Results are scattered
Production test results can be stored in different folders, databases, files or station-specific systems. This makes it difficult to compare failures across lines, products and time periods.
Test Data Management
Test Data Management for Manufacturing Teams
Arc helps hardware and manufacturing teams move from scattered test results to connected insight across yield, failures, traceability and quality.
What is test data management?
Test data management is the process of collecting, structuring, analysing and reusing test results across engineering, validation, production and quality workflows. For manufacturing teams, it connects production test data to failures, yield, traceability and quality evidence so teams can investigate problems faster.
What is test data management?
Test data management is the process of collecting, structuring, analysing and reusing the results produced by engineering, validation and production test systems.
For hardware manufacturers, test data often sits across LabVIEW applications, TestStand sequences, CSV files, databases, MES records, spreadsheets, local machines and quality reports. Each system may capture part of the picture, but teams still struggle to answer basic operational questions quickly:
- Which products are failing most often?
- Which test stations are causing repeat failures?
- Which limits changed, when and why?
- Which units passed, failed, retested or shipped?
- Which failures are linked to a batch, supplier, fixture or software version?
- What evidence do we need for customers, auditors or internal quality reviews?
Arc helps teams turn fragmented test outputs into a usable test data layer for manufacturing, quality and engineering teams.
Why test data becomes difficult to manage
Test systems are usually built to run tests first and analyse data second. That creates problems as production scales.
Formats are inconsistent
One test station may produce CSV files, another may write to a database, and another may generate PDF reports. Even when the tests are similar, the data structure may not be.
Context is missing
A result without product, serial number, station, operator, limit, fixture, software version and retest history is hard to use for root cause analysis.
Quality teams need evidence
Quality and customer-facing teams often need traceable records, not just summary dashboards. They need to know what happened, when, where and under which conditions.
What Arc helps teams do
Centralise production test data
Bring together test results from different systems, stations and formats so teams can see what is happening across products and production lines.
Analyse yield and failures
Identify repeat failures, weak test steps, station-level issues, yield drift and recurring defect patterns.
Improve traceability
Connect test results to serial numbers, batches, test limits, stations, operators, timestamps and quality workflows.
Prepare data for AI analysis
Structure test data so engineering and quality teams can query results, investigate failures and reuse test evidence more effectively.
Common test data sources
Arc is designed for teams with test data spread across systems such as:
- LabVIEW applications
- TestStand sequences
- Custom automated test systems
- End-of-line testers
- Manufacturing databases
- CSV, XML, JSON and TDMS files
- MES and QMS exports
- Manual quality reports
- Customer-facing test certificates
- Engineering validation reports
Who is this for?
Manufacturing leaders
Teams responsible for yield, throughput, production visibility and operational improvement.
Test engineering teams
Teams building, maintaining and scaling automated test systems across products and production lines.
Quality teams
Teams responsible for traceability, non-conformance investigation, customer evidence and audit readiness.
Hardware engineering teams
Teams that need test results to understand design issues, supplier problems, product reliability and field failures.
Explore test data management use cases
Resource
Production test data management
Manage production test results across stations, lines, products and retests.
ResourceManufacturing test data analytics
Turn test results into insight across yield, failures, trends and quality issues.
ResourceTest data traceability
Connect test records to products, serial numbers, limits, stations and quality evidence.
ResourceTestStand data management
Use TestStand result data more effectively across production and quality workflows.
ResourceLabVIEW test data management
Structure LabVIEW outputs so teams can analyse, compare and reuse test results.
Test data management by industry
Resource
Electronics manufacturing
Manage PCBA, box-build, functional test, inspection and production quality data.
ResourceAutomotive electronics
Connect test data to traceability, supplier quality, warranty risk and high-volume production.
ResourceAerospace and defence
Support high-reliability test evidence, auditability, configuration control and qualification workflows.
ResourceMedical devices
Improve traceability and quality evidence across regulated device manufacturing and test.
ResourceBattery manufacturing
Track test results across cells, modules, packs, BMS, end-of-line testing and quality workflows.
ResourceIndustrial electronics
Manage test data for sensors, controls, instrumentation, drives and rugged electronic products.
ResourceSemiconductor test
Connect test data to yield, binning, reliability, failure analysis and production quality workflows.
How test data management differs from MES and QMS
MES systems help manage manufacturing execution. QMS systems help manage quality processes. Test data management focuses on the detailed results, limits, failures, retests and evidence generated by test systems. Many teams need all three: MES for production control, QMS for quality workflows and a test data layer for deeper analysis and traceability.
FAQ
What is test data management?
Test data management is the process of collecting, structuring, analysing and reusing test results across engineering, validation, production and quality workflows.
Why do manufacturing teams need test data management?
Manufacturing teams need test data management because test results are often scattered across stations, files, databases and reports, making it difficult to analyse failures, improve yield and prove traceability.
Is test data management the same as MES?
No. MES manages manufacturing execution. Test data management focuses on the detailed results, limits, failures, retests and evidence produced by test systems.
Is test data management only for production?
No. It can support production test, engineering validation, reliability testing, incoming inspection, supplier quality and customer evidence workflows.
Can Arc work with LabVIEW and TestStand environments?
Arc is designed for teams that generate test data from systems such as LabVIEW, TestStand and custom automated test environments.
What is the first step?
The first step is to map where test data is created, how it is stored, what context is missing and which quality or engineering questions the team cannot answer quickly today.
Request Access
Bring an example of your current test data workflow and we’ll map where results, failures, limits, traceability and quality evidence are getting lost.
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