all critical pieces of information – type of equipment, manufacturer, model, serial number, vendor, criticality, spare parts listings. For their operations in the Gulf of Mexico, the MEL data was not complete. Incomplete equipment data was preventing them from realizing the benefits of EAM.
The Solution
The offshore platforms containing the equipment for which we needed data were constructed 5-10 years ago. Because they were offshore platforms, a manual inspection of the equipment was not feasible from a resource, cost, and timeline perspective. We had to find the data by working with other sources of information.
We reviewed and constructed equipment data from over 15,000 documents that included vendor books, data sheets, and purchase orders. We audited 100s of equipment list files contained in the document control system. We retrieved 1,000s of rows of structured data from various engineering systems to locate sources of equipment data. We analyzed over 5,000 change records to ensure all equipment changes since the creation of the original engineering documentation were captured. We normalized, structured, and quality checked the data. We partnered with teams in reliability and maintenance and engineering to verify the data.
The Result
We were able to find and load to Maximo meaningful data on 75+% of the offshore equipment. For organizations like our client’s, with many high value physical assets and operations that need to run 24×7, each failure is disruptive and costly. With an EAM solution powered by reliable equipment data, they are now positioned to reduce asset-related operating costs and reduce downtime by consistently enforcing preventive maintenance strategies. Further, the equipment data is ready to move into the spare parts phase of the project, enabling optimization of the spare parts inventory.