【正文】 ogonal …………………… pvalue ………………………… Pareto Analysis ……………… The average. May be the average of a sample (xbar), or the average of a population (m). See ?Gauge RR?. The middle value of a set of data (the 50th percentile). A statistical software package containing the majority of Six Sigma tools. A widelyused, monlyseen distribution where data is symmetrically distributed around the mean (?bell curve?). A graphical hypothesis test in which sample data is pared to a ?perfect normal? distribution. Ho: the sample data is the same as the ?perfect normal? distribution. Ha: the sample data is different (. nonnormal). The process of converting nonnormal data through the use of a transformation function. The average yield of a process with multiple steps or operations. = ()1/n See ?Ho?. Literally, “right angles”. A feature of a welldefined experiment that allows main effects to be separated from 2way and higher order interactions, as well as quadratic (squared) terms. The probability of making an alpha (a) error. A value used extensively in hypothesis testing. Also referred to as the ?observed level of significance?. pvalues are pared to the ?acceptable? level of alpha risk in order to make decisions in hypothesis tests. A problem solving tool that allows characteristics to be ranked in descending order of importance. Pareto Principle ……………… Passive (opportunity/defect) … Point of Inflexion ……………… Poisson Approximation ……… Population …………………… Power of the Test …………… ppm …………………………… Practical Problem …………… Practical Solution …………… Precision ……………………… PreControl …………………… Principle of Reverse Loading .. Probability of a defect p(d) … The “8020” rule. The principle that 20% of the variables cause 80% of the variation. A defect or opportunity that is counted upon occurrence, but that is not part of the active monitoring process. Point on the normal curve where it changes from convex to concave. Mathematically defined by setting the third derivative to zero. A mathematical approximation for Rolled Throughput Yield, given DPU: = eDPU. All data of interest for a particular process, recorded or not. Usually modelled with samples. The likelihood of detecting beneficial change. Represented as 1b. The probability of rejecting the null hypothesis. Parts per million defective. A discrete measurement of defectives for long term data The output of the Measure phase. A characterization of the Z value, centring and spread for Y. The output of the Control Phase. The optimised X levels and control plan to maintain the process at its highest Z value. How closely the data is clustered around their mean. Describes the spread of the data. A Statistical Process Control (SPC) method that allows an operator to take action on a process based on where the part measurements fall in a normal distribution. Parts are coded red, yellow or green. Planning ahead – Need to define what do you want to know, so what tool/test should be used, so what data do you need? The ?tail? area of the normal curve, beyond the specification limit(s). Problem Statement …………… Process Capability …………… Process Characterization …… Process Map ………………… Process Optimisation ………… Project Hopper ……………… QFD …………………………… Quartiles ……………………… Rbar/d ……………………… Random Cause Variation …… Range ………………………… Rational Subgrouping ……… A brief but succinct description of the issue under investigation. Includes the practical and business reasons for the project. A statistic that numerically describes how well the process could perform in the absence of ?black noise?. Examples: , Cp Understanding the Y?s and X?s in a process. Developed through the tools of the Define, Measure and Analyse phases. A problem solving tool that graphically describes each step or phase in a process. Defining the best operating point for X?s in a process. Developed through tools of the Improve/Control phases. A stack of potential Six Sigma projects, to be picked up by Black Belts or Green Belts when resources allow. Quality Function Deployment. A rigorous method of determining technical requirements and CTQ?s from the definition of Consumer Cues. ?Quarters? of a population. 1/4 of the data fall below the first quartile, 1/4 of the data fall above the 3rd quartile. An estimate of standard deviation using the range of the data and tabled adjustment factors. Used in calculation of control limits in Minitab Gauge RR Xbar graphical output. See ?White Noise?. The inherent variation of the process, free from external influences. The largest value in a data set minus the smallest value in the data set. A data collection technique that allows the separation of short term variation from long term variation. Regression …………………… Repeatability (Gauge) ……… Repetition ……………………… Reproducibility (Gauge) ……… Response Surface Experiment Resolution (Gauge) ………… Resolution (Fractional Factorial) ………………… Rolled Throughput Yield …… A statistical modelling tool that allows data to be represented by an equation. Used for continuous Y responses, usually with continuous X inputs. (There is special technique within Minitab called Logistic Regression which handles special forms of discrete X?s.) Ability of a gauge to consistently measure the same part with the same results. Part of the output o