Wear metal origin mapping
Wear-metal origin mapping links elemental spectroscopy results to likely machine components such as gears, bearings, thrust washers, bushings, liners, piston rings, rotors, shafts, and hydraulic pump components.
Select the machine application, enter the oil analysis data, and generate a practical origin map that links wear metals to likely component sources, contamination pathways, and failure mechanisms.
This tool uses application-specific wear-metal relationships for bearings, blowers, centrifuges, compressors, cone crushers, diesel engines, hydraulic systems, industrial gearboxes, paper machines, transmissions and differentials, turbines, and vacuum pumps.
Choose an application to view the relevant diagnostic logic.
The tool compares metal combinations such as Fe + Cr, Fe + Mo, Cu + Sn, Pb + Sn, Si + Fe, Water + Fe, and other application-specific patterns. It prioritises patterns and trends rather than a single absolute ppm value.
Enter current ppm values and optional baseline / previous sample values. Where no baseline is available, use the lab flag column if the report has marked an item as caution or critical.
| Element | Current ppm | Baseline / previous ppm | Lab flag | Typical interpretation in selected application |
|---|
Wear metals are interpreted in context. For example, copper alone may indicate cooler-core leaching in turbines, while copper with lead and tin is more consistent with Babbitt/journal bearing distress.
| Metal | Status | Likely source | Diagnostic clue |
|---|
Important: this is a screening tool. It does not replace a laboratory report, ferrography, inspection findings, OEM limits, or professional reliability engineering judgement.
Wear-metal origin mapping links elemental spectroscopy results to likely machine components such as gears, bearings, thrust washers, bushings, liners, piston rings, rotors, shafts, and hydraulic pump components.
Many industrial lubrication failures begin with contamination. Silicon, water, sodium, potassium, calcium, and process debris can point to dirt ingress, moisture ingress, coolant leakage, process carryover, or poor oil handling.
Oil analysis interpretation is strongest when current results are compared against previous samples, oil hours, machine hours, operating conditions, vibration data, particle counts, and inspection findings.
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