• 품질경영학회지
• /
• 제25권1호
• /
• pp.56-68
• /
• 1997

The object of multiresponse optimization is to determine conditions on hte independent variables that lead to optimal or nearly optimal values of the response variables. Derringer and Suich (1980) extended Harrington's (1965) procedure by introducing more general transformations of the response into desirability functions. The core of the desirability a, pp.oach condenses a multivariate optimization into a univariate one. But because of the subjective nature of this a, pp.oach, inexperience on the part of the user in assessing a product's desirability value may lead to inaccurate results. To compensate for this defect, a weighted desirability function is introduced which takes into consideration the vriances of the responses.

• Structural Engineering and Mechanics
• /
• 제63권3호
• /
• pp.303-315
• /
• 2017

This paper presents a review on getting a Weighted Multi-Objective Optimization (WMO) of Tuned Mass Damper (TMD) parameters based on Response Surface Methodology (RSM) coupled central composite design and Weighted Desirability Function (WDF) to attenuate the earthquake vibration of a jacket supported Offshore Wind Turbine (OWT). To optimize the parameters (stiffness and damping coefficient) of damper, the frequency ratio and damping ratio were considered as a design variable and the top displacement and frequency response were considered as objective functions. The optimization has been carried out under only El Centro earthquake results and after obtained the optimal parameters, more two earthquakes (California and Northridge) has been performed to investigate the performance of optimal damper. The obtained results also compared with the different conventional TMD's designed by Den Hartog's, Sadek et al.'s and Warburton's method. From the results, it was found that the optimal TMD based on RSM shows better response than the conventional damper. It is concluded that the proposed response model offers an efficient approach regarding the TMD optimization.

• 지식경영연구
• /
• 제21권1호
• /
• pp.27-40
• /
• 2020

Response surface methodology (RSM) empirically studies the relationship between a response variable and input variables in the product or process development phase. The ultimate goal of RSM is to find an optimal condition of the input variables that optimizes (maximizes or minimizes) the response variable. RSM can be seen as a knowledge management tool in terms of creating and utilizing data, information, and knowledge about a product production and service operations. In the field of product or process development, most real-world problems often involve a simultaneous consideration of multiple response variables. This is called a multiple response surface (MRS) problem. Various approaches have been proposed for MRS optimization, which can be classified into loss function approach, priority-based approach, desirability function approach, process capability approach, and probability-based approach. In particular, the loss function approach is divided into univariate and multivariate approaches at large. This paper focuses on the univariate approach. The univariate approach first obtains the mean square error (MSE) for individual response variables. Then, it aggregates the MSE's into a single objective function. It is common to employ the weighted sum or the Tchebycheff metric for aggregation. Finally, it finds an optimal condition of the input variables that minimizes the objective function. When aggregating, the relative weights on the MSE's should be taken into account. However, there are few studies on how to determine the weights systematically. In this study, we propose an interactive procedure to determine the weights through considering a decision maker's preference. The proposed method is illustrated by the 'colloidal gas aphrons' problem, which is a typical MRS problem. We also discuss the extension of the proposed method to the weighted MSE (WMSE).

• 품질경영학회지
• /
• 제27권2호
• /
• pp.218-236
• /
• 1999

The purpose of parameter design is to determine optimal settings of design parameters of a product or a process such that the performance characteristics of a product exhibit small variabilities around their target values. Taguchi made significant contributions in this area. However, his analysis of the problem focused on only one performance characteristic or response, although in product and process design, multiple characteristics are more common. The critical problem in dealing with multiple characteristics is how to compromise the conflict among the selected levels of the design parameters for each individual characteristic. In this paper, Methodology using SN ratio optimized by univariate technique is proposed and a parameter design procedure to achieve the optimal balance among several different response variables is developed. Existing case studies are solved by the proposed method and the results are compared with ones by the sum of SN ratios, the expected weighted loss, the desirability function, and EXTOPSIS model.

• 산업경영시스템학회지
• /
• 제22권50호
• /
• pp.171-181
• /
• 1999

Taguchi's robust design methodology has focus only a single characteristic or response, but the quality of most products is seldom defined by a characteristics, and is rather the composite of a family of characteristics which are often interrelated and nearly always measured in a variety of units. The multiple characteristics problem is how to compromise the conflicts among the selected levels of the design parameters for each individual characteristic. In this paper, Methodology using SN ratio optimized by univariate technique is proposed and a parameter design procedure to achive the optimal compromise among several different response variables is developed. One new case studies are solved by the proposed method and the results are compared with ones by the sum of SN ratios, the expected weighted loss, the desirability function, and EXTOPSIS model.

• 품질경영학회지
• /
• 제22권3호
• /
• pp.34-53
• /
• 1994

Taguchi's robust design methodology has focused only on a single performance characteristic or response, but the quality of most products is seldom defined by a characteristic, and is rather the composite of a family of characteristics which are often interrelated and nearly always measured in a variety of units. The multiple performance characteristics problem is how to compromise the conflicts among the selected levels of the design parameters for each individual performance characteristic. In this paper, the modified desirability function using SN ratio which can be optimized by univariate technique is proposed and a parameter design procedure to achieve the best balance among several different response variables is developed We reanalyze two existing case studies by the proposed method and compare these results with ones by the sum of SN ratios and the expected weighted loss.

• 한국구조물진단유지관리공학회 논문집
• /
• 제24권3호
• /
• pp.26-38
• /
• 2020

자기 충전형 콘크리트의 배합물 설계는 전형적인 다기준의사결정의 과정이다. 본 연구에서는 실험설계법과 반응표면법을 이용하여 SCC 배합물 전산 설계가 가능하도록 재료성능 및 비용모델을 생성하고, 요구조건을 반영한 여러 성능 사이의 상대적 중요도를 산정하여 가중 다목적 설계문제로 정식화하여 수치최적해를 계산함으로써 비용효율을 고려한 SCC최적설계를 수행하였다. 실험비용과 시간을 고려하여 SCC의 수많은 요구성능 중 압축강도, 철근충전성, 재료분리저항성, 비용정보 등을 다목적 최적화의 목적함수로 설정하였다. 재료경제성을 최적재료설계프로세스에 합리적으로 반영함으로써 경제적 콘크리트배합설계를 수행할 수 있었으며, 본 연구 결과 실험점 계획에서부터 최적해 산출에 이르는 과정을 객관적인 프로세스로 구성함으로써 콘크리트 범용 최적재료설계기술 및 전산화를 기대할 수 있다.

• 품질경영학회지
• /
• 제24권3호
• /
• pp.111-132
• /
• 1996

Taguchi's parameter design is to determine optimal settings of design parameters of a product or a process such that the characteristics of a product exhibit small variabilities around their target values. His analysis of the problem has focused only on a single characteristic or response, but the quality of most products is seldom defined by a characteristic, and is rather the composite of a great number of characteristics which are often interrelated and nearly always measured in a variety of units. The critical problem in dealing with multiple characteristics is how to compromise the conflicts among the selected levels of the design parameters for each individual characteristic. In this paper, the EXTOPSIS Model using SN ratio which can be optimized by univariate technique is proposed and a parameter design procedure to achieve the optimal compromise among several different response variables is developed. Two existing case studies are solved by the proposed method and the results are compared with ones by the sum of SN ratios, the expected weighted loss, and the desirability function.