• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.1
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• pp.73-80
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• 2010

The optimal design of water distribution system have started with the least cost design of single objective function using fixed hydraulic variables, eg. fixed water demand and pipe roughness. However, more adequate design is accomplished with considering uncertainties laid on water distribution system such as uncertain future water demands, resulting in successful estimation of real network's behaviors. So, many researchers have suggested a variety of approaches to consider uncertainties in water distribution system using uncertainties quantification methods and the optimal design of multi-objective function is also studied. This paper suggests the new approach of a multi-objective optimization seeking the minimum cost and maximum robustness of the network based on two uncertain variables, nodal demands and pipe roughness uncertainties. Total design procedure consists of two folds: least cost design and final optimal design under uncertainties. The uncertainties of demands and roughness are considered with Latin Hypercube sampling technique with beta probability density functions and multi-objective genetic algorithms (MOGA) is used for the optimization process. The suggested approach is tested in a case study of real network named the New York Tunnels and the applicability of new approach is checked. As the computation time passes, we can check that initial populations, one solution of solutions of multi-objective genetic algorithm, spread to lower right section on the solution space and yield Pareto Optimum solutions building Pareto Front.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.2
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• pp.163-168
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• 2011

Robust optimization or reliability-based design optimization are some of the methodologies that are employed to take into account the uncertainties of a system at the design stage. For applying such methodologies to solve industrial problems, accurate and efficient methods for estimating statistical moments and failure probability are required, and further, the results of sensitivity analysis, which is needed for searching direction during the optimization process, should also be accurate. The aim of this study is to employ the function approximation moment method into the sensitivity analysis formulation, which is expressed as an integral form, to verify the accuracy of the sensitivity results, and to solve a typical problem of reliability-based design optimization. These results are compared with those of other moment methods, and the feasibility of the function approximation moment method is verified. The sensitivity analysis formula with integral form is the efficient formulation for evaluating sensitivity because any additional function calculation is not needed provided the failure probability or statistical moments are calculated.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.10
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• pp.1323-1328
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• 2011

In the current design process for the lower arm used in automobile parts, an optimal solution of its various design variables should be found through exploration of the design space approximated using the response surface model formulated with a first- or second-order polynomial equation. In this study, a multi-level computational DOE (design of experiment) was carried out to explore the design space showing nonlinear behavior, in terms of factors such as the total weight and applied stress of the lower arm, where a fractional-factorial orthogonal array based on the artificial neural network model was introduced. In addition, the tolerance robustness of the optimal solution was estimated using a tolerance optimization with six sigma constraints, taking into account the tolerances occurring in the design variables.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.1
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• pp.112-123
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• 1997

The optimization techniques have been applied to versatile engineering problems for reducing manufacturing cost and for automatic design. The deterministic approaches or op5imization neglect the effects on uncertainties of design variables. The uncertainties include variation or perturbation such as tolerance band. The optimum may be useless when the constraints considering worst cases of design variables can not be satisfied, which results from constraint variation. The variation of design variables can also give rise to drastic change of performances. The two issues are related to constraint feasibility and insensitive performance. Robust design suggested in the present study is developed to gain an optimum insensitive to variation on design variables within feasible region. The multiobjective function is composed to the mean and the standard deviation of original objective function, while the constraints are supplemented by adding penalty term to original constraints. This method has a advantage that the second derivatives of the constraints are not required. A mathematical problem and several standard problems for structural optimization are solved to check out the usefulness of the suggested method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11a
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• pp.419-426
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• 2001

