What problem does this solve?
Maintenance talks often start with a vague sense that heat, vibration, hours, and load all matter. A transparent score shows how those inputs can be combined.
Experience Lab
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Experience Lab
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Interactive Demo · Simulated Data
An illustrative maintenance score from four sliders. It is a weighted formula, not a model trained or validated on industrial machines.
Maintenance talks often start with a vague sense that heat, vibration, hours, and load all matter. A transparent score shows how those inputs can be combined.
Each slider is scaled between a low and a high example value, then weighted. Temperature counts 35%, vibration 30%, operating hours 20%, and load 15%. The drawing of a network is decoration.
Move any slider and the risk, the alert level, the factor list, and the trend chart change together.
A real predictor needs your machine history, a defined failure, and a test you trust. SATHURIX can scope that work separately from this illustration.
Illustrative score. Not a validated industrial model.
Maintenance risk
36
0 to 100, weighted sum
Alert level
Low
Low
Temperature is 35% of its example span, vibration 30%, operating hours 20%, and load 15%. The bars are those contributions. Illustrative score. Not a validated industrial model.
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Other sliders stay where you set them. This curve is the same formula, not a forecast from machine history.
The conversation can start with which signals you already record, and which decision the score would support.