Six Sigma Basics

Define, Measure, Analyze, Improve, Control. It is the data-driven improvement cycle used for projects aimed at improving existing processes.

Green Belts. They lead smaller improvement projects while working part-time on Six Sigma, typically under the guidance of a Black Belt.

Also called an Ishikawa or cause-and-effect diagram, it helps teams brainstorm and categorize potential root causes of a problem, often grouped into the 6 Ms: Man, Machine, Material, Method, Measurement, and Mother Nature.

A p-chart monitors the proportion of defective items in subgroups of varying size, tracking attribute (pass/fail) data over time.

Cp = (USL - LSL) / (6 * standard deviation). It measures the potential capability of a process by comparing specification width to process spread, ignoring centering.

Cpk accounts for process centering. It is the minimum of (USL - mean)/(3σ) and (mean - LSL)/(3σ). Cp assumes perfect centering; Cpk reflects actual performance.

Defects, Overproduction, Waiting, Non-utilized talent, Transportation, Inventory, Motion, and Extra processing (often remembered as DOWNTIME).

VOC is the process of capturing customers' expectations, preferences, and requirements for a product or service, typically through surveys, interviews, focus groups, and complaint data.

A Type I error occurs when the null hypothesis is rejected even though it is true. Its probability equals the significance level, alpha (α).

3.4 defects per million opportunities (DPMO), corresponding to a process operating at ±6 standard deviations between the specification limits.

An X-bar chart plots the subgroup (sample) means over time to monitor the central tendency of a process, with center line and upper/lower control limits calculated from the subgroup averages.

Common cause variation is inherent to the process and predictable; special cause variation comes from external sources and creates unpredictable signals. Control charts help distinguish the two.