Trace recurring defects.
Test the likely causes.
Connect production, inspection, test and repair evidence to narrow an investigation. QualityLine helps electronics manufacturers find patterns worth testing and validate corrective actions with engineering evidence.
For electronics manufacturing and EMS quality teams.
Make the next engineering question clearer
A recurring failure can involve several process steps. Bring the relevant evidence together before choosing a corrective action.
- 01
Define the failure
Choose the defect, product population and time period. Set a comparable baseline and check that the measurement is reliable.
- 02
Connect the context
Relate available production, inspection, test and repair records using identifiers and relevant process information.
- 03
Compare candidate drivers
Look for meaningful differences across measurements, stations, products and periods. Check for missing data and alternative explanations.
- 04
Validate & follow up
Use engineering evidence or a controlled trial to confirm the cause. Review corrective-action effectiveness over an agreed period.
Correlation supports investigation. It does not establish causation. A candidate driver becomes a confirmed cause only when the engineering evidence supports it.
A functional test failure keeps returning
The failure rate has increased on one product. Start by separating a product or process issue from a measurement or station issue.
Illustrative workflow, not a customer case study or a promise of a particular result.
Explore test-station analytics →Locate the pattern
Compare failure codes and measured values by product revision, station and production period. Distinguish first tests from retests.
Follow the available history
Review related inspection, process and repair records. Confirm that identifiers and timestamps support the proposed connection.
Challenge the hypothesis
Check fixture or test-limit changes, product mix and measurement consistency before attributing the pattern to an upstream process.
Confirm and monitor
Validate the candidate cause, agree an action and review comparable units afterward. Track both recurrence and the chosen quality measure.
Begin with a question the evidence can answer
Choose a defined investigation and involve the engineering and IT owners who understand the records.
- Bring measurement detailValues, units, limits and failure codes provide more context than a final pass/fail result alone.
- Confirm the connectionsReview identifiers, timestamps, station and product context, retests and repair history.
- Set the validation planAgree the evidence needed to test a hypothesis, the action owner and how effectiveness will be reviewed.
STANLEY Healthcare
63% → 94%Reported first-pass yield improvement of 31 percentage points in its QualityLine implementation.
This is a documented customer outcome, not a benchmark for every investigation. Results depend on the environment, available data and actions taken.
Read the customer story (PDF) →Go deeper where your investigation needs it
Investigate the SMT process
Follow assembly data through printing, placement, reflow, inspection and downstream testing.
SMT analytics →Look beyond pass/fail
Understand why measured values and process context matter to a root cause investigation.
Read the test-data guide →Review the method
Explore the root cause analysis guide and connect the method with your quality process.
Read the root cause guide →What to know before you start
What is manufacturing root cause analysis software?
Manufacturing root cause analysis software helps teams organize production evidence, compare failure patterns and investigate potential drivers. QualityLine connects available process, inspection, test and repair records so engineers can prioritize and validate hypotheses.
Does a correlation prove the root cause?
No. A correlation shows a relationship in the available data. Engineers must check data quality, alternative explanations and process evidence, and may need a controlled trial before confirming a cause.
What data do we need for an initial investigation?
Start with a defined failure, affected population, comparison period and available records. Useful inputs include measurement values, limits, failure codes, product and station details, identifiers, retest history and repair outcomes. The required scope depends on the question.
Can we investigate with pass/fail results alone?
Pass/fail results help locate patterns but provide limited detail about how measurements changed. Parameter-level results and related process or repair records can support a more specific investigation. Confirm what evidence is available before defining the expected output.
Does QualityLine replace 8D, CAPA or engineering judgment?
QualityLine supports the evidence-gathering and analysis within an investigation. Your team still owns cause validation, corrective-action decisions and effectiveness review within its existing quality process.
How should we evaluate the workflow?
Choose a recurring issue with accessible records and an engineering owner. Agree the baseline, matching assumptions, evidence needed to validate a candidate cause and the measure of success. Timing depends on data readiness and the investigation scope.
Bring one quality question.
See where to start.
Walk through the relevant QualityLine workflow and discuss the data, scope and success measures for an evaluation.
Useful context for the discussion
- The product, line or recurring defect you want to investigate.
- The systems holding inspection, test and process records.
- The outcome your engineering team wants to improve.
A connection or review of your own production data is a separately agreed next step.
Explore the QualityLine platform →
