A Comparison of the Mahalanobis-Taguchi System to A Standard Statistical Method for Defect Detection

Authors

  • David Drain Missouri University of Science and Technology, Rolla, Missouri 65409 USA
  • Elizabeth A. Cudney Missouri University of Science and Technology, Rolla, Missouri 65409 USA
  • Kioumars Paryani Lawrence Technological University, Southfield, Michigan, 48075 USA
  • Naresh Sharma Missouri University of Science and Technology, Rolla, Missouri 65409 USA
Abstract:

The Mahalanobis-Taguchi System is a diagnosis and forecasting method for multivariate data. Mahalanobis distance is a measure based on correlations between the variables and different patterns that can be identified and analyzed with respect to a base or reference group. This paper presents a comparison of the Mahalanobis-Taguchi System and a standard statistical technique for defect detection by identifying abnormalities. The objective of this research is to provide a method for defect detection with acceptable alpha (probability of type I) and beta (probability of type II) errors.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

the innovation of a statistical model to estimate dependable rainfall (dr) and develop it for determination and classification of drought and wet years of iran

آب حاصل از بارش منبع تأمین نیازهای بی شمار جانداران به ویژه انسان است و هرگونه کاهش در کم و کیف آن مستقیماً حیات موجودات زنده را تحت تأثیر منفی قرار می دهد. نوسان سال به سال بارش از ویژگی های اساسی و بسیار مهم بارش های سالانه ایران محسوب می شود که آثار زیان بار آن در تمام عرصه های اقتصادی، اجتماعی و حتی سیاسی- امنیتی به نحوی منعکس می شود. چون میزان آب ناشی از بارش یکی از مولفه های اصلی برنامه ...

15 صفحه اول

Applying the Mahalanobis-Taguchi System to Vehicle Ride

The Mahalanobis Taguchi System is a diagnosis and forecasting method for multivariate data. Mahalanobis distance is a measure based on correlations between the variables and different patterns that can be identified and analyzed with respect to a base or reference group. The Mahalanobis Taguchi System is of interest because of its reported accuracy in forecasting small, correlated data sets. Th...

full text

Mahalanobis-Taguchi System-based criteria selection for strategy formulation: a case in a training institution

The increasing complexity of decision making in a severely dynamic competitive environment of the universe has urged the wise managers to have relevant strategic plans for their firms. Strategy is not formulated from one criterion but from multiple criteria in environmental scanning, and often, considering all of them is not possible. A list of criteria utilizing Delphi was selected by consu...

full text

Modeling A Design System Using the Mahalanobis Taguchi System

This work presents a novel algorithm, the MTS algorithm, which offers the Mahalanobis Taguchi System (MTS) method for parameter selections which are adjusted under a product parameter design. The utility of the algorithm is assessed how individual product parameter dimensions are selected and it can be used to focus on design system (DS) and to identify product architecture dimensions that are ...

full text

Identifying Useful Variables for Vehicle Braking Using the Adjoint Matrix Approach to the Mahalanobis-Taguchi System

The Mahalanobis Taguchi System (MTS) is a diagnosis and forecasting method for multivariate data. Mahalanobis distance (MD) is a measure based on correlations between the variables and different patterns that can be identified and analyzed with respect to a base or reference group. MTS is of interest because of its reported accuracy in forecasting small, correlated data sets. This is the type o...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 2  issue 4

pages  250- 258

publication date 2009-01-01

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023