Statistics Spotlight


My process is too variable--now what do I do?

by Snee, Ronald D.

How to produce and use a successful multi-vari study

How to produce and use a successful multi- vari study by Ronald D. Snee Process Schematic FIGURE 1 The process Process outputs Controlled variables Customer Process inputs Uncontrolled noise variables Manufacturing Process Variables TABLE 1 Process input...

Inferences on percentage changes.

by Gunst, Richard

A popular approach to the problem of inferences on functions of averages

Q U A L I T Y P R O G R E S S I O C T O B E R 2 0 0 1 I 57 Turbine Engine Average Deposits TABLE 2 Changes from lubricant eight p- values Standard Percentage Percentage Lubricant Average deviation Difference change Difference change 1 24.89 20.11 - 26.61...

Column: Statistics Roundtable: Chicken Soup for Processes

by Hare, Lynne B.

Understanding process variation is a prerequisite to using SPC

SPC can help hold onto gains once they are attained by being used for Shewhart's originally intended purpose -- to detect the entry of assignable cause variation....

Column: Statistics Roundtable: Using degradation data for product liability analysis.

by Meeker, William Q.; Doganaksoy, Necip; Hahn, Gerald J.

A case study shows how this type of data can provide more precise results in assessing reliability

High reliability systems require individual components to have extremely high reliability for a long time. Often, the time for product development is short, imposing severe constraints on reliability testing. Traditionally, methods for the analysis of...

Statistics Roundtable: Implementing Multivariate SPC Using Hotelling's T2 Statistic

by Mason, Robert L.; Young, John C.

Multivariate statistical process control (MVSPC) can be defined as the application of multivariate statistical procedures for the purpose of increasing the quality and productivity of a business. Hotelling's T2 statistic allows you to monitor many...

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