SPC & Six Sigma (DMAIC)

Scope

• ›Variable data: seam strength, GSM, key body measurements.
• ›Attribute data: end-of-line DHU, cut-panel defects, printing defects.
• ›Process capability studies for CTQ measurements against garment tolerance.
• ›Six Sigma projects following Define–Measure–Analyse–Improve–Control (DMAIC).

Cost & implementation difficulty

Not yet verified. Independently verified evidence is not available on this site. This section will be published only when a public reference exists.

Steps

1. Define: charter the project — problem, CTQ, baseline, goal, scope, team, timeline.
2. Measure: validate the measurement system (Gage R&R), collect baseline data with sub-grouping.
3. Analyse: choose control chart by data type — X̄–R or X̄–S for variables, p / np / c / u for attributes.
4. Analyse capability once the process is in statistical control: Cp = (USL−LSL)/6σ, Cpk = min(USL−μ, μ−LSL)/3σ.
5. Improve: pilot a change, re-run capability, confirm shift in mean/spread; use design-of-experiments where needed.
6. Control: standardise the new method, install SPC monitoring, define out-of-control reaction plan.

Risks

• ›Interpreting capability on an out-of-control process.
• ›Recalculating control limits every shift — hides drift.
• ›Confusing 'in-control' with 'meets specification'.
• ›Closing a project before Control phase evidence is in place.

Evidence & records

• ›Project charter with baseline and target metric.
• ›Signed measurement-system analysis (Gage R&R) with %GRR and NDC.
• ›Control charts with control limits, subgroup size and reaction log.
• ›Capability report (Cp, Cpk, Pp, Ppk) with sample size and stability confirmation.
• ›Control plan and standard operating procedure updated for the improved process.

Case study

Not yet verified. Independently verified evidence is not available on this site. This section will be published only when a public reference exists.

Author & last reviewed

Authored by Sanjeewa Dehiwalage.

Last reviewed: 2026-07-17