Client Overview
A large multi-platform fleet operator managing air and marine vehicles sought to upgrade its oil analysis capability as part of a broader move towards predictive maintenance. Previously relying on an XRF-based oil analyser, the client faced persistent issues related to limited elemental coverage, sample preparation complexity, and inconsistent accuracy, particularly for light elements and low-concentration wear metals.

Analytical Challenges

• Limited Elemental Detection: XRF systems struggled with key elements like Al, Si, Na, and additive metals at low concentrations.
• Sample Prep Complexity: Required elaborate dilution and calibration steps, limiting speed and repeatability.
• Accuracy & Sensitivity Gaps: Inability to consistently detect early-stage wear and contamination markers.
• Standard Compliance: Difficulty in aligning results with ASTM D6595, the industry-standard for oil analysis.
• Operational Demands: Need for a rugged, field-operable system usable by technicians with basic training.

Solution: Metavision-RX RDE-OES

To address these challenges, the client deployed Metavision-RX, Metal Power’s advanced Rotating Disc Electrode Optical Emission Spectrometer. Purpose-built for oil condition monitoring, the system offers fast, precise, and multi-element analysis in a robust, field-ready form factor.

Implementation & Use Cases

The Metavision-RX was rolled out across three key operational bases, supporting both marine and aviation platforms. Core applications included:

• Engine Wear Monitoring: Fe, Cu, Cr, and Al analysis for predictive insights into pistons, bearings, and liners.
• Contaminant Detection: Identification of Si, Na, and K, indicating dirt ingress or coolant leaks.
• Additive Health Tracking: Ensuring correct Zn, Ca, P, and Mg levels in lubricants to preserve functional properties.
• Hydraulic & Coolant Fluid Testing: Extending condition monitoring beyond engine systems.

Performance Highlights

Conclusion

The deployment of Metavision-RX marked a pivotal shift from reactive servicing to predictive maintenance. By eliminating the limitations of XRF technology and streamlining analysis workflows, the client achieved faster diagnostics, higher accuracy, and significantly improved maintenance planning, ultimately leading to enhanced fleet reliability and reduced lifecycle costs.