First-pass yield · Electronics & EMS
Improve first pass yield.
Find where to act.
Connect inspection, test and repair records to investigate recurring failures. QualityLine helps your engineers focus corrective action and track whether more units pass the first time.
Built for quality, test and manufacturing teams in electronics, SMT and EMS.
Understand the losses
A yield number tells you what changed.
The records help explain why.
When first-pass yield falls, the useful next question is where the losses concentrate. Bring the relevant evidence together before choosing a corrective action.
Recurring defects
Find patterns across production
Compare failure modes across products, lines, stations and periods. Check whether an issue is widespread or concentrated in a particular part of the process.
Explore SMT analytics →Retests & rework
See what a final pass can hide
Review first attempts alongside later tests and repairs. A unit that eventually passes can still consume test capacity and engineering time.
Explore test data analytics →Process relationships
Build a focused investigation
Compare affected units with relevant passing units. Use relationships in the data to form hypotheses that engineers can check against process evidence.
Explore root cause analysis →The improvement workflow
Turn a yield concern into a measurable improvement project
QualityLine supports the investigation. Your engineering team validates the cause and owns the process change.
- 01
Set a reliable baseline
Choose the product, process boundary and period. Agree how to count first attempts, retests, rework and units still in process so the comparison stays consistent.
- 02
Connect the relevant records
Bring together available inspection, test and repair data. Review identifiers and timestamps to establish which records can be matched to a unit or production period.
- 03
Narrow the likely drivers
Compare the affected population by failure mode, station, product and time. Examine process relationships and separate possible test-system issues from product defects.
- 04
Validate and monitor
Check the hypothesis with engineering evidence, record the corrective action and compare subsequent runs. Account for product mix, volumes and changes to test limits.
STANLEY Healthcare
63% → 94%
Reported first-pass yield
A 31 percentage-point improvement in the customer’s reported project.
Source: QualityLine’s STANLEY Healthcare customer testimonial. This is a specific customer outcome, not a forecast for every factory.
Customer experience
Connected evidence. A clearer path to action.
STANLEY Healthcare describes using QualityLine to investigate individual units, components and problems, and to connect production findings with engineering follow-up.
The customer story covers alerts, cross-correlation and feedback between production, engineering and design teams.
Read the STANLEY Healthcare story (PDF) →
Results depend on the production environment, data and implementation scope.
Measure the result
Track better first passes alongside the cost of recovery
Agree the measures before the project starts. Keep the same definitions and compare like-for-like products and processes.
First-pass yield
The share of units that pass the defined process on the first attempt.
Retest rate
How many units need another test, with false failures reviewed separately where evidence allows.
Rework & scrap
The recovery effort and material losses behind the final yield figure.
Investigation time
How long it takes to move from a reported issue to a validated corrective action.
Implementation & fit
Start with the records behind one yield problem
Define a focused evaluation with your quality, engineering and IT teams. Your existing manufacturing systems can continue to serve their current roles.
What data is useful?
- Inspection results from SPI, AOI or X-ray.
- ICT, functional test and other test measurements.
- Attempt sequence, failure codes and repair records.
- Unit identifiers, product, station and time context.
What do we agree first?
- The product, line and quality question to evaluate.
- Source access, record completeness and matching coverage.
- Historical data, ongoing feeds and refresh needs.
- Integration responsibilities, timeline and success measures.
The available identifiers determine how far records can be traced. Review manufacturing data integration and the QualityLine platform to see how the wider workflow fits together.
Before you evaluate
Questions about improving FPY with QualityLine
How does QualityLine help improve first-pass yield?
QualityLine connects available manufacturing records so teams can compare yield and failure patterns, investigate process relationships and monitor changes after corrective action. Engineers validate the findings and decide which process changes to make.
Can it separate product defects from test-system issues?
Test measurements, attempt history and repair records can help teams investigate that distinction. A pass on retest alone does not prove a false failure. The conclusion depends on the available evidence and engineering checks of the product and test system.
Do we need to replace our MES or test equipment?
QualityLine adds analysis alongside existing manufacturing systems. The team reviews your available exports or feeds and agrees the required connections. Confirm data access, identifiers and any integration work during scoping.
How quickly can we see an improvement?
Timing depends on data access, record quality, the investigation scope and the process changes required. Start with a defined product or line, agree a baseline and set review milestones. A fixed yield gain or implementation timeline should not be assumed.
What should we bring to a demo?
Bring one yield problem, the affected product or process and an outline of the systems holding inspection, test and repair records. The demo covers the product workflow and fit. Any review or connection of your production data is agreed separately.
See the workflow
Bring a yield problem.
See where QualityLine fits.
Walk through the product with a manufacturing analytics specialist and discuss a focused starting point for your team.
What we’ll cover
- Your recurring yield or test challenges.
- The relevant analysis and investigation workflow.
- Available data sources and integration questions.
- A practical scope for the next step.
