W. Chen, J. K. Allen, K.-L. Tsui and F. Mistree, "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors". Journal of Mechanical Design, 118:478-- 485, December 1996. 8  Home/Search   Document Details and Download   Summary   Related Articles   Check

....with the original quality function or with the expectation based measure. Di#erent combinations of objectives are possible: maximizing the expectation and maximizing the original function, for example in [1] maximizing the expectation and minimizing the variance, for example in [4]; maximizing the original function and minimizing the variance. Since robustness and performance (even if its measure is expectation based) are often exclusive objectives, see Figure 1 for an example, it makes sense to analyze this problem in the framework of multicriteria optimization. In ....

W. Chen, J. K. Allen, K.-L. Tsui, and F. Mistree. A procedure for robust design: Minimizing variations caused by noise factors and control factors. ASME Journal of Mechanical Design, 118:478--485, 1996.

....addressed as a trade o# between optimality and robustness. As suggested in [1] the trade o# can be realized by simultaneously optimizing the expectation and optimizing the original function, for example in [1] optimizing the expectation and minimizing the variance, for example in [4]; optimizing the original function and minimizing the variance. The approach adopted in this work can be categorized into this class, however, instead of directly minimizing the variance of the function, the variance of the design variables are also taken into account. In evolutionary ....

....be formulated as follows, assuming the maximal deviation of the both variables is 1: minimize f 1 = 31) f 2 = 32) subject to g(x) x 2 8.45, 33) 9, 34) 9, 35) where = 5.1046 and # = 0. 4168 are the ideal solutions for the mean and deviation of the function[4]. We call the objective for robustness in equation (32) the theoretical robustness measure, which is explicitly derived from the original fitness function. The dynamic weighted aggregation method with a (15, 100) ES is used to solve the multiobjective optimization problem. The obtained Pareto ....

W. Chen, J. K. Allen, K.-L. Tsui, and F. Mistree. A procedure for robust design: Minimizing variations caused by noise factors and control factors. ASME Journal of Mechanical Design, 118:478--485, 1996.

.... design criterion (Box, 1988; Nair, 1992) the developments in the design community have produced nonlinear programming based robust design methods that can be used in a variety of applications (Otto and Antonsson, 1993; Parkinson et al. 1993; Sundaresan et al. 1993; Cagan and Williams, 1993; Chen et al. 1996; Su and Renaud, 1997) including probabilistic based robust optimization (Eggert and Mayne, 1993) With the introduction of the nonlinear programming framework to robust design, the issue that has brought more and more attention in recent developments is the modeling of the multiple quality ....

Chen, W., Allen, J. K., Mistree, F. and Tsui, K.-L., 1996, "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors," ASME Journal of Mechanical Design, Vol. 118, pp.478-485.

....is subject to many sources of uncertainty [17] endogenous factors such as design risks, outcomes of tests during development, or new technologies, and . exogenous factors, such as funding changes, market acceptance of the product, etc. Many approaches exist for modeling such uncertainty [1, 4, 19, 20, 28]. We apply probability mathematics in this paper, reflecting the fact that these uncertainties are not due to designer selection uncertainty, but uncontrollable factors. Our contact with several industries suggests that the key issue when planning a new line of products is platform flexibility. ....

Chen, W., Allen, J., Tsui K.-L., Mistree, F., "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors, Journal of Mechanical Design, 1996, 118(4), 478-493.

....characteristics, one must first understand the formulation aspect: defining the links that characterize the interaction and understanding what is unknown or uncertain about these links. Recent research reported by the authors of this paper (see Ref. 13] as well as the authors in Ref. [14] has resulted in approaches to representing uncertainty, generally at the system level, and propagating that uncertainty into some response which measures the goodness of design alternatives. This measure is usually associated with the concept of robustness, and the area of research is generally ....

Chen, W., Allen, J., Tsui. K.L., Mistree, F., "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factor and Control Factors," ASME Journal of Mechanical Design, Vol. 118, No. 4, pp. 478485,

....design is generally applied to the methods of Taguchi (Phadke 1989) who presented a method using designed experiments to find a combination of process settings that would be insensitive to input variation. Taguchi s methods have been used widely in industry, with some important extensions from Chen, Allen, and colleagues (1996) and Chinnam and Kolarik (1997) Taguchi uses a block diagram representation of manufacturing processes called the P diagram. This diagram is very similar to the schematic we use to represent a generic manufacturing system. We distinguish between incoming material and process variables, but each ....

