What Is Six Sigma? DMAIC, Defects, and Statistical Control

Six Sigma is a data-driven methodology for reducing process variation and eliminating defects. A Six Sigma process produces fewer than 3.4 defects per million opportunities. The methodology provides the statistical framework that lean manufacturing often lacks.

The name: Sigma (σ) is the statistical standard deviation. A Six Sigma process has its mean six standard deviations away from the nearest specification limit — meaning defects are statistically near-impossible.

Sigma Levels — What They Mean

Defects Per Million Opportunities (DPMO) by Sigma Level

1 Sigma — 691,462 DPMO (69% defective)

691,462 DPMO

3 Sigma — 66,807 DPMO (typical manufacturing)

66,807 DPMO

4 Sigma — 6,210 DPMO

6,210 DPMO

5 Sigma — 233 DPMO

233 DPMO

6 Sigma — 3.4 DPMO (world-class)

3.4 DPMO ★

The DMAIC Framework

Define — State the problem clearly

Define the problem in terms of customer impact. Identify the project scope, team, timeline, and success criteria. The problem statement should be data-driven: "X% of units in Area Y exceed standard cycle time by Z minutes."

Measure — Quantify current performance

Collect baseline data on the current process. Establish a measurement system. Validate that your measurement system is accurate. Quantify the gap between current and target performance. In TaktClock, this is the session database — actual elapsed times vs. standard times, automatically logged.

Analyze — Find the root causes

Use statistical analysis to identify which inputs drive the output variation. Distinguish signal from noise. Tools: fishbone diagram, Pareto chart, regression analysis, hypothesis testing. The Bottleneck and Trends tabs in TaktClock support this phase.

Improve — Implement and validate solutions

Design solutions that address root causes. Test and validate that each solution actually reduces variation. Use pilot runs and controlled experiments. Measure the improvement against the baseline established in the Measure phase.

Control — Sustain the improvement

Build monitoring systems that detect if the process drifts back. Control charts, standard work documents, and regular audits. TaktClock's Trends tab provides the ongoing monitoring data to detect drift before it becomes a problem.

❓ Knowledge Check

In the DMAIC framework, which phase is responsible for validating that the measurement system accurately captures the data you need?

✓ Correct! Measurement System Analysis (MSA) — including Gage R&R studies — is performed in the Measure phase. If the measurement system is inaccurate, all subsequent analysis is built on bad data. Validating the measurement system first is a foundational Six Sigma principle.

Lean Six Sigma and TaktClock

Lean Six Sigma combines the waste elimination of lean with the variation reduction of Six Sigma. TaktClock supports both disciplines: the live takt timer and floor map address lean waste visibility, while the session database provides the cycle time data needed for statistical analysis in Six Sigma improvement projects.

Session database for MSA Cycle time variation data Trends tab for control phase Bottleneck tab for Analyze phase

See It Live

These Concepts, Running on Your Floor

30 minutes. Real product. We'll show TaktClock implementing these principles live against your production configuration.