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

Document Type : Research Paper


1 University of Missouri – Rolla, Rolla, Missouri 65409 USA

2 Lawrence Technological University, Southfield, Massachusetts 02139 USA


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 of data that is encountered with consumer vehicle ratings. MTS enables a reduction in dimensionality and the ability to develop a scale based on MD values. MTS identifies a set of useful variables from the complete data set with equivalent correlation and considerably less time and data. This paper presents the application of the Adjoint Matrix Approach to MTS for vehicle braking to identify a reduced set of useful variables in multidimensional systems.


Main Subjects

[1] Al-Otum, H.M.(2003), Morphological operators for color image processing based on Mahalanobis
distance measure, Optical Engineering, 42 (9); 2595-2606.
[2] Anandan, P., Irani M.(2002), Factorization with uncertainty, International Journal of Computer
Vision, 49 (2-3); 101-116.
[3] Asada, M. (2001), Wafer yield prediction by the Mahalanobis-Taguchi system, IEEE International
Workshop on Statistical Methodology, 6; 25-28.
[4] Garcia-Lagos, F., Joya, G., Marin, F.J., Sandoval F. (2003), Modular power system topology
assessment using Gaussian potential functions, IEEE Proceedings-Generation Transmission and
Distribution, 150 (5); 635-640.
[5] Hayashi, S., Y. Tanaka, Kodama E. (2001), A new manufacturing control system using Mahalanobis
distance for maximizing productivity, IEEE Transactions, 15 (4); 59-62.
[6] Manly, B.F.J. (1994), Multivariate Statistical Methods: A Primer; Chapman & Hall, London.
[7] Shen, H., Carter, J.F., Brereton, R.G., Eckers C. (2003), Discrimination between tablet production
methods using pyrolysis-gas chromatography-mass spectrometry and pattern recognition, Analyst,
128(3); 287-292.
[8] Taguchi, G., Jugulum R. (2002), The Mahalanobis-Taguchi strategy; John Wiley & Sons, Inc., New
York, NY.
[9] Taguchi, S.(2000), Mahalanobis-Taguchi system, ASI Taguchi Symposium, Detroit, MI.
[10] Wu, Y. (2004), Pattern recognition using Mahalanobis distance, TPD Symposium, Journal of Quality
Engineering Forum, 12 (5); 787-795.