Six Sigma Study Guide

Six Sigma Study Guide - Six Sigma Study Guide A Attribute...

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Six Sigma Study Guide A Attribute data is discrete Appraisal- ex: cost of calibration and first trial test hardware Affinity diagram: used in define Anova test for comparing 3 or more means are that the populations are independent, Normal and that they have homogenous (equal) variances Analyze Phase: identify the root cause of process variability B Binomial- (n/r(n-r))*P^rQ^n-r Brainstorming and prior operational knowledge are used during the design phase of the experiment to gather process information, help determine the objectives of the study and to identify potential input factors. Breakthrough: describes the desired change in performance level Blocking is used to account for the variation due to known sources such as people, machines, etc. that are not of direct interest to the study, in order to minimize their impact on the total variation. Balanced Scorecard: Corporate, Sales, Internal, Infrastructure baseline performance level: Provide a starting reference point to gage improvement Box Plots are used to investigate the effect of discrete inputs on continuous outputs. Several levels of inputs can be compared side-by-side, making this an easy-to-understand tool for use with a team C Cyclical variation can be displayed as variation among consecutive pieces, variation among groups of pieces, variation among consecutive batches Conveyance is moving a single part excess times Continuous flow is to reduce the batch (or lot) size to one Change Agent: overcome fear of unkown Check Sheet: used for collecting data to study the symptom of a problem Cp tells you=what is possible if your process is perfectly centered, process potential, relative ratio of the process variation to the specifications range, the best you process can be o Cp is less or equal that Pp o Process becomes centered the Cpk or Ppk increases o Cp of 3 means very little product (1%) is out of specification o Cp and Cpk are for short term data sets o Sigma level increases-Ppk and Cpk increase o The process data must be normally distributed in order for any capability index (Cp, Cpk, Pp, or Ppk) to correctly reflect capability. Transformation may be accomplished using any of several different algorithms to achieve a fit to the normal distribution. Contingency Tables- compare more than two sample proportions with each other Cpk equals 1 when +- 3 sigma and normal center distribution Cp=(USL-LSL)/6ó = (5-3)/6*0.25 = 1.33. Cpk=min((USL-process mean)/3ó , (process mean-LSL)/ 3ó) = min((5- 4.2)/3*0.25 , (4.2-3)/3*0.25) = min(1.07,1.6) = 1.07. Coefficient of variance: standard deviation/mean complete fold-over adds a second fraction of runs to the design with the signs of all factors reversed, thus breaking the aliases between all main effects and two-factor interactions. Note: A single factor fold-over only breaks the aliases on the specific factor chosen for the fold-over. Criteria to selected a project: B/(I +C)>1
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Six Sigma Study Guide - Six Sigma Study Guide A Attribute...

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