AI Root Cause Analysis

AI root cause analysis for recurring manufacturing defects and yield loss.

QualityLine connects existing inspection, test, repair, MES, ERP, and sensor data so manufacturing teams can identify likely root-cause drivers across systems, not just isolated symptoms.

The issue is usually not missing data. It is disconnected data.

See how it works

Works with existing data
No new production hardware
Integration handled by QualityLine
NDA before data sharing

QualityLine · Root Cause Analysis Many symptoms. One root cause.

QualityLine connects signals across systems to surface the likely root cause.

Why Root Causes Stay Hidden

Every system shows a piece.
The cause lives between them.

Each machine, test, and sensor sees only its own step.

Symptomseasy to spot inside one system
Root causeshidden in how systems connect

It is not a data problem.
It is a connection problem.

Connected analysis The defect shows at the end. The cause starts upstream.

QualityLine connects signals across systems to surface the pattern behind the issue.

How It Works

How QualityLine supports root-cause analysis

Four steps. Works with existing data, with no new production hardware.

1

Connect existing data

QualityLine connects the inspection, test, repair, MES, ERP, and sensor data your line already produces. Integration is handled for you.

2

Correlate across systems

It compares signals across machines and tests to surface patterns that single systems cannot show on their own.

3

Surface likely drivers

It highlights the most likely root-cause drivers behind a defect or yield pattern, with the connected evidence behind them.

4

Support action and alerts

It supports evidence-backed corrective action, and can alert teams when the same pattern returns.

The goal is simple: help teams move from chasing symptoms to acting on connected root-cause evidence.

QualityLine in action

QualityLine analytics

What Teams Can Uncover

Examples of root-cause patterns QualityLine can help surface

These are example patterns, not guaranteed results. What surfaces on your line depends on your data.

QualityLine main dashboard showing connected manufacturing quality data — **Main dashboard** connected quality view across systems

QualityLine OEE analytics, finding quality issues faster with AI — **Find quality issues faster with AI** OEE analytics

Recurring solder defects on one line

A likely driver to investigate

+Paste volume drift at the printer, surfaced by connecting SPI and AOI data.

Test failures that appear on one shift

A likely driver to investigate

+Reflow temperature drift, surfaced by connecting reflow and test data.

Yield slowly trending down

A likely driver to investigate

+Placement drift on fine-pitch parts, surfaced across placement and inspection data.

Intermittent failures, no clear pattern

A likely driver to investigate

+Test fixture or probe wear, surfaced across repeated test records.

See what QualityLine can surface in your own factory data.

Works with existing data. No new production hardware. NDA before data sharing.

Built On Your Existing Data

Works with the data your factory already produces

No new machines. No new sensors. QualityLine connects what is already running and turns it into connected evidence.

Pick & PlaceAOIICT SPIFlying ProbeX-Ray ReflowFCTRepair MESERPSensors

+No new production hardware
+No disruption to the line
+Integration handled by QualityLine
+NDA before data sharing

See how data integration works →

The Difference

From isolated reports to connected root-cause evidence

Same factory data. A more connected way to investigate it.

With separate tools

One view at a time

−Teams compare reports manually
−Each system shows only its own view
−Symptoms are easier to see than causes
−CAPA evidence can be fragmented

With QualityLine

One connected picture

+Connects data across systems
+Correlates signals automatically
+Surfaces likely root-cause drivers
+Supports evidence-backed investigation and corrective action

Proven In Production

Trusted on production lines worldwide

QualityLine is used by manufacturers to connect data and support root-cause investigations at scale.

90%

of out-of-spec issues traced to root cause

1,000+

production lines deployed worldwide

30%

average yield improvement

+22%

first-pass yield at Emerson

Explore More

Related QualityLine analytics

Root-cause analysis is one part of the platform. These connect to the same factory data.

FAQ

Questions we hear most

Straight answers, no marketing talk.

AI root cause analysis in manufacturing connects data from across the line (inspection, test, repair, MES, ERP, and sensors) and uses analytics to surface the most likely root-cause drivers behind a defect or yield pattern. A single system shows symptoms within its own step. Connecting the data is what helps teams move toward root-cause evidence.

QualityLine connects existing data from Pick and Place, SPI, AOI, X-Ray, Reflow, ICT, Flying Probe, FCT, Repair, MES, ERP, and sensors into one connected view, so patterns that span several systems become easier to investigate.

No. QualityLine works with the data your machines and test systems already produce. There is no new production hardware and no disruption to the line. Integration is handled by QualityLine, with an NDA in place before any data sharing.

SPC monitors variation within a single parameter or system and signals when something drifts out of spec. Root cause analysis looks across systems to help explain why that drift happened. QualityLine connects signals from many systems to help surface the likely root-cause drivers, not just the symptom.

MES, ERP, BI tools, and dashboards are very good at showing what happened inside their own scope. They are not designed to correlate signals across inspection, test, repair, and process systems. QualityLine connects those sources and helps surface likely root-cause patterns across them.

Yes. Recurring defects often persist because corrective action targets the symptom rather than the connected root-cause pattern. By connecting data across systems, QualityLine helps teams investigate why an issue keeps returning and supports more durable corrective action.

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