• Title/Summary/Keyword: Nonlinear Satisfaction Function

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Development of Design Evaluation Method Through Nonlinear Satisfaction Function (비선형 만족도 함수를 이용한 설계평가 방법의 개발)

  • Moon, Y.R.;Cha, S.W.
    • Proceedings of the KSME Conference
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    • 2001.06c
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    • pp.420-425
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    • 2001
  • The information content is determined by establishing the system range for each of the FRs and by determing the overlap between system range and the design range (i.e the designer-specified range). However, conventional information content doesn't include designer's intention sufficiently. In this paper, the satisfaction function is presented to embody designer's intention by calculating information contents. The satisfaction function is created in order to deal with the uncertanties involved in determining the design range and the system range in terms of a given physical parameter. So, the satisfaction function help designer to choose the optimal design among many proposed design.

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Development of Fuzzy Membership Function for Emotional Satisfaction Quantification (감성 만족도의 정량화를 위한 퍼지 소속 함수 개발)

  • Park, Jun-Seok;Myeong, No-Hae
    • Journal of the Ergonomics Society of Korea
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    • v.23 no.2
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    • pp.37-54
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    • 2004
  • Fuzzy theory provides an intelligence treatment model for judgement about information when it needs a solution or a decision making about vague problems. Therefore, fuzzy theory is used for appropriate evaluation and decision on obscure information as human's emotion in human factors, In previous study, fuzzy membership function is defined for judgement infOlmation as human's emotion then ultimate results are deducted through fuzzy inference model. This method uses general CWTent through literature review or max, min and average as representative statics value about considering variables. But, this method makes away with nonlinear's or inegular's factors of human sensibility. Accordingly, application of this method leads to considerable loss of information in the ultimate evaluation. For that reason, this method has a limitation in objective evaluation of human factors. So, this study focuses on development of fuzzy membership function, which evaluates human's emotion or feeling accurately and objectively. We used the regression analysis and reasoned a fuzzy membership function about the relation of the variables. Then we verified the adequacy with the reliability through the experiment after this.

Determining the Importance of Customer Attributes with Kano's Model (카노 모형을 고려한 고객 요구 속성의 중요도 산정)

  • Kim, Kyung-Mee O.
    • Journal of Korean Society for Quality Management
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    • v.35 no.4
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    • pp.38-51
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    • 2007
  • The House of Quality(HOQ) is used in the development stage to identify important customer attributes and corresponding engineering characteristics. The importance of each customer attribute obtained in the HOQ affects to the quality of the final product or service. Traditionally, such importance is derived based on the assumption that customer satisfaction is linearly proportional to the product performance. In this paper, we propose a nonlinear function so as to relate the product performance with the customer satisfaction according to the Kano model. A performance goal is obtained by maximizing the total customer satisfaction under a cost constraint and the importance of each customer attribute is developed from the performance goal. Therefore, the proposed approach incorporates the Kano categories and the improvement cost in determining the importance of customer attributes.

Expansion of Sensitivity Analysis for Statistical Moments and Probability Constraints to Non-Normal Variables (비정규 분포에 대한 통계적 모멘트와 확률 제한조건의 민감도 해석)

  • Huh, Jae-Sung;Kwak, Byung-Man
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.34 no.11
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    • pp.1691-1696
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    • 2010
  • The efforts of reflecting the system's uncertainties in design step have been made and robust optimization or reliabilitybased design optimization are examples of the most famous methodologies. The statistical moments of a performance function and the constraints corresponding to probability conditions are involved in the formulation of these methodologies. Therefore, it is essential to effectively and accurately calculate them. The sensitivities of these methodologies have to be determined when nonlinear programming is utilized during the optimization process. The sensitivity of statistical moments and probability constraints is expressed in the integral form and limited to the normal random variable; we aim to expand the sensitivity formulation to nonnormal variables. Additional functional calculation will not be required when statistical moments and failure or satisfaction probabilities are already obtained at a design point. On the other hand, the accuracy of the sensitivity results could be worse than that of the moments because the target function is expressed as a product of the performance function and the explicit functions derived from probability density functions.

The Efficient Sensitivity Analysis on Statistical Moments and Probability Constraints in Robust Optimal Design (강건 최적설계에서 통계적 모멘트와 확률 제한조건에 대한 효율적인 민감도 해석)

  • Huh, Jae-Sung;Kwak, Byung-Man
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.32 no.1
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    • pp.29-34
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    • 2008
  • The efforts of reflecting the system's uncertainties in design step have been made and robust optimization or reliability-based design optimization are examples of the most famous methodologies. In their formulation, the mean and standard deviation of a performance function and constraints expressed by probability conditions are involved. Therefore, it is essential to effectively and accurately calculate them and, in addition, the sensitivity results are required to obtain when the nonlinear programming is utilized during optimization process. We aim to obtain the new and efficient sensitivity formulation, which is based on integral form, on statistical moments such as the mean and standard deviation, and probability constraints. It does not require the additional functional calculation when statistical moments and failure or satisfaction probabilities are already obtained at a design point. Moreover, some numerical examples have been calculated and compared with the exact solution or the results of Monte Carlo Simulation method. The results seem to be very satisfactory.

A Study on Balanced Team Formation Method Reflecting Characteristics of Students (학생들의 특성을 반영한 균형적인 팀 편성 방법에 관한 연구)

  • Kim, Jong-hwan
    • Journal of Korea Society of Industrial Information Systems
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    • v.24 no.6
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    • pp.55-65
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    • 2019
  • With the advent of the Fourth Industrial Revolution and changes in the educational environment, team-based assignments are increasing in university classes. Effective team formation in team-based class is an important issue that affects students' satisfaction and the effectiveness of education. However, previous studies mostly focused on post analysis on the results of team formation, which makes it difficult to use them in actual classes. In this paper, we present a mathematical model of how to create a balanced team that reflects students' abilities and other characteristics. Characteristic values for assignment may be scores, such as students' proficiency, binary values such as gender, and multi-values, such as grade or department. This problem is a type of equitable partitioning problem, which takes the form of 0-1 integer programming, and the objective function is linear or nonlinear, depending on how balance is achieved. The basic model or the extended model presented can be applied to the situation where teams are balanced in consideration of various factors in actual class.