Data integration · Electronics & EMS
Manufacturing data integration.
Connect the quality story.
Bring inspection, test, repair and production records into a connected view. QualityLine helps your team put the data behind each quality question in context.
Start with a defined product, line or investigation. Build on the records your factory already creates.
From separate records to shared context
The starting point
Connect the records relevant to your quality question
An inspection result, test measurement and repair note can describe different parts of the same unit’s history. Integration makes those records usable together, where the available identifiers and process context allow.
Production & inspection
SMT process and inspection records
SPI, pick-and-place, reflow, AOI and X-ray data can add process conditions, inspection outcomes and assembly context to an investigation.
Explore SMT analytics →Test & repair
Measurements and recovery history
ICT, functional test, flying probe and repair records help connect measured values, test limits, failures, repeat attempts and corrective work.
Explore test data analytics →Factory systems
Product and production context
Available MES, ERP and production exports can add product, lot, route, station and time context. The relevant fields depend on your systems and the question being investigated.
See the platform workflow →Additional records
Sensor readings and manual logs
Recorded process conditions, manual checks and repair notes can add useful evidence. Review how each record is captured and whether it can be connected to the same unit or period.
Explore manual testing analytics →Data harmonization
Make the records comparable.
Check how they connect.
Different systems may use different names, units and identifiers. Mapping those differences is part of integration; it does not replace missing measurements or establish a link that the source data cannot support.
- Unit and assembly identifiers
- Serial numbers, board IDs or panel positions help connect the same item across process steps.
- Product and revision
- Part number and version context help avoid comparing unlike products or test programs.
- Station and time
- Station IDs, timestamps and time zones place records in the right sequence and production period.
- Measurements and limits
- Parameter names, values, units and applicable limits add detail beyond the final pass/fail result.
- Attempts and outcomes
- Test status and attempt history help distinguish first passes from retests and later recovery.
- Repair findings
- Failure codes, component references and repair actions connect the test symptom with subsequent investigation.
One unit, three records
Illustrative records, not customer data
- 09:10 · TestUnit 1042Voltage test failed
- 09:35 · RepairUnit 1042Repair action recorded
- 09:50 · RetestUnit 1042Voltage test passed
The shared identifier and sequence make the history useful. If an identifier is missing or ambiguous, document the gap before treating records as one unit. Explore manufacturing traceability analytics.
From review to use
An integration plan your engineering and IT teams can assess
Choose the initial scope and validate it before expanding. Historical data can establish a baseline; ongoing collection supports continued monitoring where a suitable connection is available.
- 01
Define the question and sources
Agree the product, line, period and quality measures. Identify the relevant systems, data owners, available history and required update frequency.
- 02
Review samples and mapping
Check field meanings, formats, identifiers, units, duplicates and missing records. Define which comparisons and connections the data can support.
- 03
Agree collection and deployment
Set the access method, transfer arrangements, hosting, responsibilities and any local collection requirements. Confirm the implementation work with the system owners.
- 04
Validate and maintain the feed
Compare imported records and results with the source. Agree checks for missing or delayed data and a process for changes to formats, test programs or identifiers.
Deployment and data handling
Discuss QualityLine cloud, customer private cloud or on-premises deployment for your project. Confirm the available configuration and support responsibilities during scoping.
Review access permissions, transfer methods, hosting location, retention and confidentiality requirements with your IT team before connecting production data.
Who does what?
Your team: identifies data owners, authorizes access and explains process and field definitions.
QualityLine: reviews mapping and collection needs, configures the agreed integration and supports validation.
Together: agree acceptance checks, ongoing ownership and a response when source data changes.
Put the data to work
A connected foundation for quality decisions
Integration prepares the evidence for analysis. Engineers use the resulting context to investigate, validate findings and decide what to change.
Investigate recurring failures
Compare measurements and process context across affected and passing units.
Root cause analysis →Understand yield losses
Review first attempts, retests and repair history with consistent counting rules.
Improve first-pass yield →Follow a unit’s history
Review connected records across the process and identify where coverage ends.
Traceability analytics →Molex customer story
22%
Reported increase in production capacity within the first year
Molex’s customer story describes automated data integration, KPI reporting and remote monitoring, implemented with QualityLine’s dedicated team.
The reported capacity result relates to the overall customer implementation. It is not an integration-only effect or a guaranteed outcome.
Read the Molex customer story (PDF) →Integration questions
What to confirm before you start
Which data formats can QualityLine work with?
Test log files and database extracts can be reviewed as starting inputs. Compatibility depends on the structure, fields and access available. Bring representative samples and field definitions so QualityLine can confirm parsing, mapping and the collection method for your sources.
Do we need an MES or a new API?
An MES is not required for every project. Available inspection, test, repair and production records can provide a starting point. A new API is not necessarily needed when a suitable existing output is available; the collection approach and any connection work are confirmed during the technical review.
What if systems use different serial numbers?
Review whether a reliable mapping exists, such as a panel-to-board relationship or an assembly record. If it does not, some analysis may be limited to a station, batch or period. Do not assume complete unit traceability from timestamps alone.
Can we use historical data and add ongoing collection?
Yes. Historical records can support an initial baseline and investigation. Ongoing collection can then support monitoring for the agreed sources. The update frequency depends on how often the source produces accessible data and on the configured collection method.
Can we keep our existing systems and data outputs?
QualityLine works alongside existing manufacturing systems. Review the current outputs first, then agree any collection or mapping work needed. Include the relevant system owners when planning access and changes.
How long does integration take?
The timeline depends on the number of sources, data access, record quality, matching requirements and deployment scope. Begin with a defined product, line or question, then agree milestones and acceptance checks before implementation.
Plan your starting point
Bring your quality question.
Map the data behind it.
See the QualityLine workflow and discuss the sources and integration questions relevant to your factory.
Any review or connection of production data is agreed separately.
Useful context for the discussion
- The product, line or quality issue you want to investigate.
- The systems that hold inspection, test and repair records.
- Available identifiers, history and export formats.
- Your IT contact and preferred deployment approach.