Industrial products determined by fixed size posses definite limits variety by manufacture tolerance in existence. The optimum value solved by deterministic approaches do not account of tolerance bands of design variables and material properties. If we examine optimum value considering tolerance bands of design variables and material properties, it might be useless, owing to exist infeasible region. We have two ways to prevent being useless value. The one is to minimize tolerance band, the other is to consider tolerance band in optimum design. The former needed more accuracy during manufacturing process require higher production cost, the letter is more appropriate to consider tolerance band. In this research, we consider the tolerance bands of all variables, which might have the tolerance bands used in the problem, based on optimum value of deterministic approaches. Orthogonal arrays are used to minimize the number of trial. Tolerance bands are supposed discretionary according to design variable. Appropriateness suggested by this research is examined through two examples. Mathematical problem is investigated only in terms of tolerance bands of design variables, and cantilever beam problem is explained through tolerance bands of design variable, material properties and loading conditions. It is proved that values from the presented method are satisfactory for tolerance bands of variables.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.8 s.251
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• pp.1001-1007
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• 2006

In this paper we present robust optimal supporting positions for large glass panels used for TFT-LCD monitors when they are stored in a cassette during manufacturing process. The criterion taken is to minimize their maximum deflection. Since they are supported by some supports and have large deformations, contact analysis with a geometrically nonlinear effect is necessary. In addition, the center of a panel can not be positioned exactly as intended and should be considered as uncertainties. To take into account of these effects, the mean and the standard deviation of system response functions, particularly the deflection of the panels, need be calculated. A function approximation moment method (FAMM) is utilized to estimate them. It is a special type of response surface methodology for structural reliability analysis and can be efficiently used to estimate the two stochastic properties, that is, the system performance and the perturbations caused by uncertainties. For a design purpose, they are to be minimized simultaneously by some optimization algorithm to obtain robust optimal supporting positions.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.2
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• pp.160-167
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• 2004

The correlation between the object function and the design parameter is shown on this paper by using the characteristic function for the mixed result of the structural analysis, the buckling analysis and the table of orthogonal array according to the original overhead crane's dimensional change. About the above two functions, the effectiveness of design change according to the change of design parameters could be estimated. Also, the overhead crane's weight is reduced up to 10.55 percent maintaining the structural stability according to the thickness of plate.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.836-840
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• 2006

Design optimization of layered plates bonding process is conducted to achieve high product quality by considering uncertainties in a manufacturing process. During the cooling process of the sequential sub-processes, different thermal expansion coefficients lead to residual stress and displacement. thus resulting in defects on the surface of the adherent. So robust process optimization is performed to minimize the residual stress mean and variation of the assembly while constraining the distortion as well as the instantaneous maximum stress to the allowable limits. In robust process optimization, the dimension reduction (DR) method is employed to quantify both reliability and quality of the layered plate bonding. Using this method. the average and standard deviation is estimated. Response surface is constructed using the statistical data obtained by the DRM for robust objectives and constraints. from which the optimum solution is obtained.

• Korean Journal of Computational Design and Engineering
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• v.15 no.5
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• pp.325-332
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• 2010

A lens system for mobile phone cameras is comprised of various lenses and designed so as to satisfy design requirements for responses such as a modular transfer function (MTF). However, it is difficult to manufacture and assemble camera modules to maintain the same performance compared with the designed camera modules, because of uncertainty. We should always design a lens system by considering uncertainty that can be caused by errors in the manufacturing and assembly process of mobile phone cameras. The robust optimization offers tools of making robust decisions with the consideration of design parameters, uncontrollable parameters, and the variance of the system. Using an efficient reliability analysis method and an optimization algorithm, we obtained robust optimization results that maximize the mean of MTF and minimize the standard deviation and proposed a new robust design process for a lens system.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.3
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• pp.90-97
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• 2009

In the study, a design methodology for robust minimization of a warpage in injection-molded part is presented. Taguchi's parameter design method is integrated with a computer simulation tool for injection molding to search for best design with robustness against the process variability by noises. The proposed methodology is based on a two-stage process: (1) reducing a warpage in the part by optimizing the part geometry including the layout and size of ribs, and (2) additionally minimizing the warpage by optimizing process conditions. An example is used to illustrate the usefulness of the design methodology.