Client Type:
Nuclear Power Generation Facility
Location:
Confidential
Industry:
Energy – Nuclear Power
Challenge:
The plant relied on traditional maintenance schedules that often led to reactive repairs, unexpected equipment failures, and costly unplanned outages. Operations lacked real-time insights and predictive foresight, putting both safety and efficiency at risk. Leadership identified the need for a smarter, data-driven strategy that could reduce downtime, improve performance, and enhance overall risk management.
Our Approach:
Introduced digital twin technology to create a real-time virtual replica of the plant
Conducted simulations and data infrastructure reviews to identify weak points
Embedded AI tools for predictive maintenance, energy optimisation, and staff resource planning
Aligned digital twin systems with legacy operations, overcoming stakeholder resistance
Upgraded data collection systems by installing modern sensors and enhancing monitoring points
Enabled real-time visibility into plant operations through connected systems
Provided operational foresight by simulating failure scenarios and disruption paths
Results:
Strengthened operational safety and performance visibility
Detected critical risks in planning stage, avoiding costly delays
Enabled predictive maintenance, reducing downtime and disruptions
Improved decision-making and resource allocation across teams
Shifted risk management approach from reactive to proactive
Created a scalable model for long-term digital transformation in high-risk environments
Client Feedback:
“The digital twin became more than just a tool for efficiency – it evolved into a critical asset for maintaining operational safety and protecting both the plant’s infrastructure and its personnel.”
“By running simulations and reviewing the plant’s data infrastructure, we identified potential weak points early.”
– Yasir Masood, Programme and Risk Consultant, GleeYM