• Title, Summary, Keyword: response surface analysis

Search Result 1,572, Processing Time 0.053 seconds

Design Optimization of Bolted Connection with Wood Laminated Composite Beams Subjected to Distributed Loads (분포하중을 받는 목재 적층복합재 빔의 볼트 체결 최적화 설계)

  • Cho, Hee Keun
    • Journal of The Korean Society of Manufacturing Technology Engineers
    • /
    • v.26 no.3
    • /
    • pp.292-298
    • /
    • 2017
  • Numerical analysis for various design parameters should be preceded by optimal design of composite materials. Numerous studies have been conducted on the bolting of interconnecting beams. In this study, the response surface method was applied to optimize the design of bolted joints connected by laminated wood composite beams. The response surface was created by combining the FEA code for composite analysis and the algorithm for forming the response surface. Optimization on this response surface was performed with a genetic algorithm to derive the results. The determination of the optimum bolt-hole position for the connection of composite beams is an optimization problem. Tsai-Wu composite failure index, maximum deflection, and simple von Mises stress are set as the objective functions. It has been proved that the design results of the optimized bolt-hole are superior to the design performance of the existing conventional bolt-hole position.

A Study on Process Optimization Using Partial Least Squares Response Surface Function (편최소제곱 반응표면함수를 이용한 공정 최적화에 관한 연구)

  • Park, Sung-Hyun;Choi, Um-Moon;Park, Chang-Soon
    • Journal of the Korean Society for Quality Management
    • /
    • v.27 no.2
    • /
    • pp.237-250
    • /
    • 1999
  • Response surface analysis has been a popular tool conducted by engineers in many processes. In this paper, response surface function, named partial least squares response surface function is proposed. Partial least squares response surface function is a function of partial least squares components and the response surface modeling is used in either a first-order or a second-order model. Also, this approach will have the engineers be able to do the response surface modeling and the process optimization even when the number of experimental runs is less than the number of model parameters. This idea is applied to the nondesign data and an application of partial least squares response surface function to the process optimization is considered.

  • PDF

Optimization of Ultrasonic Imprinting Using the Response Surface Method (반응표면법을 이용한 초음파 임프린팅 공정의 최적화)

  • Jung, W.S.;Cho, Y.H.;Park, K.
    • Transactions of Materials Processing
    • /
    • v.22 no.1
    • /
    • pp.36-41
    • /
    • 2013
  • The present study examines the micro-pattern replication on a plastic film using ultrasonic imprinting. Ultrasonic imprinting uses ultrasonic waves to generate repetitive microscale deformation in the polymer film. The resulting deformation heat on the surface of the film causes the surface region to soften sufficiently so that a replication of the micro-pattern can be obtained. To successfully replicate the micro-pattern on a large area of polymer film, a high replication ratio is needed as well as good uniformity over the entire region. In this study, a horn design is investigated by finite element analysis and is optimized through a response surface analysis. In the ultrasonic imprinting experiments, the response surface method was also used to determine the optimal processing conditions for better replication characteristics.

A Study on the Forging of wheel Bearing Hub by using Response Surface Methodology (반응표면분석법을 이용한 휠 베어링 허브 단조에 관한 연구)

  • Song, Yo-Sun;Yeo, Hong-Tae;Hur-Kwan-Do
    • Journal of the Korean Society for Precision Engineering
    • /
    • v.22 no.8
    • /
    • pp.100-107
    • /
    • 2005
  • The objective of the study is to improve the quality of wheel bearing hub by the rigid-plastic finite element analysis and the response surface methodology. The rigid-plastic finite element codes, AFDEX-2D and DEFORM-3D, were used to analyze the two-dimensional and three-dimensional forging processes, respectively. The response surface analysis is used to find the minimum underfill by the variation of design variables such as the height of billet after upsetting and punch angles of blocker dies. The metal flow of forged product shows good agreement with the results from 2D and 3D analysis. Also, the quality of the wheel bearing hub has been improved by the optimization of design variables and the machining time has been reduced by the machining allowance.

An efficient Reliability Analysis Method Based on The Design of Experiments Augmented by The Response Surface Method (실험계획법과 반응표면법을 이용한 효율적인 신뢰도 기법의 개발)

  • 이상훈;곽병만
    • Proceedings of the Korean Society of Precision Engineering Conference
    • /
    • /
    • pp.700-703
    • /
    • 2004
  • A reliability analysis and design procedure based on the design of experiment (DOE) is combined with the response surface method (RSM) for numerical efficiency. The procedure established is based on a 3$^n$ full factorial DOE for numerical quadrature using explicit formula of optimum levels and weights derived for general distributions. The full factorial moment method (FFMM) shows good performance in terms of accuracy and ability to treat non-normally distributed random variables. But, the FFMM becomes very inefficient because the number of function evaluation required increases exponentially as the number of random variables considered increases. To enhance the efficiency, the response surface moment method (RSMM) is proposed. In RSMM, experiments only with high probability are conducted and the rest of data are complemented by a quadratic response surface approximation without mixed terms. The response surface is updated by conducting experiments one by one until the value of failure probability is converged. It is calculated using the Pearson system and the four statistical moments obtained from the experimental data. A measure for checking the relative importance of an experimental point is proposed and named as influence index. During the update of response surface, mixed terms can be added into the formulation.

