• Journal of Integrative Natural Science
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• v.14 no.3
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• pp.73-77
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• 2021

Robust design is an approach to reduce the performance variation of mutiple responses in products and processes. In fact, in many experimental designs require the simultaneous optimization of multiple responses. In this paper, we propose how to simultaneously optimize multiple responses for robust design when data are collected from a combined array. The proposed method is based on the quadratic loss function. An example is illustrated to show the proposed method.

• Journal of the Korean Statistical Society
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• v.20 no.2
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• pp.147-155
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• 1991

This paper treats a robust design criterion which minimizes the effects of outliers and model inadequacy, and investigates robust designs for some response surface designs. In order to develop a robust design criterion and robust design, the integrated mean squared error of *(equation omitted) over a region is utilized, where *(equation omitted). is the estimated response by the minimum bias estimation proposed by carson, Manson and Hader (1969) . According to the number of aberrant observations and their positions, the proposed criterion and designs are studied. Also further development of the proposed criterion is treated when outliers can occur in any position of a design.

• Journal of Korean Society for Quality Management
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• v.31 no.4
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• pp.239-246
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• 2003

Dynamic robust design has been regarded as the most powerful design methodology for improving product quality, Dynamic SN ratio adopted in dynamic robust design combines two major quality attributes, the variability around the linear function and the slope of the linear function, into a single design metric. The principal shortcoming associated with the dynamic SN ratio is that the metric is independent of designer's preferences for the quality attributes due to priori sets of attribute tradeoff values inherent in it. Therefore, a more rigorous preference­based design metric to accurately capture designer's intent and preference is needed. A new design metric that can be used in dynamic robust design is proposed. The effectiveness of the proposed design metric is examined with the aid of a demonstrative case study and the results are discussed.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.12
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• pp.92-99
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• 2021

The ever-growing demand for enhanced competitiveness of engineered systems require designing in quality strategies that can efficiently incorporate multiple design attributes into a system. In a robust design, there must be consideration for any uncontrollable factors that should not be disregarded in the design process. Studies on multi-attribute design challenges usually assume mutual utility independence amongst the design attributes. However, mutual utility independence does not exist in every design situation. In this study, a new robust design methodology that has two utility-dependent attributes are presented. The proposed method was then compared with a traditional robust design that utilizes a wave soldering process design. The results of this case study indicate that the proposed method yields a better solution than the traditional method.

• Journal of Mechanical Science and Technology
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• v.20 no.8
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• pp.1169-1182
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• 2006

Robust design technology has been applied to versatile engineering problems to ensure consistency in product performance. Since 1980s, the concept of robust design has been introduced to numerical optimization field, which is called the robust optimization. The robustness in the robust optimization is determined by a measure of insensitiveness with respect to the variation of a response. However, there are significant difficulties associated with the calculation of variations represented as its mean and variance. To overcome the current limitation, this research presents an implementation of the approximate statistical moment method based on kriging metamodel. Two sampling methods are simultaneously utilized to obtain the sequential surrogate model of a response. The statistics such as mean and variance are obtained based on the reliable kriging model and the second-order statistical approximation method. Then, the simulated annealing algorithm of global optimization methods is adopted to find the global robust optimum. The mathematical problem and the two-bar design problem are investigated to show the validity of the proposed method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.7
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• pp.1234-1242
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• 2003

In this paper we present a simple and efficient robust optimal design formulation for MEMS structures and its application to a resonant-type micro probe. The basic idea is to use the gradient index (GI) to improve robustness of the objective and constraint functions. In the robust optimal design procedure, a deterministic optimization for performance of MEMS structures is followed by design sensitivity analysis with respect to uncertainties such as fabrication errors and change of operating conditions. During the process of deterministic optimization and sensitivity analysis, dominant performance and uncertain variables are identified to define GI. The GI is incorporated as a term of objective and constraint functions in the robust optimal design formulation to make both performance and robustness improved. While most previous approaches for robust optimal design require statistical information on design variations, the proposed GI based method needs no such information and therefore is cost-effective and easily applicable to early design stages. For the micro probe example, robust optimums are obtained to satisfy the targets for the measurement sensitivity and they are compared in terms of robustness and production yield with the deterministic optimums through the Monte Carlo simulation. This method, although shown for MEMS structures, may as well be easily applied to conventional mechanical structures where information on uncertainties is lacking but robustness is highly important.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.8
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• pp.1426-1435
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• 2003

Design goal is to find the one that has the highest probability of success and the smallest variation. A robustness index has been proposed to satisfy these conditions. The two-step optimization process of the target problem requires a scaling factor. The search process of a scaling factor is replaced with the making of the decoupled design between the mean and the standard deviation. The decoupled design matrix is formed from the sensitivity or the sum of squares. After establishing the design matrix, the robust design process has a new three-step one. The first is ″reduce variability,″ the second is ″make the candidate designs that satisfy constraints and move the mean on the target,″ and the final is ″select the best robust design using the proposed robustness index.″ The robust design process is verified by three examples and the results using the robustness index are compared with those of other indices.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.5
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• pp.351-360
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• 2013

Taguchi's robust design is a method for quality improvement by making a system insensitive to uncontrollable variations incurred by noise factors and it has received much attention in a wide range of engineering fields. Robust design can be broadly classified into static and dynamic ones. This paper is concerned with dynamic robust design. Taguchi suggested to use a signal-to-noise ratio as a robustness measure, but there has been much debate and criticism on its blind use. In order to cope with this drawback, many alternatives have been proposed. They are divided into performance measure modeling (PMM) and response function modeling (RFM) approaches. In this paper, both PMM and RFM approaches for dynamic robust design are reviewed. An example for illustration is provided as well.

• Korean Journal of Computational Design and Engineering
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• v.15 no.5
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• pp.325-332
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• 2010

A lens system for mobile phone cameras is comprised of various lenses and designed so as to satisfy design requirements for responses such as a modular transfer function (MTF). However, it is difficult to manufacture and assemble camera modules to maintain the same performance compared with the designed camera modules, because of uncertainty. We should always design a lens system by considering uncertainty that can be caused by errors in the manufacturing and assembly process of mobile phone cameras. The robust optimization offers tools of making robust decisions with the consideration of design parameters, uncontrollable parameters, and the variance of the system. Using an efficient reliability analysis method and an optimization algorithm, we obtained robust optimization results that maximize the mean of MTF and minimize the standard deviation and proposed a new robust design process for a lens system.

• Nuclear Engineering and Technology
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• v.37 no.2
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• pp.139-150
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• 2005

A robust control design procedure for a nuclear reactor has been developed and experimentally validated on the Penn State TRIGA research reactor. The utilization of the robust controller as a component of an autonomous control system is also demonstrated. Two methods of specifying a low order (fourth-order) nominal-plant model for a robust control design were evaluated: 1) by approximation based on the 'physics' of the process and 2) by an optimal Hankel approximation of a higher order plant model. The uncertainty between the nominal plant models and the higher order plant model is supplied as a specification to the ,u-synthesis robust control design procedure. Two methods of quantifying uncertainty were evaluated: 1) a combination of additive and multiplicative uncertainty and 2) multiplicative uncertainty alone. The conclusions are that the optimal Hankel approximation and a combination of additive and multiplicative uncertainty are the best approach to design robust control for this application. The results from nonlinear simulation testing and the physical experiments are consistent and thus help to confirm the correctness of the robust control design procedures and conclusions.