User manual SAS JMP QUALITY AND RELIABILITY METHODS

[. . . ] Quality and Reliability Methods Get the Most from JMP® Whether you are a first-time or a long-time user, there is always something to learn about JMP. Visit JMP. com and to find the following: · · · · · · live and recorded Webcasts about how to get started with JMP video demos and Webcasts of new features and advanced techniques schedules for seminars being held in your area success stories showing how others use JMP a blog with tips, tricks, and stories from JMP staff a forum to discuss JMP with other users http://www. jmp. com/getstarted/ Release 9 Quality and Reliability Methods "The real voyage of discovery consists not in seeking new landscapes, but in having new eyes. " Marcel Proust JMP, A Business Unit of SAS SAS Campus Drive Cary, NC 27513 The correct bibliographic citation for this manual is as follows: SAS Institute Inc. JMP® 9 Quality and Reliability Methods Copyright © 2010, SAS Institute Inc. , Cary, NC, USA ISBN 978-1-60764-594-8 All rights reserved. For a hard-copy book: No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, or otherwise, without the prior written permission of the publisher, SAS Institute Inc. [. . . ] 184 Chapter 7 Variability Charts Variability Charts 161 Variability Charts A variability chart is built to study how a measurement varies across categories. Along with the data, you can view the mean, range, and standard deviation of the data in each category. The analysis options assume that the primary interest is how the mean and variance change across the categories. A variability chart has the response on the y-axis and a multilevel categorized x-axis. The body of the chart can have the features illustrated in Figure 7. 2. Figure 7. 2 Example of a Variability Chart points with range bars group means cell means lines connecting cell means Launch the Variability Platform The Variability /Gauge Chart command on the Graph menu displays the Variability Chart Launch dialog shown in Figure 7. 3. You specify the classification columns that group the measurements in the X, Grouping list. If the factors form a nested hierarchy, specify the higher terms first. If you specify more than one Y column, there will be a separate variability chart for each response. Specifying a standard or reference column that contains the "true" or known values for the measured part enables the Bias and Linearity Study options. Both of these options perform analysis on the differences between the observed measurement and the reference or standard value. The following example uses 2 Factors Crossed. jmp, found in the Variability Data folder. 162 Variability Charts Variability Charts Chapter 7 Figure 7. 3 The Variability/Gauge Chart Launch Dialog Chart Type allows you to choose between a variability gauge analysis (for a continuous response) and an attribute gauge analysis (for a categorical response, usually "pass" or "fail"). For details on attribute gauge analysis, see "Attribute Gauge Charts, " p. 178. Model Type allows you to choose the model type (Main Effect, Crossed, Nested, etc. ). Options allows you to specify the method for computing variance components (for more details see "Variance Component Method, " p. 169), and the alpha level used by the platform. Variability Chart When you complete the Launch dialog and click OK, the variability chart and the standard deviation chart shown in Figure 7. 4 appear by default. This variability chart shows three measurements taken by each operator for parts numbered 1 to 10, with maximum and minimum bars to show the range of measurements. The standard deviation chart plots the standard deviation of measurements taken on each part by each operator. Chapter 7 Variability Charts Variability Charts 163 Figure 7. 4 Variability Charts for Two-Factors Crossed Data Note: In other platforms, if a row is excluded, it still appears on a chart or plot. But, on variability charts, excluded rows are not shown on the charts. If all the data in a combination of X, Grouping variables is excluded, then that combination does not appear on the Variability Chart or Std Dev Chart. Variability Platform Options The platform popup menu lets you modify the appearance of the chart, perform Gauge R&R analysis and compute variance components. Vertical Charts toggles between horizontal layout and vertical layout. Show Range Bars shows the bar from the minimum to the maximum of each cell. Show Cell Means shows the mean mark for each cell. Show Separators shows the separator lines between levels of the X, Grouping variables. shows the mean for groups of cells as a horizontal solid line. Show Group Means 164 Variability Charts Variability Charts Show Grand Mean shows the overall mean as a gray dotted line across the whole graph. [. . . ] (1962), "Sequential Application of Simplex Designs in Optimization and Evolutionary Operation, " Technometrics 4, 441­461. References 317 Stevens, J. P. (1979), "Comment on Olson: Choosing a Test Statistic in Multivariate Analysis of Variance, " Psychological Bulletin, 86, 355­360. (1986), Applied Multivariate Statistics for the Social Sciences, New Jersey: Laurence Erlbaum Associates. "Additive Splines in Statistics, " In Proceedings of the Statistical Computing Section, 45-48, Amer. [. . . ]