An overview of taguchi method and newly developed statistical methods for robust design
TL;DR: In this article, the authors summarized the statistical methods for planning and analyzing robust design experiments originally proposed by Taguchi; then reviewed newly developed statistical methods and identified areas and problems where more researches are needed.
Abstract: Robust Design is an important method for improving product quality, manufacturability, and reliability at low cost. Taguchi's introduction of this method in 1980 to several major American industries resulted in significant quality improvement in product and manufacturing process design. While the robust design objective of making product performance insensitive to hard-to-control noise was recognized to be very important, many of the statistical methods proposed by Taguchi, such as the use of signal-to-noise ratios, orthogonal arrays, linear graphs, and accumulation analysis, have room for improvement. To popularize me use of robust design among engineers, it is essential to develop more effective, statistically efficient, and user-friendly tech niques and tools. This paper first summarizes the statistical methods for planning and analyzing robust design experiments originally proposed by Taguchi; then reviews newly developed statistical methods and identifies areas and problems where more resear...
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28 Sep 2014
TL;DR: This paper presents an experimental study of parameter design and tolerance design for dynamic characteristics in the context of Offline and online quality control.
Abstract: Contents: Variety and Quality. Variability loss and tolerance. Determining tolerances. Tolerance design and experimental design. Offline and online quality control. Parameter design and tolerance design: case study. Experimental design for smaller is better characteristics. Experimental design for larger is better characteristics. Bypassing the S/N ratio: spring experiment. Experimental design for dynamic characteristics.
672 citations
TL;DR: This variation embodies the integration of the Response Surface Methodology (RSM) with the compromise Decision Support Problem (DSP) and is especially useful for design problems where there are no closed-form solutions and system performance is computationally expensive to evaluate.
Abstract: In this paper, we introduce a small variation to current approaches broadly called Taguchi Robust Design Methods. In these methods, there are two broad categories of problems associated with simultaneously minimizing performance variations and bringing the mean on target, namely, Type 1-minimizing variations in performance caused by variations in noise factors (uncontrollable parameters). Type II-minimizing variations in performance caused by variations in control factors (design variables). In this paper, we introduce a variation to the existing approaches to solve both types of problems. This variation embodies the integration of the Response Surface Methodology (RSM) with the compromise Decision Support Problem (DSP). Our approach is especially useful for design problems where there are no closed-form solutions and system performance is computationally expensive to evaluate. The design of a solar powered irrigation system is used as an example.
584 citations
Cites background from "An overview of taguchi method and n..."
...3 Associate Professor, School of Industrial and Systems Engineering, Georgia Institue of Technology, Atlanta Georgia....
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13 Sep 1998
TL;DR: In this paper, a robust design procedure is developed to allow a designer to express his/her preference structure of multiple aspects of robust design, which is then used to determine the robust design solution which is guaranteed to belong to the set of efficient solutions (Pareto points).
Abstract: In robust design, associated with each quality characteristic, the design objective often involves multiple aspects such as bringing the mean of performance on target and minimizing the variations. Current ways of handling these multiple aspects using either the Taguchi's signal-to-noise ratio or the weighted-sum method are not adequate. In this paper, we solve bi-objective robust design problems from a utility perspective by following upon the recent developments on relating utility function optimization to a Compromise Programming (CP) method. A robust design procedure is developed to allow a designer to express his/her preference structure of multiple aspects of robust design. The CP approach, i.e., the Tchebycheff method, is then used to determine the robust design solution which is guaranteed to belong to the set of efficient solutions (Pareto points). The quality utility at the candidate solution is represented by means of a quadratic function in a certain sense equivalent to the weighted Tchebycheff metric. The obtained utility function can be used to explore the set of efficient solutions in a neighborhood of the candidate solution. The iterative nature of our proposed procedure will assist decision making in quality engineering and the applications of robust design.
360 citations
Cites background from "An overview of taguchi method and n..."
...Department of Mathematical Sciences Clemson University...
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...For "the nominal the better” type of problem, it was proven (Tsui, 1992) that the expected quality loss can be obtained as E [L(Y,T)]= K [σ2 + (T − µ)2 ] , (2.1) where K is the loss function coefficient, Y is the random variable of quality characteristic y, T is the target or desired value of the…...
