QualityLine · Manufacturing quality improvement
Improve product quality.
Make the improvement last.
Turn inspection, test and repair records into a focused quality improvement project. QualityLine helps electronics and EMS teams understand recurring defects, compare production groups and review what changes after corrective action.
Choose the problem worth solving
Give the team a specific quality question.
Product quality improvement starts with a clear requirement and evidence of where performance falls short. Choose one product family, defect or production stage so the team can agree what to investigate and how to judge progress.
Why does this failure return?
Connect original failures with inspection findings, repair feedback and production conditions. Prioritize patterns that need engineering investigation.
Where is quality creating extra work?
Review repeated tests, repair activity and recorded scrap alongside output. A final pass can hide the effort required to get there.
Why do comparable runs differ?
Compare the same product revision and test conditions across lines, stations or periods. Check the records before attributing a difference to the process.
From a priority to a measured result
Connect the investigation to the follow-up.
Use the same definitions from the first review through the improvement check. QualityLine brings available manufacturing records together so engineers and quality managers can work from a shared view.
Agree what “better” means.
Name the defect, affected units, comparison period and owner. Confirm which records count as first attempts, retests, repairs and scrap. Review missing records and measurement consistency.
Follow the result across stages.
Match available assembly, inspection and test records. Compare relevant groups and examine repair feedback. An association with a material lot or station is a lead for validation.
Test the engineering explanation.
Check alternative causes, including fixtures and test programs. Your team confirms the cause and approves any process change. Record what changed and when before comparing results.
Analytics supports the decision. It does not authorize a process change or product release.
Check whether the gain holds.
Review later production with comparable product mix, test coverage and counting rules. Watch repeat failures and other affected measures. Assign an owner to investigate if performance changes again.
This fits a structured improvement approach such as define, measure, analyze, improve and control. Read ASQ’s overview of DMAIC.
Keep the measurement clear
A quality improvement needs more than one headline number.
Choose a primary outcome and a small set of supporting measures. Keep the unit, denominator and production scope visible so a change in product mix or retest handling does not look like an improvement.
First-pass yield
Units passing the defined process on their first attempt divided by units entering it. Keep repaired or retested units out of the first-pass numerator.
Nonconforming units
Count unique units that fail the agreed requirement against the inspected population. Track defect types separately: one unit can have more than one defect.
Rework and scrap
Review affected units and recorded labor, material or disposal costs. Agree cost assumptions and keep repeat repair attempts visible.
Escapes and returns
Where records can be matched, review failures found downstream or after shipment. Use an appropriate shipment cohort and allow for the delay before returns arrive.
Process capability is a separate question about measurements relative to specifications. Check process stability and the method’s assumptions before interpreting Cpk. Read the process capability guide →
Illustrative electronics example · No customer data
Final pass rate looks steady.
Repair demand is growing.
An electronics team sees more repeat repairs even though most units eventually pass final test. The improvement project needs to follow the failure history and the workload behind that final result.
- Keep the first failure. Separate the original test result from later attempts and repair dispositions.
- Compare a consistent group. Review the same board revision, test program and production scope. Check whether repeated symptoms share a station, component lot or repair action.
- Validate one change. Engineers investigate the suspected mechanism and document the approved action.
- Review the wider result. Compare repeat failures, repair demand and scrap in later production. Confirm that a better headline result has not shifted the loss elsewhere.
Published customer evidence
Emerson: bringing production records into a shared view.
Emerson customer account
18Production chains in the reported implementation
Emerson’s customer account describes harmonized data capture and analysis of yield problems across 18 production chains. It also describes KPI reporting, dashboard customization and improved production visibility.
The account reports a return on investment of around four months. This is a customer-specific outcome; the investment baseline and calculation method are not detailed in the published account.
Read the Emerson customer account (PDF) →
Results depend on the production environment, connected records and implementation scope.
Plan a focused evaluation
Bring one quality question and the records behind it.
Start with a product family, line or recurring issue. Review source access, export formats, shared identifiers and refresh frequency with your engineering and IT teams.
QualityLine can work with available production, inspection, test and repair data, including relevant MES or ERP records. Connection requirements and analysis coverage are agreed for the project.
Explore the manufacturing analytics platform →- Define the decisionWhich issue will the team investigate, and who owns the response?
- Check the evidenceCan records be matched, and are missing results or test changes understood?
- Agree the evaluationSet the baseline, access controls, success measures and review period.
Common questions
Before you start a quality improvement project.
How can manufacturing analytics support product quality improvement?
It connects available production, inspection, test and repair records so teams can compare quality outcomes, investigate recurring patterns and review results after a change. Engineers validate the explanation and decide which corrective action is appropriate.
How is this different from root cause analysis or first-pass yield improvement?
This use case covers the improvement project from selecting a problem to reviewing whether the result lasts. Root cause analysis focuses on investigating why a failure occurs. First-pass yield improvement focuses on units passing a defined process on the first attempt. Both can support the wider quality project.
Which quality measure should we start with?
Choose a measure that matches the problem: first-pass yield, nonconforming units, repeat repairs, scrap or downstream failures. Define the population, counting rules and review period. Use supporting measures to check whether a change has moved the loss elsewhere.
Does QualityLine replace our quality management system?
The analytics supports investigations and performance review. Your team keeps its approved quality procedures, document controls, corrective-action approvals and release responsibilities. Review the relationship with existing systems during project scoping.
How quickly can we expect an improvement?
Timing depends on data access, record quality, the investigation and the production needed to evaluate a change. Agree the implementation plan, baseline and review period before setting a target. A dashboard alone does not establish that product quality has improved.
What should we prepare for a demo?
Bring a short description of the quality issue, the products or lines involved and the systems that hold inspection, test and repair records. We can discuss the workflow and data requirements first; sharing production data is agreed separately.
See the workflow
Choose a quality problem.
See how to investigate it.
Walk through the analysis, the records it needs and the measures your team could use to evaluate an improvement.
What we’ll cover
- Your production and quality priorities.
- The relevant investigation and monitoring workflow.
- Data requirements and a suitable evaluation scope.
Use of your production data is scoped separately after the initial discussion.
