• Title/Summary/Keyword: Optimal Experimental Design

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Optimal Design of a Washer using a Response Surface Method (반응표면분석법을 이용한 세탁기의 최적설계)

  • Han, Hyeong-Seok;Kim, Tae-Yeong;Park, Tae-Won
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.23 no.11 s.170
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    • pp.1871-1877
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    • 1999
  • An optimal design method using a response surface method for dynamic characteristics of a washer is presented. The proposed method uses the design of experiment and a computer model is used for the experiment. The value of the cost function is estimated using a computer model for each case of the design variable variation. An orthogonal array is used to obtain best cases to be considered with minimum number of experimentation. Using these experimental values, optimal design is performed using a response surface method. The method used in this paper can be applied to any complicated mechanical systems that can be modelled and analyzed by a computer program. The method is applied to the design of dynamic characteristics of a washer.

Optimal Degradation Experimental Design in Non-Linear Random Coefficients Models (비선형 확률계수모형을 고려한 최적 열화시험 설계)

  • Kim, Seong-Joon;Bae, Suk-Joo
    • Journal of Applied Reliability
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    • v.9 no.1
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    • pp.13-28
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    • 2009
  • In this paper we propose a method for designing optimum degradation test based on nonlinear random-coefficients models. We use the approximated expression of the Fisher information matrix for nonlinear random-coefficients models. We apply the simplex algorithm to the inverse of the determinant of Fisher information matrix to satisfy the D-optimal criterion. By comparison of the results from PDP degradation data, we suggest a general guideline to obtain optimum experimental design for determining inspection intervals and number of samples in degradation testing.

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Optimal Depth Calibration for KinectTM Sensors via an Experimental Design Method (실험 계획법에 기반한 키넥트 센서의 최적 깊이 캘리브레이션 방법)

  • Park, Jae-Han;Bae, Ji-Hum;Baeg, Moon-Hong
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.11
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    • pp.1003-1007
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    • 2015
  • Depth calibration is a procedure for finding the conversion function that maps disparity data from a depth-sensing camera to actual distance information. In this paper, we present an optimal depth calibration method for Kinect$^{TM}$ sensors based on an experimental design and convex optimization. The proposed method, which utilizes multiple measurements from only two points, suggests a simplified calibration procedure. The confidence ellipsoids obtained from a series of simulations confirm that a simpler procedure produces a more reliable calibration function.

Augmented D-Optimal Design for Effective Response Surface Modeling and Optimization

  • Kim, Min-Soo;Hong, Kyung-Jin;Park, Dong-Hoon
    • Journal of Mechanical Science and Technology
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    • v.16 no.2
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    • pp.203-210
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    • 2002
  • For effective response surface modeling during sequential approximate optimization (SAO), the normalized and the augmented D-optimality criteria are presented. The normalized D-optimality criterion uses the normalized Fisher information matrix by its diagonal terms in order to obtain a balance among the linear-order and higher-order terms. Then, it is augmented to directly include other experimental designs or the pre-sampled designs. This augmentation enables the trust region managed sequential approximate optimization to directly use the pre-sampled designs in the overlapped trust regions in constructing the new response surface models. In order to show the effectiveness of the normalized and the augmented D-optimality criteria, following two comparisons are performed. First, the information surface of the normalized D-optimal design is compared with those of the original D-optimal design. Second, a trust-region managed sequential approximate optimizer having three D-optimal designs is developed and three design problems are solved. These comparisons show that the normalized D-optimal design gives more rotatable designs than the original D-optimal design, and the augmented D-optimal design can reduce the number of analyses by 30% - 40% than the original D-optimal design.

Experimental Verification for Optimal Efficiency Model of Inverter-Fed Induction Motor (인버터 구동 유도 전동기의 최적 효율 모델 확인 실험)

  • 김재우;김병택;권병일
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.53 no.5
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    • pp.277-282
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    • 2004
  • The optimal design of the rotor slot for inverter-fed induction motor was performed. The purpose of the paper is to verify the optimal point by experiment. A sensitivity analysis is performed, and the models near to an optimal point are selected. In the selecting process of models, 2 design variables with high sensitivity are selected out of 5 design variables. On the basis of the selected variables, 2 models near to the optimal point are decided. The tim e-step F.E.A and the experiment are performed. Optimal point and performance improvement of the optimal mode are verified.

Exploring Integrated Design Strategies for the Optimal Use of BIM

  • Park, Hyoung-June;Lee, Ji-Hyun
    • Architectural research
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    • v.12 no.2
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    • pp.9-14
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    • 2010
  • This paper introduces an experimental design studio that explores the optimal use of current digital technologies in order to employ Building Information Modeling at the early phase of design process. Based upon the outcomes from the aforementioned studio, the paper discusses the integrated design strategies for BIM in the design process. In this paper, BIM is proposed as a design tool that increases an overal design productivity more effectively and efficiently compared to BIM as a construction tool with encouraging a design communication among different partakers in the design process.

