【正文】 iation of the sample by sqrt(n). SEM = s/sqrt(n). See “Z transform”. A feature of factorial Design of Experiments (DoE) that determines the order of the high/low settings of the X?s for each run of an experiment by using a predetermined pattern of +1?s and 1?s for each X. Extreme test points in a Central Composite Design of Experiments. Found by taking the fourth root of the number of ?Cube points? (factorial points) in the design and adding/subtracting this value from the Centre Point. The oute of the Analyze phase. Is the problem centring, spread or both? SPC. A graphical method of monitoring a process and determining statistically when the process requires attention by paring it to a historical mean and calculated control limits at +/ 3 sigma. Output of the Improve phase. Where do the X?s need to be set to control the Y? The study of variation, including methods of describing, quantifying and reducing variation, as well as estimating risks. A regression technique where the model is developed one step at a time, adding X variables one at a time to the model in order of their contribution to changes in Y. A problem solving tool listing the characteristics of interest on one side of the page, and showing contributing factors to the characteristics as branches. Subgroup ……………………… Sustained Process Capability ttest …………………………… Target ………………………… Technical Requirement ……… Test Sensitivity (d/s) ………… Tolerance ……………………… TOP (Total Opportunities) …… Transfer ……………………… Transform …………………… Trivial Many X?s ……………… UCL (Upper Control Limit) …… Unit …………………………… A sample of like parts or related data taken consecutively that contains only inherent process variation (?white noise?) Capability of a process in the long term A statistical test used to pare two means, or to pare a mean to a standard value. The specified or desired average of a process Physical or process characteristic that must be controlled to address a Consumer Cue also known as “The Gap”. A statistic used to determine sample size for hypothesis testing. Compares the difference in means to the spread of the data. The amount of variation allowable by design in a process. Tolerance = USLLSL. Number of opportunities per unit times the number of units. The last phase of a Six Sigma project, where knowledge gained is transferred to all other similar processes ie synergy. Any mathematical relationship used to translate data of one space into data of another space (. transforms to convert nonnormal data to normal data。 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。 the lower graph (Range) plots the difference between the high and low value of the subgroup. Control limits are also used on the Range chart. The dependent variable, or output, of a process. ?First Time? or ?First Pass? Yield. Classical Yield. Number of good units/total produced. ?Normalized Average Yield?. (Rolled Throughput Yield)1/n. Average yield at each step of the process. ?Rolled Throughput Yield?. Yields of all steps of the process multiplied together. The reported process capability. A value derived by bining all defects into one tail of the distribution, then reading the Z value ……………………… Z transform …………………… ……………………………… …………………………… The reported process capability. A value derived by bining all defects into one tail of the distribution, then reading the Z value from a Normal table. May be short term or long term (must quote which). A statistic that converts any normal distribution into the ?standard normal? distribution (mean=0, standard deviation=1. Z=(Xm)/s Longterm process capability. Indicates process performance, including the shift and drift of the process. Shortterm process capability. Indicates “process entitlement”. 謝謝觀看 /歡迎下載 BY FAITH I MEAN A VISION OF GOOD ONE CHERISHES AND THE ENTHUSIASM THAT PUSHES ONE TO SEEK ITS FULFILLMENT REGARDLESS OF OBSTACLES. BY FAITH I BY FAITH