Quality Module
MSA to validate measurement system reliability
In IVR 5.0 AI, MSA ensures that results generated by IMTE — Inspection Measuring and Test Equipment are statistically reliable, repeatable and reproducible, using real production data — without manual data entry.
What MSA evaluates
- Repeatability and Reproducibility (Gage R&R)
- Measurement variation vs. process variation
- Operator, method and equipment influence
- Statistical confidence for SPC and decisions
- Structured data aligned with QIF (ISO 23952)
Why MSA matters
If the measurement system is not reliable, process control becomes uncertain. MSA reduces the risk of accepting out-of-spec parts or rejecting conforming parts, using objective criteria and statistical evidence.
Controlled decision risk
Turn measurement variation into practical criteria for product release, process validation, and inspection strategy improvements.
Consistent data, less rework
Integration reduces manual transcription and “shadow spreadsheets”. Studies stay aligned with the real measurement flow.
Audit-ready evidence
Reports include history, data origin, study versioning, and references to the inspection plan.
Connected to CAD + QIF + DMIS
MSA delivers more value when tied to dimensional results and traceability from engineering to inspection.
Structured around QIF (ISO 23952) to standardize identification, metadata, traceability, and interoperability across systems.
How IVR runs MSA
The MSA module focuses on evidence and traceability. Data can come from your current ecosystem and, when applicable, directly from any IMTE — Inspection Measuring and Test Equipment, preserving identification and history without manual intervention.
1) Study standardization
Define parts, characteristics, operators, repetitions, and criteria. Studies are versioned and reusable.
2) Data capture and structure
Build datasets with full identification: part/cavity, operator/shift, instrument, timestamp, lot, and context.
3) Calculation and validation
Run the study with configurable indicators and criteria, comparing system variation to part variation.
4) Reports and evidence
Generate reports ready for audits and DMS, with traceability for both data and applied method.
Integration to reduce decision risk
- QIF (ISO 23952) as the interoperability and data structure foundation
- Dimensional reports with evidence and traceability
- CAD + QIF + DMIS to close the loop from engineering to inspection
- Automated capture to eliminate typing errors and record divergence
Typical outputs
- Versioned, reusable studies
- MSA reports with evidence and traceability
- Configurable criteria aligned to internal standards
- Audit- and DMS-ready documentation
Common use cases
Apply MSA whenever decisions depend directly on measurement system reliability.
Process validation
Validate the system before using measurement data for process release and capability.
Fixture and method changes
Reassess the impact of a new fixture, probe, program, strategy, or measurement condition.
Equipment comparison
Check consistency across systems, shifts, and operators, reducing result conflicts.
Customer and audit evidence
Traceable study documentation linked to measurement history and dimensional reports.
With measurement validated, the next step is continuous statistical control: SPC.
Ready to validate your measurement system with evidence?
Share your scenario (parts, characteristics, method, and data origin) and we will define the technical path to reduce decision risk with MSA.