Chen, W., J. Allen, et al. (1996). "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors." Journal of Mechanical Design 118(4): 478-493.

....compromise DSP, the variation among the family of products is captured by the deviations of the design variables and the resulting performance deviations using variation based modeling. The use of variation based modeling has been reported earlier for robust design applications in Chen et al. [3]. For ease of computation, a probabilistic representation is adopted. The design variables of each product are modeled to follow uniform probability distributions represented by two variables: the mean, m, and the standard deviation, s. The resulting variation of each performance parameter is ....

Chen, W., Allen, J. K., Tsui, K. L. and Mistree, F. (1996). A procedure for robust design: minimizing variations caused by noise and control factors. Journal of Mechanical Design, 118(4), 478--485.

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Chen, W., Allen, J.K., Mistree, F. and Tsui, K.-L., A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors, ASME Journal of Mechanical Design, Vol. 118, No. 4, 1996, pp.478-485.

....3) The values of the configuration deviation variables d i , d i (i = 5 9; corresponding to goals, Eqns. 19 23) Satisfy: SFC 1.030 lbm h lbf normalized [8] Thrust 990 lbf normalized [9] Mixing pressure ratio (Phot Pcold) 0.94 [10] SFC 0.96 d 1 = 1 [12] STDSFC 0. 01 d 2 = 1 [13] THRUST 1052 d 3 = 1 [14] STDTHR 29 d 4 = 1 [15] Weight 1425 lbs [16] Length 7 ft [17] Fan diameter 38.4 in [18] Thegoals: WEIGHT 1350 d 5 = 1 [19] STDWGT 0.005 d 6 = 1 [20] LENGTH 6 d 7 = 1 [21] STDLNG 0.02 d 8 = 1 [22] FANDIA 37 d 9 = 1 [23] Bounds on ....

Chen, W., Allen, J.K., Tsui, K.-L., and Mistree, F., "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors," ASME Journal of Mechanical Design, Vol. 118, No. 4, 1996, pp. 478-485.

....even with modifications, MCS is generally not affordable in the design of complex engineering systems. As the direct use of data sampling methods is very expensive, an alternative approach that is being widely considered is the use of response surface models to replace the numerical models [6, 20 23], either over the space of all variables or that of the 5 random variables only [24,25] Data sampling is then performed based on the response surface model instead of the original numerical model. The drawback of using this approach is the cost associated with generating an accurate response ....

Chen, W., Allen, J.K., Mistree, F., and Tsui, K.-L., "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors," ASME Journal of Mechanical Design, Vol. 118, pp.478-485, 1996.

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Chen, W., Allen, J.K., Mistree, F., and Tsui, K.-L., 1996a, "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors," ASME Journal of Mechanical Design, Vol. 118, pp.478-485.

.... including Manners, 1990; Laskey, 1996; Ayyub and Chao, 1997; Du and Chen, 1999a) The commonly used method for uncertainty analysis is the sensitivity based approximation approach that includes the worst case analysis and the moment matching method (Eggert, 1991; Parkinson, et al. 1993, Chen, et al. 1996; Du and Chen, 1999b, Du and Chen, 2000, and Du, et al. 2000) With the worst case analysis, all the fluctuations are assumed to occur simultaneously in the worst possible combinations and based on this assumption, the worst value of the system output (extreme condition) can be found by the first ....

Chen, W., Allen, J.K., Mistree, F., and Tsui, K.-L., 1996, "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors," ASME Journal of Mechanical Design, Vol. 118, pp.478-485.

No context found.

Chen, W., Allen, J.K., Mistree, F., and Tsui, K.-L., 1996a, "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors," ASME Journal of Mechanical Design, Vol. 118, pp.478-485.

....and generating optimal solutions that could reduce the impact of the uncertainty in a global scale. In the engineering design community, the robust design concept has been extended into the early stages of design to improve the quality of design decisions. A part of the author s investigation (Chen et al. 1996) is to extend the robust design concept into the early stages of design for making decisions that are robust to the changes of downstream 7 design considerations (called Type I robust design) and decisions that are flexible to be allowed to vary within a range (called Type II robust design) ....

