• 대한기계학회논문집A
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• 제25권12호
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• pp.1960-1965
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• 2001

In the practical design, it is important to extract the design space information of a complex system in order to optimize the design because the design contains huge amount of design conflicts in general. In this research FEA (finite element analysis) has been successfully implemented and integrated with a statistical approach such as DOE (design of experiments) based RSM (response surface model) to optimize the thermal deformation of an automotive disk brake. The DOE is used for exploring the engineer's design space and for building the RSM in order to facilitate the effective solution of multi-objective optimization problems. The RSM is utilized as an efficient means to rapidly model the trade-off among many conflicting goals existed in the FEA applications. To reduce the computational burden associated with the FEA, the second-order regression models are generated to derive the objective functions and constraints. In this approach, the multiple objective functions and constraints represented by RSM are solved using the sequential quadratic programming to archive the optimal design of disk brake.

• Communications for Statistical Applications and Methods
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• 제26권6호
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• pp.527-538
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• 2019

This paper considers the issue of obtaining the optimal design in Poisson regression model when the sample size is small. Poisson regression model is widely used for the analysis of count data. Asymptotic theory provides the basis for making inference on the parameters in this model. However, for small size experiments, asymptotic approximations, such as unbiasedness, may not be valid. Therefore, first, we employ the second order expansion of the bias of the maximum likelihood estimator (MLE) and derive the mean square error (MSE) of MLE to measure the quality of an estimator. We then define DM-optimality criterion, which is based on a function of the MSE. This criterion is applied to obtain locally optimal designs for small size experiments. The effect of sample size on the obtained designs are shown. We also obtain locally DM-optimal designs for some special cases of the model.

• 품질경영학회지
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• 제37권1호
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• pp.29-39
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• 2009

This article investigates economic-statistical design of VSSI(variable sampling size and interval) cause-selecting charts considering two assignable causes. We consider a process which is composed of two dependent sub-processes. In each sub-process, two kinds of assignable cause may exist. We propose a procedure for designing VSSI cause-selecting charts, based on Lorenzen and Vance model. Computational experiments show that the VSSI cause-selecting chart is superior to the FSSI cause-selecting chart in the economic-statistical characteristics, even under two assignable causes.

• Communications for Statistical Applications and Methods
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• 제15권1호
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• pp.125-136
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• 2008

많은 실제적인 공학 설계문제에 있어서, 목적함수의 형태는 설계변수들에 의하여 정확하게 주어지지 않는다. 이러한 환경 하에서, 구조해석, 유체 역학 해석, 열역학 분석과 같은 등과 같은 문제에서 설계변수들의 값이 주어졌을 때 목적함수들의 값은 실제 실험이나 계산상의 실험을 통하여 얻어지게 된다. 일반적으로, 이러한 실험들은 많은 비용이 든다. 이런 경우에는 실험의 횟수를 가능한 적게 하기위하여, 목적함수의 형태를 예측하는 것과 병행하여 최적화를 수행하게 된다. 반응표면분석(Response Surface Methodology, RSM)은 이러한 접근 방법에서 잘 알려져 있다. 본 논문에서는 목적함수의 예측을 위하여 서포트 벡터 기계(Support Vector Machines, SVM)의 방법을 적용할 것이다. 이러한 접근에서 가장 중요한 과제들 중의 하나는 가능한 실험의 횟수를 적게 하기 위하여 적절하게 표본자료들을 배치하는 것이다. 이러한 목적에 서포트 벡터의 정보들이 효과적으로 사용되어짐을 보이고 제안한 방법의 효율성은 공학 설계문제에서 잘 알려진 수치 예제를 통하여 보인다.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 추계학술대회 논문집
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• pp.54-59
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• 2004

A measure for good products manufactured by grinding process is the surface roughness that is affected by a lot of operating parameters such as types of abrasive, grain size, bond material, wheel speed, table speed, depth of cut, hardness of workpiece and stiffness of grinding machine. In this study, an application of the design of experiments was tried for evaluating the effect of operating parameters on the surface roughness. The workpiece was a high speed tool steel(SKH51) and the surface grinding was conducted. In order to obtain the best surface roughness within constraints of the working range, the optimal grinding conditions were selected. The usefulness of this method was evaluated by the statistical strategy.

