【正文】 g a beta error (frequently set at 10%). Evaluating the capability of a process as it stands today, without “tweaking” . passive observation. Evaluating the capability of similar processes to quantify what constitutes ?the Best?. A person whose full time job consists of application of Six Sigma tools/methods on projects. Process variation due to ?outside influences?. See Assignable Cause Variation. Graph showing the portion of a distribution between the first and third percentiles within a ?box?. The boxplot also shows the median of the distribution and the extreme values. Often used to pare population. A technique used by an Advocacy Team to, for ., develop a list of potential X?s at the beginning of project. A process characteristic describing how well the mean of the sample corresponds to the target value. A method used to transform X variables in DoE?s that develop higher order (quadratic) models。Glossary 4Block …………………………… a error …………………………… a risk ……………………………… Accuracy ………………………… Active (opportunity or defect) … Advocacy Team ………………… Alternate Hypothesis ………… ANOVA …………………………… ANOVA method (Gauge RR) … Assignable cause variation …… Attribute Chart ………………… Attribute data …………………… Average ……………………… Graphical tool to show the relationship between process capability, control technology. The error made if difference is claimed, when the reality is sameness (. rejecting good parts。 Producer?s Risk). The risk (probability) of making an a error (frequently set at 5%). How close measurements are, on average, to their target. An opportunity or defect that is being measured (a defect we are looking for). The group of people who have a stake in the Six Sigma project, including those who must keep it in control. See Ha Analysis of Variance. A statistical method of quantifying contributions of discrete levels of “X”s to the variation in a “Y” response. A Minitab selection for Gauge RR that includes operatorpart interaction in the calculation of variation contributions. The most accurate method for Gauge RR. Removable variation in a process。 reduces correlation between X?s. A fundamental statistical theorem stating that the distribution of averages of a characteristic tends to be normal, even when the parent population is highly nonnormal. Central Composite Design …… Champion ………………………… Champion Review ……………… ChiSquared test ………………… Classical Yield …………………… Common Cause Variation ……… Components Search …………… Confidence ……………………… Confidence Interval ……………… Consumer ………………………… Continuous Data ………………… A Design of Experiments (DoE) method where each X is tested at 5 levels (see ?Star Points?). A CCD provides the capability to model a process with a quadratic equation OR a linear equation. Typically a director someone who can support the Six Sigma project and has the authority to remove barriers and provide resources. Takes an active part in Project Review. A regular meeting to present Six Sigma projects, share experiences and remove roadblocks. Hypothesis test for discrete data. Evaluates the probability that counts in different cells are dependent on one another, or tests Goodness of Fit to some a priori probability distribution. See “First Pass Yield”. Good units produced divided by Total Units Produced. See “White Noise”. The inherent variation of a process, free from external influences. Usually measured over a short time period. A method of screening for Vital Few X?s in manufactured assemblies. Also known as ?Part Swapping?. The plement of alpha risk. Confidence = 1a. A range of plausible values for a population parameter, such as mean or standard deviation. The end user of a product (the homeowner, for .). The consumer is external to the business. Data that can be meaningfully broken down into smaller and smaller increments . length, temperature etc.) Contour Plot ………………… Control Limits ……………… Cost of Quality ……………… Cp …………………………… Cpk …………………………… CQ …………………………… CTQ ………………………… Cube Plot …………………… Customer …………………… Data Window ………………… Defect ………………………… Dependent Variable ………… A graph used to analyze experiments of a Central Composite Design. Two X?s prise the axes, and levels of constant Y are shown in the body of graph. Resembles a topographical map. Lines on a Statistical Process Control (SPC) chart that represent decision criteria for taking action on the process. Lines are drawn +/ 3 standard deviations (s) from the mean. A financial reconciliation of all the costs associated with defects (scrap, rework, concessions etc.) Statistic used to measure Process Capability. Assumes data is centred on target. Similar in concept to Statistic used to measure Process Performance. Does not assume centred data. Similar in concept to Commercial Quality. Used to categorize nonmanufacturing projects that impact the consumer and/or customer. CriticaltoQuality characteristic. An aspect of the product or service that is important to the customer/consumer. A graph used for analysis of the results of a factorial designed experiment (DoE). Shows test conditions that optimize the response. The recipient of the output of a process. May be internal (. Assembly is a customer of finishing shops), or external (. Currys, Belling etc.) who then sell our products to consumers. The spreadsheet window in Minitab where data is entered