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TL;DR: The robust design of a vibration absorber with mass and stiffness uncertainty in the main system is used to demonstrate the robust design approach in dynamics as discussed by the authors, and the results show a significant improvement in performance compared with the conventional solution.
328 citations
Cites methods from "An overview of taguchi method and n..."
...Tsui [13] showed that the Taguchi method does not necessarily find an accurate solution for design problems with highly non-linear behaviour....
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TL;DR: This paper provides a review of statistical methods that are useful in conducting computer experiments and describes approaches for the two primary tasks of metamodeling: selecting an experimental design and fitting a statistical model.
Abstract: In this paper, we provide a review of statistical methods that are useful in conducting computer experiments. Our focus is on the task of metamodeling, which is driven by the goal of optimizing a complex system via a deterministic simulation model. However, we also mention the case of a stochastic simulation, and examples of both cases are discussed. The organization of our review first presents several engineering applications, it then describes approaches for the two primary tasks of metamodeling: (i) selecting an experimental design; and (ii) fitting a statistical model. Seven statistical modeling methods are included. Both classical and newer experimental designs are discussed. Finally, our own computational study tests the various metamodeling options on two two-dimensional response surfaces and one ten-dimensional surface.
314 citations
Cites methods from "An overview of taguchi method and n..."
...This idea is related to the robust design method for improving product quality, manufacturability, and reliability at low cost (Taguchi, 1987; Nair, 1992; Tsui, 1992; 1996a, 1996b, 1997; McCaskey and Tsui, 1997)....
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References
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TL;DR: In this article, Lindley et al. make the less restrictive assumption that such a normal, homoscedastic, linear model is appropriate after some suitable transformation has been applied to the y's.
Abstract: [Read at a RESEARCH METHODS MEETING of the SOCIETY, April 8th, 1964, Professor D. V. LINDLEY in the Chair] SUMMARY In the analysis of data it is often assumed that observations Yl, Y2, *-, Yn are independently normally distributed with constant variance and with expectations specified by a model linear in a set of parameters 0. In this paper we make the less restrictive assumption that such a normal, homoscedastic, linear model is appropriate after some suitable transformation has been applied to the y's. Inferences about the transformation and about the parameters of the linear model are made by computing the likelihood function and the relevant posterior distribution. The contributions of normality, homoscedasticity and additivity to the transformation are separated. The relation of the present methods to earlier procedures for finding transformations is discussed. The methods are illustrated with examples.
12,158 citations
Book•
01 Jan 2015TL;DR: This book offers a complete blueprint for structuring projects to achieve rapid completion with high engineering productivity during the research and development phase to ensure that high quality products can be made quickly and at the lowest possible cost.
Abstract: From the Publisher:
Phadke was trained in robust design techniques by Genichi Taguchi, the mastermind behind Japanese quality manufacturing technologies and the father of Japanese quality control. Taguchi's approach is currently under consideration to be adopted as a student protocol with the US govrnment. The foreword is written by Taguchi. This book offers a complete blueprint for structuring projects to achieve rapid completion with high engineering productivity during the research and development phase to ensure that high quality products can be made quickly and at the lowest possible cost. Some topics covered are: orthogonol arrays, how to construct orthogonal arrays, computer-aided robutst design techniques, dynamic systems design methods, and more.
3,928 citations
Journal Article•
1,945 citations
Book•
01 Oct 1986
TL;DR: In this paper, a case study of variance loss and tolerance design for online and offline quality control is presented, where the S/N ratio is bypassed by a spring experiment.
Abstract: Contents: Variety and Quality. Variability loss and tolerance. Determining tolerances. Tolerance design and experimental design. Offline and online quality control. Parameter design and tolerance design: case study. Experimental design for smaller is better characteristics. Experimental design for larger is better characteristics. Bypassing the S/N ratio: spring experiment. Experimental design for dynamic characteristics.
927 citations
TL;DR: In this paper, a procedure to estimate appropriate transformations in this context is described and illustrated, and a simple functional form in transformed variables rather than with a more complicated form in the original variables is presented.
Abstract: In representing a realationship between a response and a number of independent variables, it is preferable when possible to work with a simple functional form in transformed variables rather than with a more complicated form in the original variables. This paper describes and illustrates a procedure to estimate appropriate transformations in this context.
768 citations