Chen, W., Allen, J. K., Mistree, F. and Tsui, K.-L., 1996, "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors", ASME Journal of Mechanical Design, 118, 478-485.

....Efficient Solutions, Utility Function, Decision Analysis Words Count: 2,912. 2 1. INTRODUCTION A variety of nonlinear programming based robust design methods have been recently proposed (Otto and Antonsson, 1991; Parkinson et al. 1993; Sundaresan et al. 1993; Cagan and Williams, 1993; Chen et al. 1996; Su and Renaud, 1997) It has been recognized that robust design does involve multiple quality aspects that can be generalized into optimizing the mean of performance and minimizing the variation of performance . Since the performance variation is often minimized at the cost of sacrificing the ....

Chen, W., Allen, J. K., Mistree, F. and Tsui, K.-L., 1996, "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors," ASME Journal of Mechanical Design, Vol. 118, pp.478-485.

.... for system synthesis [25, 34] Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration [35] Noise modeling techniques for implementing robust preliminary design when approximate models are employed [6,7] These techniques were developed for a case study performed with Rolls Royce Allison and are based on an existing engine designed for midsize commercial, regional business jets. The solutions obtained are similar to the design model of the existing commercial engine, but are better with respect ....

Chen, W., Allen, J.K, Tsui, K-L and Mistree, F., "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors," ASME Journal of Mechanical Design,vol. 118, no. 4, pp.478485, 1996.

No context found.

Chen, W., Allen, J.K, Tsui, K-L and Mistree, F., "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors," ASME Journal of Mechanical Design, vol. 118, no. 4, pp. 478485, 1996.

.... modification of the signal to noise ratio as the robust design criterion (Box, 1988; Nair, 1992) the developments in the design community have produced nonlinear programming based robust design methods that can be used in a variety of applications (Parkinson et al. 1993; Sundaresan et al. 1993; Chen et al. 1996). A comprehensive review of existing robust optimization methods developed by the engineering design community was provided by Su and Renaud (1997) and will not be repeated here. A general robust design procedure was developed by one of the authors (Chen et al. 1996) to overcome the ....

....Sundaresan et al. 1993; Chen et al. 1996) A comprehensive review of existing robust optimization methods developed by the engineering design community was provided by Su and Renaud (1997) and will not be repeated here. A general robust design procedure was developed by one of the authors (Chen et al. 1996) to overcome the limitations of Taguchi s method, and to solve two broad categories of robust design problems. Namely, Type I robust design associated with the minimization of variations in performance caused by variations in noise (uncontrollable) factors, and Type II robust design associated ....

Chen, W., Allen, J. K., Mistree, F. and Tsui, K.- L., 1996, "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors," ASME Journal of Mechanical Design, Vol.

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Chen, W., Allen, J. K., Mistree, F. and Tsui, K.-L., 1996b, "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors," ASME Journal of Mechanical Design, Vol. 118, pp.478-485.

....specifications has been demonstrated by earlier work in this area (Lewis, et al. 1999; Simpson, et al. 1996) Greater design flexibility can be achieved during the design process by generating a range of solutions rather than a single point solution; this is the basis for the RCEM. The RCEM (Chen, et al. 1996) facilitates quick evaluation of design alternatives and generation of top level design specifications with quality considerations in the early stages of design. It classifies the design parameters as noise and control factors and uses the compromise DSP to determine the solution in which the ....

Chen, W., Allen, J. K., Tsui, K. L. and Mistree, F., 1996, " A Procedure for Robust Design: Minimizing Variations Caused by Noise and Control Factors," Journal of Mechanical Design, Vol. 118, No. 4, pp.478-485.

No context found.

Chen, W., Allen, J.K., Mistree, F. and Tsui, K.-L., "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors," ASME Journal of Mechanical Design, Vol. 118, No. 4, 1996, pp.478-485.

No context found.

W. Chen, J. K. Allen, K.-L. Tsui and F. Mistree, "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors". Journal of Mechanical Design, 118:478-- 485, December 1996. 8

No context found.

Chen, W., J.K. Allen, K-L. Tsui, and F. Mistree, 1996, "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors," ASME Journal of Mechanical Design, 118, No. 4, pp. 478-485.

No context found.

Chen, W., Allen, J.K., Mistree, F., and Tsui, K.-L., "A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors," ASME Journal of Mechanical Design, Vol. 118, pp. 478-485, 1996.

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