Unplanned asset downtime is one of the costliest factors affecting energy businesses around the world today. Inspecting such large and complex sites or assets is extremely time-consuming, expensive and risky, especially when completed manually. Even the deployment of robots alone is not an optimised solution, given the lack of systematic frameworks and processes to manage and store the data and information ingested and acquired about the asset throughout its lifecycle.
This talk is about how robotics and AI can deliver a cost-efficient and reliable solution to asset integrity management, by combining with AIM-specific digital twin technology, for supporting planning and decision-making over the life of the asset. We will also explore the challenges of conventional practices such as asset tagging and inspections, and look at how they can readily be overcome with such high-tech solutions.
Key question – How to design and create a digital twin that is fit for purpose?
- The digital twin is an enabler, not an objective
- Streamlining AIM workflows
- Creating, updating and analysing digital twins
- Mirror to the best extent possible the physical reality of the site or asset
Head of Engineering