Corrosion Mapping at Kinross-Tasiast Gold Mine
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NDTMiningCorrosion MappingGold Processing

Corrosion Mapping at Kinross-Tasiast Gold Mine

Tasiast, Mauritania August 2023 Chanza
Phased Array UltrasonicsCorrosion MappingAsset Integrity Assessment
2,400m
Piping Inspected
24
Vessels Mapped
12
Critical Findings
$2.4M
Downtime Prevented

Project Background

Kinross Gold Corporation operates the Tasiast Gold Mine in Mauritania, one of the largest gold mining operations in West Africa. The facility processes thousands of tonnes of ore daily through complex piping systems and pressure vessels. Maintaining the integrity of these critical assets is paramount to operational continuity and safety.

NDT technician performing ultrasonic inspection on industrial piping
RSL technician conducting phased array ultrasonic testing on process piping

The Challenge

The harsh operating environment at Tasiast, combined with the corrosive nature of gold processing chemicals, creates significant challenges for maintaining asset integrity. The client needed a reliable partner capable of conducting comprehensive corrosion assessments across hundreds of meters of piping and multiple pressure vessels, all while minimizing operational disruption.

“RSL's systematic approach to corrosion mapping gave us the confidence to make informed maintenance decisions. Their data quality and professional reporting exceeded our expectations.”

— Site Maintenance Manager, Kinross-Tasiast

Our Approach

RSL mobilized a team of ASNT Level II and Level III certified technicians equipped with the latest Phased Array Ultrasonic Testing equipment. We developed a grid-based inspection methodology that allowed us to create detailed thickness maps showing wall loss patterns across all inspected assets.

2,400m
Piping Inspected
24
Vessels Mapped
50,000+
Data Points
6 weeks
Project Duration

Results & Impact

Our comprehensive corrosion mapping program identified 12 critical areas requiring immediate repair intervention and 34 areas for monitoring. The detailed thickness data enabled the client to develop a risk-based maintenance strategy, prioritizing repairs based on remaining life calculations. This proactive approach prevented an estimated $2.4 million in potential unplanned downtime costs.

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