Multi-Vari Analysis

by Mario Perez-Wilson

Multi-Vari is the perfect tool to determine where variability comes from in your process (lot-to-lot, shift-to-shift, machine-to-machine, etc.), because it does not require manipulating the independent variables (or process parameters) as you would with design of experiments.

Once you have determined where the major source of variability comes from, then you target your experimental designs (DOE) more efficiently to reduce that particular source of variation.

Book Description	Benefits
Multi-Vari Chart and Analysis is the first book that describes how to compute a standard deviation (or variance) for each source of variability in your process. This is accomplished by statistically analyzing Multi-Vari chart data, using analysis of variance and variance decomposition. Multi-Vari charting is presented as a pre-experimentation technique designed to isolate and quantify the major components of variability in production processes, including vendors' and suppliers' processes.	Follow a step-by-step approach to construct Multi-Vari charts, to implement them and to analyze their data statistically. Learn how to uncover the major sources of variability of your suppliers' and vendors' data using Multi-Vari Statistical Analysis. Discover the components of variation in your process and quantify the different sources: Within shift Between shift Shift-to-shift Lot-to-lot Within lot Machine-to-machine Within operator Operator-to-operator Between operators etc...

Availability	Table of Contents
Pages: 98 Current Edition: 2014 ISBN: 1-883237-01-7 Available with seminar attendance	Introduction Multi-Vari Chart Description Family of Variation Positional Variation Cyclical Variation Temporal Variation Construction of a Multi-Vari Chart Determining the Limits of Variation Determining the Sampling Scheme Graphing the Ranges Analyzing the Chart Statistical Analysis of Multi-Vari Charts Estimating Positional Variation Estimating Cyclical Variation Estimating Temporal Variation Analysis of Variance of Multi-Vari Charts Across Time Sum of Squares Between Piece Sum of Squares Within Piece Sum of Squares Components of Variation Expected Mean Square Computation Case Studies Computer Manufacturer Fuel Injection Manufacturer Medical Product Manufacturer Appendix Statistical Tables References Index
Factum
Multi-Vari is not a Dorian Shainin technique as many believe, it was first developed by Leonard Seder back in 1950. The tool was always used as a chart, until this book, which described for the first time how to breakdown the data and quantify and isolate each variance statistically.

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