  • PDF

An improved response surface method for reliability analysis of structures

  • Basaga, Hasan Basri;Bayraktar, Alemdar;Kaymaz, Irfan
    • Structural Engineering and Mechanics
    • /
    • v.42 no.2
    • /
    • pp.175-189
    • /
    • 2012
  • This paper presents an algorithm for structural reliability with the response surface method. For this aim, an approach with three stages is proposed named as improved response surface method. In the algorithm, firstly, a quadratic approximate function is formed and design point is determined with First Order Reliability Method. Secondly, a point close to the exact limit state function is searched using the design point. Lastly, vector projected method is used to generate the sample points and Second Order Reliability Method is performed to obtain reliability index and probability of failure. Five numerical examples are selected to illustrate the proposed algorithm. The limit state functions of three examples (cantilever beam, highly nonlinear limit state function and dynamic response of an oscillator) are defined explicitly and the others (frame and truss structures) are defined implicitly. ANSYS finite element program is utilized to obtain the response of the structures which are needed in the reliability analysis of implicit limit state functions. The results (reliability index, probability of failure and limit state function evaluations) obtained from the improved response surface are compared with those of Monte Carlo Simulation, First Order Reliability Method, Second Order Reliability Method and Classical Response Surface Method. According to the results, proposed algorithm gives better results for both reliability index and limit state function evaluations.

Analysis and Optimization of Grinding Condition by Response Surface Model (반응표면모델(RSM)에 의한 평면연삭조건 최적화 및 평가)

  • Kim S.O.;Kwak J.S.;Koo Y.;Sim S.B.;Jeong Y.D.;Ha M.K.
    • Proceedings of the Korean Society of Precision Engineering Conference
    • /
    • /
    • pp.1257-1260
    • /
    • 2005
  • Grinding process has unique characteristics compared with other machining processes. The cutting edges of the grinding wheel don't have uniformity and act differently on the workpiece at each grinding. The response surface analysis is one of various methods for optimizing and evaluating the process parameters to achieve the desired output. In this study, the effect of the grinding parameters on outcomes of the surface grinding was analyzed experimently. To predict the grinding outcomes and to select the grinding conditions before grinding, the second-order response surface models for the grinding force and the surface roughness were developed.

  • PDF

Reliability Analysis and Optimization Considering Dynamic Characteristics of Vehicle Torsion Beam (차량 토션빔의 동적 특성을 고려한 신뢰성 분석 및 최적설계)

  • 이춘승;임홍재;이상범
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
    • /
    • /
    • pp.813-817
    • /
    • 2002
  • This paper presents the reliability analysis technique on the dynamic characteristics of the torsion beam consisting the suspension system of passenger car. We utilize response surface method (RSM) and Monte Carlo simulation to obtain the response surface model that describes the limit state function for the natural frequencies of the torsion beam. Using the response surface model and the design optimization technique, we have obtained the optimized section considering the reliability of the torsion beam structure.

  • PDF

Multi-Level Response Surface Approximation for Large-Scale Robust Design Optimization Problems (다층분석법을 이용한 대규모 파라미터 설계 최적화)

  • Kim, Young-Jin
    • Korean Management Science Review
    • /
    • v.24 no.2
    • /
    • pp.73-80
    • /
    • 2007
  • Robust Design(RD) is a cost-effective methodology to determine the optimal settings of control factors that make a product performance insensitive to the influence of noise factors. To better facilitate the robust design optimization, a dual response surface approach, which models both the process mean and standard deviation as separate response surfaces, has been successfully accepted by researchers and practitioners. However, the construction of response surface approximations has been limited to problems with only a few variables, mainly due to an excessive number of experimental runs necessary to fit sufficiently accurate models. In this regard, an innovative response surface approach has been proposed to investigate robust design optimization problems with larger number of variables. Response surfaces for process mean and standard deviation are partitioned and estimated based on the multi-level approximation method, which may reduce the number of experimental runs necessary for fitting response surface models to a great extent. The applicability and usefulness of proposed approach have been demonstrated through an illustrative example.

Capabilities of stochastic response surface method and response surface method in reliability analysis

  • Jiang, Shui-Hua;Li, Dian-Qing;Zhou, Chuang-Bing;Zhang, Li-Min
    • Structural Engineering and Mechanics
    • /
    • v.49 no.1
    • /
    • pp.111-128
    • /
    • 2014
  • The stochastic response surface method (SRSM) and the response surface method (RSM) are often used for structural reliability analysis, especially for reliability problems with implicit performance functions. This paper aims to compare these two methods in terms of fitting the performance function, accuracy and efficiency in estimating probability of failure as well as statistical moments of system output response. The computational procedures of two response surface methods are briefly introduced first. Then their capabilities are demonstrated and compared in detail through two examples. The results indicate that the probability of failure mainly reflects the accuracy of the response surface function (RSF) fitting the performance function in the vicinity of the design point, while the statistical moments of system output response reflect the accuracy of the RSF fitting the performance function in the entire space. In addition, the performance function can be well fitted by the SRSM with an optimal order polynomial chaos expansion both in the entire physical and in the independent standard normal spaces. However, it can be only well fitted by the RSM in the vicinity of the design point. For reliability problems involving random variables with approximate normal distributions, such as normal, lognormal, and Gumbel Max distributions, both the probability of failure and statistical moments of system output response can be accurately estimated by the SRSM, whereas the RSM can only produce the probability of failure with a reasonable accuracy.