Dynamic Testing & Predictive Maintenance by Sensor-Works

Dynamic Testing:

1. Definitions and Standards:

   • Differentiation between components, assets, and machines is critical when communicating with customers.
   • Dynamic testing involves operating the asset under power, ideally under load, and assessing parameters such as vibration, thermal behaviour, and acoustics.

2. Vibration Analysis:

   • Accelerometers are the primary tools, capturing acceleration data, which is integrated to velocity for standardised assessments (e.g., ISO 10816).
   • Testing Practices:
     • Ensure motors are derated by 20–30% during workshop tests to account for additional vibrations when coupled on-site.
     • Bearings must be tested under load to prevent skidding and damage.
     • Thermal growth and grease settling require testing at operational temperature.
   • Proper placement of sensors is vital (e.g., near load zones and bearings). Avoid areas with resonance, such as panel junctions or housings.

3. Infrastructure Considerations:

   • Use isolation bases to eliminate external vibration contamination and ensure accurate readings.
   • Monitoring setups can vary, e.g., above-ground bases for ease of maintenance versus below-ground bases for stability.

Predictive Maintenance (PdM):

1. Evolution of Maintenance Strategies:

   • Maintenance has evolved from reactive to preventative, predictive, and proactive approaches.
   • Predictive maintenance integrates condition-based monitoring with root cause failure analysis to prevent future issues.

2. Customer Perspective:

   • Maintenance should be framed as a value driver, reducing downtime, waste, and hidden costs.
   • Total Cost of Ownership (TCO) and Operational Equipment Efficiency (OEE) are key metrics for demonstrating PdM's financial impact (e.g., a 1% improvement in OEE results in a 2% profit increase).

3. Technology Applications:

   • Tools like vibration analysis, thermal imaging, and ultrasonic testing can identify failure modes early.
   • Trend monitoring and spectral analysis provide deeper insights into machine health.

Criticality Matrix and Implementation:

1. Prioritisation of Assets:

   • Begin with a criticality matrix to assess the importance and failure consequences of each machine.
   • Address high-criticality assets first, gradually expanding to a mix of strategies (e.g., run-to-failure for non-critical standby assets).

2. Condition Monitoring Systems:

   • For larger fleets (20+ machines), invest in comprehensive CMMS platforms to manage data and reporting efficiently.

Failure Analysis and Lubrication:

1. Failure Drivers:

   • Improper lubrication is a leading cause of failures (e.g., mixing incompatible oils).
   • SKF studies highlight that 51% of failures are wear-related, while 40% are avoidable through better practices.

2. Bearing Health:

   • Early failures manifest in high-frequency acceleration, progressing to advanced damage detectable in velocity and temperature trends.
   • Regular lubrication checks and addressing misalignments enhance longevity and energy efficiency.

Sustainability and Circular Economy:

• Proper maintenance practices reduce unplanned breakdowns, prolong service life, and lower energy consumption, supporting sustainability goals.

Presenter

Jim Fowlie

Director, Sensor Works

Jim Fowlie is a seasoned expert in reliability engineering with over four decades of experience in heavy industry. After earning his degree in electronics in 1981, Jim dedicated his career to advancing maintenance strategies and dynamic testing practices. For 15 years, he led SKF's Certified Partner Program, auditing workshops globally and implementing rigorous protocols and standards.

Director of Sensor Works, Jim specialises in wireless data acquisition and predictive maintenance technologies. A passionate advocate for sustainable practices and proactive maintenance strategies, Jim draws on his extensive knowledge of vibration analysis, lubrication, and machine health to deliver practical insights. His expertise helps businesses optimise asset performance, reduce downtime, and support the circular economy.