Drilling and Well Operations
Asset and Integrity Management
Safety and Risk
Decarbonization and Energy Transition
Training and Advisory
News & insights
Asset & integrity management insights
Drilling & well operations insights
Safety & risk insights
Health, safety, environment and quality (HSEQ)
Management and The Board
To verify the client’s current asset register, update and collect name plate data and assure drawings matched the current onsite layout by providing updated drawings where required.
Power generation company
Biomass power plant (waste-to-energy)
Following a recent purchase of the facility, the maintenance team were faced with missing, inaccurate, and incomplete data within the computerized maintenance management system (CMMS) and associated engineering drawings.
In addition to this, since the site was purchased, new equipment had been added and existing equipment had been upgraded, further triggering the need for a site verification and data collection exercise to assure the CMMS replicated the physical plant.
An accurate asset register
Having up to date and accurate drawings and asset register data will provide the means to manage and maintain equipment efficiently and effectively
Having safety critical equipment identified in the CMMS provides the means to manage and maintain them effectively to assure they perform as per their design criteria when they need to
Optimized part sourcing
Having access to accurate name plate data will enable the correct spares to be ordered in a timely manner, to avoid outage and having to pay expedited fees for last minute orders
All safety, production and environmentally critical equipment are accounted for and can be managed to reduce exposure to risk in hazardous areas
Maintenance planning efficiencies
Accurate drawings are essential for understanding equipment isolation requirements to plan maintenance effectively
ePAV™ was used to unlock time and cost efficiencies during the asset verification and data collection process by utilizing its smart auto-fill technologies, built-in rulesets, and automated data QA processes to:
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