• 품질경영학회지
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• 제34권2호
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• pp.122-128
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• 2006

One feature of a computer simulation experiment, different from a physical experiment, is that the output is often deterministic. Moreover the codes are computationally very expensive to run. This paper deals with the design and analysis of computer experiments(DACE) which is a relatively new statistical research area. We model the response of computer experiments as the realization of a stochastic process. This approach is basically the same as using a spatial linear model. Applications to the optimal mechanical designing and model calibration problems are illustrated. Algorithms for selecting the best spatial linear model are also proposed.

• Journal of the Korean Statistical Society
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• 제35권2호
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• pp.201-212
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• 2006

The technique of foldover is usually used by experimenters to de-alias the effects that are interesting in follow-up experiment. Employing a $2^{k-p}$ design with resolution III or higher, Li and Lin (2003) developed an algorithm and used computer programs to search its corresponding optimal foldover design for selected 16-run and 32-run experiments. Based on the minimum aberration criterion, the strong combined-optimal design, defined by Li and Lin, is the better choice of the initial design. In this article, we apply the technique of blocking to find the strong combined-optimal designs. Furthermore, we will tabulate all 16-run and 32-run strong combined-optimal designs and their corresponding core foldover plans for practical use. Some new designs that have not appeared in the other literature but constructed by the technique of blocking are also proposed in this article.

• Journal of Microbiology and Biotechnology
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• 제22권12호
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• pp.1767-1775
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• 2012

The Cr(VI) removal capability of Acinetobacter junii VITSUKMW2 isolated from the Sukinda chromite mine site was evaluated and enhanced using statistical design techniques. The removal capacity was evaluated at different pH values (5-11) and temperatures ($30-40^{\circ}C$) and with various carbon and nitrogen sources. Plackett-Burman design was used to select the operational parameters for bioremediation of Cr(VI). Three parameters (molasses, yeast extract, and Cr(VI) concentration) were chosen for further optimization using central composite design. The optimal combination of parameters was found to be 14.85 g/l molasses, 4.72 g/l yeast extract, and 54 mg/l initial Cr(VI), with 99.95% removal of Cr(VI) in 12 h. A. junii VITSUKMW2 was shown to have significant potential for removal of Cr(VI).

• 한국정밀공학회지
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• 제30권11호
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• pp.1179-1185
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• 2013

In this study, the design optimization of the automotive side member is performed to maximize the crash energy absorption efficiency per unit weight. Design parameters which seriously influence on the frontal crash performance are selected through the sensitivity analysis using the Plackett-Burman design method. And also the design variables, which are determined from the sensitivity analysis, are optimized by two methods. One is conventional approximate optimization method which uses the statistical design of experiments (DOE) and response surface method (RSM). The other is a methodology derived from previous work by the authors, which is called sequential design of experiments (SDOE), to reduce a trial and error procedure and to find an appropriate condition for using micro-genetic algorithm. The proposed optimization technique shows that the automotive side member structure can be designed considering the frontal crash performance.

• International Journal of Quality Innovation
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• 제3권2호
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• pp.13-28
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• 2002

Higher efficiency and effectiveness of Research & Development phases can be attained using advanced statistical methodologies. In this work statistical methodologies are combined with a deterministic approach to engineering design. In order to show the potentiality of such integration, a simple but effective example is presented. It concerns the problem of optimising the performances of a paper helicopter. The design of this simple device is not new in quality engineering literature and has been mainly used for educational purposes. Taking full advantage of fundamental engineering knowledge, an aerodynamic model is originally formulated in order to describe the flight of the helicopter. Screening experiments were necessary to get first estimates of model parameters. Subsequently, deterministic evaluations based on this model were necessary to set up further experimental phases needed to search (or a better design. Thanks to this integration of statistical and deterministic phases, a significant performance improvement is obtained. Moreover, the engineering knowledge かms out to be developed since an explanation of the “why” of better performances, although approximate, is achieved. The final design solution is robust in a broader sense, being both validated by experimental evidence and closely examined by engineering knowledge.