Comparison of Experimental Design and Evolution Strategy for Optimal Design of BLDC Motor (BLDC 전동기 회전자 자극의 최적화에 대한 진화전략 및 실험적 설계기법의 상호 비교)

  • Yi, H.K.;Bae, B.H.;Woo, J.S.;Hahn, J.H.;Park, S.J.;Kwon, Y.A.
    • Proceedings of the KIEE Conference
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    • 2004.04a
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    • pp.43-45
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    • 2004
  • This paper presents the optimal design of a brushless DC motor(BLDC) keeping the average torque and cogging torque of the initial model while minimizing the volume of magnet pole. Experimental design method and evolution strategy technique are performed for the shape optimization. The presented optimal designs show the both methods have the almost same result.

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A Study on the Determination of Experimental Size of Near-orthogonal Two-level Balanced Trace Optimal Resolution-V Fractional Factorial Designs (직교성에 가까운 트레이스 최적 2-수준 Resolution-V 균형 일부실험법의 실험크기 결정에 관한 연구)

  • Kim, Sang Ik
    • Journal of Korean Society for Quality Management
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    • v.45 no.4
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    • pp.889-902
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    • 2017
  • Purpose: The orthogonality and trace optimal properties are desirable for constructing designs of experiments. This article focuses on the determination of the sizes of experiments for the balanced trace optimal resolution-V fractional factorial designs for 2-level factorial designs, which have near-orthogonal properties. Methods: In this paper, first we introduce the trace optimal $2^t$ fractional factorial designs for $4{\leq}t{\leq}7$, by exploiting the partially balanced array for various cases of experimental sizes. Moreover some orthogonality criteria are also suggested with which the degree of the orthogonality of the designs can be evaluated. And we appraise the orthogonal properties of the introduced designs from various aspects. Results: We evaluate the orthogonal properties for the various experimental sizes of the balanced trace optimal resolution-V fractional factorial designs of the 2-level factorials in which each factor has two levels. And the near-orthogonal 2-level balanced trace optimal resolution-V fractional factorial designs are suggested, which have adequate sizes of experiments. Conclusion: We can construct the trace optimal $2^t$ fractional factorial designs for $4{\leq}t{\leq}7$ by exploiting the results suggested in this paper, which have near-orthogonal property and appropriate experimental sizes. The suggested designs can be employed usefully especially when we intend to analyze both the main effects and two factor interactions of the 2-level factorial experiments.

Topology Design Optimization and Experimental Validation of Heat Conduction Problems (열전도 문제에 관한 위상 최적설계의 실험적 검증)

  • Cha, Song-Hyun;Kim, Hyun-Seok;Cho, Seonho
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.28 no.1
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    • pp.9-18
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    • 2015
  • In this paper, we verify the optimal topology design for heat conduction problems in steady stated which is obtained numerically using the adjoint design sensitivity analysis(DSA) method. In adjoint variable method(AVM), the already factorized system matrix is utilized to obtain the adjoint solution so that its computation cost is trivial for the sensitivity. For the topology optimization, the design variables are parameterized into normalized bulk material densities. The objective function and constraint are the thermal compliance of the structure and the allowable volume, respectively. For the experimental validation of the optimal topology design, we compare the results with those that have identical volume but designed intuitively using a thermal imaging camera. To manufacture the optimal design, we apply a simple numerical method to convert it into point cloud data and perform CAD modeling using commercial reverse engineering software. Based on the CAD model, we manufacture the optimal topology design by CNC.

The Optimal Design Method of the Train Repair Facility based on the Simulation (시뮬레이션을 이용한 철도 정비 시설의 최적 설계 방법)

  • Um, In-Sup;Cheon, Hyeon-Jae;Lee, Hong-Chul
    • Journal of the Korean Society for Railway
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    • v.10 no.3 s.40
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    • pp.306-312
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    • 2007
  • This paper presents the optimal design method of the train repair facility based on the simulation analysis. The train is divided into the power car, motorized car and passenger car for the simulation process analysis and train repair facility is composed of each subsystems such as a blast, dry and wash workshop. In simulation analysis, we consider the critical (dependent) factors and design (independent) factors for the optimal design. Therefore, a simulation optimization uses Evolution Strategy (ES) in order to find the optimal design factors. Experimental results indicate that simulation design factors are sufficient to satisfy the conditions of dependent variables. The proposed analysis method demonstrates that simulation design factors determined by the simulation optimization are appropriate for real design factors in a real situation and the accuracy and confidence for the simulation results are increased.