AIxInsight
Monitors inspection results, defect logs, images, trends, alerts, operator review, and traceability.
IT HELPS TEAMS UNDERSTAND:
- What happened?
- Where did it happen?
- How often is it happening?
- Is the pattern changing?
Found the Defect.
but
What’s Behind It?
Connect defect patterns with production conditions to focus quality investigations on
the factors that matter. AIxCause analyzes relationships between inspection results and
process data, helping teams understand what changed when defects appeared.
Detection Shows the Problem.
Not the Reason.
A defect record tells you what failed and when it happened. It rarely explains why.
Finding the cause may require teams to compare inspection results with:
- Machine settings and Line speed
- Temperature and humidity
- Raw-material batches and Suppliers
- Products and SKUs
- Shifts and operators
- Maintenance events
When this information sits across separate systems, investigations become slow, manual, and dependent on individual experience.
Connect the Context
AIxCause brings inspection results and relevant production data into the same analysis.
It looks for relationships between defect patterns and the conditions surrounding them, helping teams identify where to investigate next.
Instead of asking only, "Why did this defect happen?"; teams can ask more focused questions:
Did the defect increase after a machine setting changed?
Is it concentrated in one material batch?
Does it appear more often above a certain line speed?
Is the pattern linked to a specific supplier?
Did the issue begin after maintenance?
Does it occur under particular environmental conditions?
Is it limited to one product, shift, or production period?
Find What Changed
AIxCause can analyze defect results against any
relevant data the manufacturer can provide.
Process Conditions
- Machine parameters
- Line speed
- Pressure
- Temperature
- Humidity
- Other process measurements
Production Context
- Product and SKU
- Batch and production run
- Shift and operator
- Line and location
- Date and time
Material Information
- Raw-material batch
- Supplier
- Material properties
- Incoming inspection data
Equipment History
- Maintenance events
- Component changes
- Calibration records
- Operating-state changes
The available analysis depends on the quality, relevance, and consistency of the connected data.
See the Pattern.
Investigate the Cause.
AIxInsight and AIxCause support two connected stages of
quality intelligence.
AIxCause
Connects those results with production conditions and additional process data.
IT HELPS TEAMS INVESTIGATE:
- What changed?
- Which conditions are associated with the pattern?
- Where should the investigation begin?
- Did the relationship change after corrective action?
When Root-Cause Analysis Stalls
AIxCause is designed for situations where:
01
The same defect keeps returning
02
Teams cannot explain a change in defect frequency
03
Investigation data is spread across different systems
04
Too many process variables could be involved
05
The issue may be related to materials or suppliers
06
Machine settings change across production runs
07
Corrective actions are difficult to evaluate
08
Quality investigations rely heavily on manual comparison
09
Teams need evidence before changing the process
Built for Cross-Functional Decisions
Quality Leaders
Move from defect reporting to a structured investigation supported by inspection evidence.
Read More →Operations Leaders
See which production conditions are associated with changes in quality performance.
Read More →Start With the Data You Have
You do not need every possible production variable before beginning.
Start with the inspection records and available process data. AI-Innovate can assess which sources are relevant, how they can be connected, and whether the available data is sufficient for meaningful analysis.
Talk to an Expert →Tell us about the recurring defect, available inspection history, and production data.
