【正文】 log, reciprocal, power functions etc.) The 80% of the independent variables (X?s) that generate only 20% of the total process variation. Variables that influence the process, but at a much less significant level than the ?Vital Few?. The upper control boundary on a Statistical Process Control (SPC) chart. A limit calculated as the mean plus 3 standard deviations. NOTE: SEM (Standard Error of the Mean) is used for s: stdev = s/sqrt(n) A userdefined quantity representing the output of a process. May be a part, system Unit …………………………… USL …………………………… Variance ……………………… Vital Few X?s ………………… White Noise …………………… X ……………………………… Xbar ………………………… Xbar/R chart ………………… Y response…………………… …………………………… …………………………… ……………………………… ……………………… A userdefined quantity representing the output of a process. May be a part, system, ponent of a part or a subsystem. Upper Specification Limit (Standard Deviation)2 The 20% of the independent variables that generate 80% of the total process variation. These are X?s which must be controlled to bring a process to Six Sigma levels of performance. See ?Common Cause Variation?. The natural variation within the process, free of external influences. The independent variable(s), or input(s), of a process. The mean or average of a sample. The sum of all data in the sample divided by the number of samples. A Statistical Process Control (SPC) chart in which the upper graph is used to plot subgroup averages pared to calculated control limits。 ., a feature specified with a specification to one decimal place would require a gauge with a resolution of two decimal places etc. A roman numeral that indicates the degree of confounding in a fractional factorial design. Higher resolution indicates less confounding . less ambiguity in the source of effects. The product of yields at each step of a process. Can be estimated using the Poisson Approximation. s ………………………………… Sample ……………………… Session Window …………… Shift …………………………… Short term data …………… Sigma (s) ……………………… Six Sigma Team Member …… Skewness …………………… Specification ………………… Spread ………………………… Stability (Gauge) ……………… Standard Deviation ………… The standard deviation of a sample. A measure of spread (or variability) of the data. s=sqrt[S(xxbar)/(n1)] A collection (subset) of data intended to represent the characteristics of the parent population. One of the 4 Minitab windows. Used for mand entry and data output. The difference between shortterm and longterm process variation. = Data obtained in such a way that it contains NO assignable cause variation (?black noise?). Only the inherent process variation is represented, which allows calculation of The standard deviation of a population. A stakeholder in the Six Sigma process. A person who needs to have an understanding of the methodology, but does not formally use the tools. Evaluation of the symmetry of a distribution. Skewness=0 for perfect symmetry。 the lower graph (Moving Range) plots the difference between sequential data as points on the chart. Control limits are also calculated for this chart. Variables (X?s) that influence the response of a dependent variable (Y) Statistical analyses that quantify the risk of statements about populations, based on sample data. Inferential statistics are usually hypothesis tests or confidence intervals. The Best the process can be, with only variation due to white noise present. See Entitlement, A graph used to analyse factorial and fractional factorial designs of experiments. Indicates the effect on Y when two X?s are changed simultaneously. The greater the difference in slopes between the X?s, the greater the interaction. Kurtosis ………………………… L1 Spreadsheet ……………… L2 Spreadsheet …………… LCL (Lower Control Limit) … Leverage Variable …………… Linearity (gauge)……………… Long term data ………………… LSL ……………………………… m ………………………………… Macro …………………………… Main Effects Plot ……………… Master Black Belt …………… Comparison of the height of the peak of a distribution to the spread of the ?tails?. The kurtosis value is 3 for a perfect normal distribution. Excel spreadsheet for discrete data that calculates subsystem Z values and ?rolls? them into a systemlevel Z value. Replaced by Product Report in Minitab release Excel spreadsheet for continuous data that calculates and Replaced by Process Reports in Minitab release The lower control boundary on a Statistical Process Control (SPC) chart. A limit calculated as the mean minus 3 standard deviations. Note: SEM (Standard Error of the Mean) is used for s。 variation due to outside influences. See ?Black Noise?. Statistical Process Control (SPC) chart for discrete data. Includes p, np, c and u charts. Data that can be described by levels, integer values or categories only. See Discrete data. The sum of all data in a sample divided by the number of data points in the sample. See Mean. b error …………………………… b risk …………………………… Baselining ……………………… Benchmarking…………………… Black Belt ……………………… Black Noise ……………………… Boxplot ………………………… Brainstorming …………………… Centring ………………………… Centring of X variables ………… Central Limit Theorem ………… The error made if sameness is claimed, when the reality is difference (. accepting bad parts Consumer?s Risk). The risk (probability) of makin