Kenneth M. Ragsdell

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 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.

A Comparison Study of Mahalanobis-Taguchi System and Neural Network for Multivariate Pattern Recognition

The Mahalanobis-Taguchi System is a diagnosis and predictive method for analyzing patterns in multivariate cases. The goal of this study is to compare the ability of the Mahalanobis-Taguchi System and a neural network to discriminate using small data sets. We examine the discriminant ability as a function of data set size using an application area where reliable data is publicly available. The study uses the Wisconsin Breast Cancer study with nine attributes and one class.Copyright

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. 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 Mahalanobis-Taguchi System and its application to identify a reduced set of useful variables in multidimensional systems.Copyright

Applying the Mahalanobis-Taguchi System to Vehicle Handling

The Mahalanobis-Taguchi system (MTS) is a diagnosis and forecasting method using multivariate data. Mahalanobis distance (MD) is a measure based on correlations between the variables and patterns that can be identified and analyzed with respect to a base or reference group. The MTS is of interest because of its reported accuracy in forecasting using 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 article presents the application of the MTS, its applicability in identifying a reduced set of useful variables in multidimensional systems, and a comparison of results with those obtained from a standard statistical approach to the problem.

An Approach Toward Integrating Top-Down and Bottom-Up Product Concept and Design Selection

This paper proposes an approach to integrate top-down and bottom-up procedures for product concept and design selection. The top-down procedure identifies relationships between product requirements and design parameters and specifies an acceptable range of design parameters (called a design range) from product specifications and tolerances. Then, within the design range, the bottom-up procedure optimizes design specifications and tolerances in order to minimize a product cost. A product cost is defined as a sum of component costs, each of which is a function of design specifications and tolerances. A concept, with design specifications and tolerances, that minimizes product cost is an optimunt concept. The proposed approach is demonstrated using an illustrative example. Sensitivity analysis with respect to the parameters of the product cost illustrates that the shape of design range defines how responsive a product is to uncertainty in cost function parameters relevant to design tolerances.

Forecasting Consumer Satisfaction for Vehicle Ride Using the Mahalanobis-Taguchi Gram-Schmidt Technique

Abstract: Consumers assess and perceive quality and performance at the vehicle level, but important cost-effective decisions at the sub-system or component level must be made by the producer in order to economically satisfy consumer needs by providing affordable products. Consumers evaluate vehicle attributes such as ride, handling, roominess, braking, and acceleration. These vehicle level attributes are influenced by factors at all levels of the vehicle architecture, and these factors are often correlated. The goal of this research is to efficiently forecast consumer satisfaction measured as a function of available vehicle level performance data. This article presents the application of the Mahalanobis-Taguchi Gram-Schmidt technique to identify a reduced set of useful variables for vehicle ride.

A Top-Down Concept Selection Integrating Analytical and Optimization Approaches

This paper proposes a top-down approach for product concept selection. The proposed approach integrates an analytical approach to define an acceptable part specification range (part range), and an optimization approach to find optimum tolerances of part specifications. In the analytical part of the procedure, an inverse of design matrix is used to identify a part range. In the optimization part of the procedure, a product cost is defined as a function of part specification tolerances, and optimization algorithm is used to find optimum part specification tolerances that minimize the cost of the concept. The concept with the minimum cost is selected as the optimum concept. The usefulness of the proposed approach is demonstrated using an illustrative example.Copyright

Customer Expectation and Warranty Cost — Nominal-the-Best Case

A fixed target, be it at zero or infinity, is assumed in Taguchis method for formulating the quality loss function (QLF). The QLF only accounts for immediate issues within manufacturing facilities whereas warranty cost occurs during customer use. Variable customer expectation has not been considered in the Taguchi methodology. This article presents a methodology to predict warranty probability, the probability of customer complaint, on the basis of two independent variables; product performance and consumer expectation. It is expected that the formulation presented will serve as a basic model for predicting warranty loss using warranty probability due to a single characteristic under certain assumptions. The nominal-the-best case is considered in this article and warranty cost is estimated for an automotive example to demonstrate the methodology.

Design and Simulation of Computer Business Model for Primary Processing of Hardwood Material

Computer business model of hardwood production gives the user an opportunity to examine different ways and provide the capability of executing scenarios using alternative activities and process flow paths. This paper illustrates the design of business model based on which the simulation will be built. It will be able to simulate the effect of variables in each process and provide the output in terms of cost, quality and quantity of timber products produced at the end of primary hardwood processing. The simulation will act as a powerful decision making tool and be user friendly. It will be built with the combination of Visual Basic.NET and Microsoft Excel. It will provide cost and revenue estimates, identifies process issues and will have the capability to rapidly react to changing markets. The simulation will also be able to study the viability of capturing more product value and reducing production cost.Copyright