AI and Machine Learning for industrial reliability

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Services · Process step 3

Compare similar components and phases

Evidence becomes useful when it is compared, challenged, and connected to credible failure modes, learning needs, workflow risks, or equipment decisions. Conflicting indicators should be explained rather than hidden. This page applies that step specifically to Infrared thermography.

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Compare similar components and phases for Infrared thermography
Step 03 · Compare similar components and phases

Why this step matters

Turn observations into a defensible interpretation.

Evidence becomes useful when it is compared, challenged, and connected to credible failure modes, learning needs, workflow risks, or equipment decisions. Conflicting indicators should be explained rather than hidden.

Review patterns, trends, operating influence, uncertainty, and complementary evidence before assigning significance or priority.

Applied to Infrared thermography

  • Technical focus: Bearing and coupling temperature
  • Where it applies: Rotating equipment
  • Expected evidence: Finding priority
  • Working principle: A hot spot is evidence—not a diagnosis—until loading, emissivity, reflection, and comparison are considered.

What happens in practice

  1. 01
    Prepare the context

    Confirm the asset, people, records, operating state, and boundaries needed to address bearing and coupling temperature.

  2. 02
    Make the work traceable

    Review patterns, trends, operating influence, uncertainty, and complementary evidence before assigning significance or priority.

  3. 03
    Confirm the handoff

    Check that the result can support finding priority and that unresolved uncertainty is visible.

ILLUSTRATIVE FIELD SCENARIO

A sample of how this step may unfold

A maintenance team requests focused technical support after an exception appears during an inspection, route, or operating review. During review, the first indicator is compared with history, operating state, and complementary evidence. The team tests whether “Bearing and coupling temperature” is supported, considers other explanations, and documents why finding priority is—or is not—defensible. The example closes with the principle that a hot spot is evidence—not a diagnosis—until loading, emissivity, reflection, and comparison are considered.

This is an educational example, not a description of a specific client engagement or a guaranteed result.

Evidence to expect

What should be visible before moving on.

  • A valid comparison or baseline
  • Supporting and conflicting indicators
  • A stated level of confidence
  • A traceable reason for significance and priority

Common mistake

What weakens this step.

Treating one indicator—or one output from AI and Machine Learning—as a complete diagnosis without challenging it against context and complementary evidence.

What good looks like

  • The conclusion follows visibly from the evidence
  • Uncertainty and alternative explanations are stated
  • Priority reflects condition and consequence

Where this step ends

A clear record, a clear limit, and a clear next move.

A good closeout leaves the next person with a practical explanation of what was done, what the evidence supports, what remains uncertain, and what should happen next. For this capability, the working principle remains: A hot spot is evidence—not a diagnosis—until loading, emissivity, reflection, and comparison are considered.

Start a conversation

Discuss the compare similar components and phases step with STAH.

Share the asset, operating concern, data opportunity, or reliability goal. STAH can help shape a focused, human-reviewed next step.