Measurement System Error Analysis: Analyzing and Reducing Measurement Errors In Test Systems

Peralta, Mike

  • 出版商: Createspace Independent Publishing Platform
  • 出版日期: 2012-02-15
  • 售價: $1,400
  • 貴賓價: 9.5$1,330
  • 語言: 英文
  • 頁數: 208
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1470054051
  • ISBN-13: 9781470054052
  • 相關分類: 工程數學 Engineering-mathematics理工類
  • 無法訂購

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商品描述

The goal of this book is to carefully define and derive the statistical relationships relevant to the errors that do and can occur in measurement systems. The emphasis is on test systems employed in manufacturing. However, the statistical techniques presented are general and can be applied to any field of science, engineering, or any field which employs the mathematics of statistics to gather and analyze information.

As will be explained throughout this book, knowing the statistics of measurement error for test equipment will allow us to know and improve test accuracy and precision, which in turn, will allow us to greatly improve: Product Quality, Test Productivity, and Product Yields.

The center of this work is the "Test Capability Study" this is a spreadsheet based analysis that can quickly be set up and give an estimate of the overall uncertainty of a measurement based on a sampling of test systems or test configurations. The "Test Capability Study" is a streamlined and more efficient form of the "Gage R & R Study."

Also covered is the "Propagation of Errors" (POE) analysis to first and second order. The first order POE is commonly treated in many fine books, but the second order POE is rarely treated. For those familiar with first order POE I think you will find it a real treat to study the second order POE as it will help you get a deeper and more accurate understanding of POE.

As well as treating measurement errors, second order POE can accurately analyze variation contributions to product distributions as well as other variations in physical systems that can be defined mathematically.

作者簡介

This book was developed by Mike Peralta (Ph.D.), Semiconductor Device Modeling Engineer. His main research interest has been in the statistics of semiconductor devices. Before his position as Device Modeling Engineer (1997-2006 at Burr-Brown/Texas Instruments) he was with the Quality Department at Burr-Brown from 1982 to 1997 where he was involved with test development, statistical training, design of experiments training, test statistics development and training, and mathematical and database software development. (Burr-Brown merged with Texas Instruments in 2000.) From 2006 to 2012 he has been with Medtronic in Tempe, Arizona - also as a Semiconductor Device Modeling Engineer where he has continued to help model semiconductor models as well as developing high precision mismatch characterization and modeling techniques. Mike holds a Ph.D. in Physics (1999) from the University of Arizona. He also holds a B.S. in Math/Statistics (1990), a B.S. in Physics (1990), and a B.S.E.E.(1985), all from the University of Arizona.