Measure submission pack

Learning objectives

• Assemble a Measure submission pack that proves data trustworthiness.
• Fix the measurement system before quantifying performance.
• Report baseline stability and capability with honest limitations.

Required evidence

• Detailed process map
• Operational definitions (point, method, condition, unit, tolerance)
• Data-collection plan and check sheet
• Sampling and stratification plan
• MSA (Gage R&R or attribute agreement)
• Baseline time plots, Pareto and descriptive statistics
• DPU/DPMO/yield where valid
• Stability and capability with assumption checks
• Revised target and refreshed benefit

Copy-friendly Measure pack checklist

• Operational definitions signed
• MSA passes minimum thresholds
• Sampling is representative
• Baseline is stable before capability
• Raw flat data and codebook retained
• Exclusions documented with reason

Garment-factory example

A measurement project defines a chest-measure point, tape method and tolerance; runs a 3-appraiser × 10-part gauge study; then samples across size, style and shift for two stable weeks before capability is calculated.

Method

1. Pilot the data-collection sheet before scaling.
2. Repair the measurement system before analysis.
3. Store raw flat data plus codebook, not only summaries.

Common mistakes

• Capability calculated on unstable data.
• Convenience sampling.
• Redefining defects mid-collection to improve the number.