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Reliability improvement with design of experiments
01 Jul 1993-
TL;DR: This work demonstrates how to use design of experiments for concurrent product design, process development and reliability engineering.
Abstract: Shows how to set up and operate a practical reliability programme using the design of experiments to provide the required information. Emphasizing real solutions, this work demonstrates how to use design of experiments for concurrent product design, process development and reliability engineering.
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TL;DR: In this paper, the authors use a conceptual degradation-based reliability model to describe the role of, and need for, integration of reliability data sources such as accelerated degradation testing, accelerated life testing (for materials and components), accelerated multifactor robust-design experiments and over-stress prototype testing, and the use of field data (especially early-production) to produce a robust, highreliability product and to provide a process for continuing improvement of reliability of existing and future products.
Abstract: Today's manufacturers face increasingly intense global competition. To remain profitable, they are challenged to design, develop, test, and manufacture high reliability products in ever-shorter product-cycle times and, at the same time, remain within stringent cost constraints. Design, manufacturing, and reliability engineers have developed an impressive array of tools for producing reliable products. These tools will continue to be important. However, due to changes in the way that new product-concepts are being developed and brought to market, there is need for change in the usual methods used for design-for-reliability and reliability testing, assessment, and improvement programs. This tutorial uses a conceptual degradation-based reliability model to describe the role of, and need for, integration of reliability data sources. These sources include accelerated degradation testing, accelerated life testing (for materials and components), accelerated multifactor robust-design experiments and over-stress prototype testing (for subsystems and systems), and the use of field data (especially early-production) to produce a robust, high-reliability product and to provide a process for continuing improvement of reliability of existing and future products. Manufacturers need to develop economical and timely methods of obtaining, at each step of the product design and development process, the information needed to meet overall reliability goals. We emphasize the need for intensive, effective upstream testing of product materials, components, and design concepts. >
130 citations
TL;DR: This is the bibliography referenced in the article by Wayne B Nelson titled "A bibliography of accelerated test plans," published in the IEEE Transactions on Reliability June 2005 issue.
Abstract: This is the bibliography referenced in the article by Wayne B Nelson titled "A bibliography of accelerated test plans," published in the IEEE Transactions on Reliability June 2005 issue (vol.54, no.2, ISSN 0018-9529).
109 citations
TL;DR: In this paper, the Industrial Infrastructure Program through the Korea Institute for Advancement of Technology (KIAT) grant funded by the Korea Government Ministry of Trade, Industry and Energy (Grant No. N0000502).
Abstract: This work was supported by the Industrial Infrastructure Program through the Korea Institute for Advancement of Technology (KIAT) grant funded by the Korea Government Ministry of Trade, Industry and Energy (Grant No. N0000502).
85 citations
TL;DR: The Taguchi Design of Experiments (DoEs) off-line quality control method is presented, which offers considerable benefits in time and accuracy when compared with the conventional serial approach of trial and error in the optimization of the design parameters of a neural network.
Abstract: The size and training parameters of artificial neural networks have a critical effect on their performance. This paper presents the application of the Taguchi Design of Experiments (DoEs) off-line quality control method in the optimization of the design parameters of a neural network. Being a ‘parallel’ approach, the method offers considerable benefits in time and accuracy when compared with the conventional serial approach of trial and error. The use of the Taguchi method ensures that the quality of the neural network is taken into account at the design stage. The interpretation of the experimental results is based on the statistical technique known as analysis of variance (ANOVA). The signal-to-noise ratio (S/N) is used in designing a robust neural network that is less sensitive to noise. The effect of design parameters and neural network behaviour are also revealed as a result. Although a Wood Veneer Inspection Neural Network (WVINN) is the particular application presented here, the design methodology can be applied to neural networks in general. Copyright © 2000 John Wiley & Sons, Ltd.
83 citations
TL;DR: An integrated methodology for quality & reliability improvement when degradation data are available as the response in the experiments is developed using an integrated loss function.
Abstract: Design of experiments is a useful tool for improving the quality & reliability of products. This article develops an integrated methodology for quality & reliability improvement when degradation data are available as the response in the experiments. The noise factors affecting the product are classified into two groups which led to a Brownian motion model for the degradation characteristic. A simple optimization procedure for finding the best control factor setting is developed using an integrated loss function. The methodology is illustrated with an application to a window wiper switch experiment.
82 citations
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TL;DR: In this article, a more general transformation approach is introduced for other commonly met kinds of dependence between σ y and μ y (including no dependence), and a lambda plot is presented that uses the data to suggest an appropriate transformation.
Abstract: For the analysis of designed experiments, Taguchi uses performance criteria that he calls signal-to-noise (SN) ratios. Three such criteria are here denoted by SN T , SN L , and SN S . The criterion SN T was to be used in preference to the standard deviation for the problem of achieving, for some quality characteristic y, the smallest mean squared error about an operating target value. Leon, Shoemaker, and Kacker (1987) showed how SN T was appropriate to solve this problem only when σ y was proportional to μ y . On that assumption, the same result could be obtained more simply by conducting the analysis in terms of log y rather than y. A more general transformation approach is here introduced for other, commonly met kinds of dependence between σ y and μ y (including no dependence), and a lambda plot is presented that uses the data to suggest an appropriate transformation. The criteria SN L and SN S were for problems in which the objective was to make the response as large or as small as possible. It is arg...
495 citations
TL;DR: In this paper, a graph-aided method is proposed to solve the problem of fractional factorial factorial experiment planning, where prior knowledge may suggest that some interactions are potentially important and should therefore be estimated free of the main effects.
Abstract: In planning a fractional factorial experiment prior knowledge may suggest that some interactions are potentially important and should therefore be estimated free of the main effects. In this article, we propose a graph-aided method to solve this problem for two-level experiments. First, we choose the defining relations for a 2 n–k design according to a goodness criterion such as the minimum aberration criterion. Then we construct all of the nonisomorphic graphs that represent the solutions to the problem of simultaneous estimation of main effects and two-factor interactions for the given defining relations. In each graph a vertex represents a factor and an edge represents the interaction between the two factors. For the experiment planner, the job is simple: Draw a graph representing the specified interactions and compare it with the list of graphs obtained previously. Our approach is a substantial improvement over Taguchi's linear graphs.
178 citations
27 citations