• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.593-609
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• 2004

Peak response is a more suitable index than mean response in the light of structural safety. In this study, a controller optimization method is proposed to restrict peak responses of building structures subject to earthquake excitations, which are modeled as partially stationary stochastic process. The constraints are given with specified failure probabilities of peak responses. LQR is chosen to assure stability in numerical process of optimization. Optimization problem is formulated with weightings on controlled outputs as design variables and gradients of objective and constraint functions are derived. Full state feedback controllers designed by the proposed method satisfy various design objectives and output feedback controllers using LQG also yield similar results without significant performance deterioration.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.5
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• pp.121-128
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• 2012

The optimization of cooling system parameters for designing injection mold is very important to acquire the highest part quality. In this paper, the integration of computer simulations of injection molding and Analysis of Variance(ANOVA) with orthogonal array was used as a design tool to optimize the cooling system parameters aimed at minimizing the part warpage. The design optimizer was applied to find the optimum levels of cooling system parameters for a dustpan. This optimization resulted in more uniform temperature distribution over the part and significant reduction of a part warpage, showing the capability of present method as an effective design tool. The whole optimization process was performed systematically in a proper number of cooling simulations. The design optimizer can be utilized effectively in the industry practice for designing mold cooling system with less cost and time.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.6
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• pp.70-76
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• 2011

This paper presents an optimization procedure for reducing warpage of injection molded part by using a volumetric shrinkage deviation as an objective function. A design of experiments based on orthogonal arrays was used in the optimization procedure, and the entire optimization was performed through a two stage process - a preliminary experimentation and a principal experimentation. Proposed optimization method was applied to the design of a CPU-base part in computer. With the moderate number of experiments, an optimal molding condition for uniform distribution of volumetric shrinkage was obtained, as a result, the warpage of the molded part was significantly reduced.

• Transactions of Materials Processing
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• v.30 no.1
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• pp.27-34
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• 2021

In this study, response surface method (RSM) was used in modeling and multi-objective optimization of the parameters of AA5052-H32 in incremental sheet forming (ISF). The goals of optimization were the maximum forming angle, minimum thickness reduction, and minimum surface roughness, with varying values in response to changes in production process parameters, such as tool diameter, tool spindle speed, step depth, and tool feed rate. A Box-Behnken experimental design (BBD) was used to develop an RSM model for modeling the variations in the forming angle, thickness reduction, and surface roughness in response to variations in process parameters. Subsequently, the RSM model was used as the fitness function for multi-objective optimization of the ISF process based on experimental design. The results showed that RSM can be effectively used to control the forming angle, thickness reduction, and surface roughness.

• Elastomers and Composites
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• v.34 no.4
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• pp.321-331
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• 1999

The curing process is the final step in tire manufacturing whereby a green tire built from layers of rubber compounds is formed to the desired shape and the compounds are converted to a strong, elastic materials to meet tire performance needs under elevated pressure and temperature in a press. A numerical optimization procedure was developed to improve product quality in a tire curing process. First, a dynamic constrained optimization problem was formulated to determine the optimal condition of the supplied cure media during a curing process. The objective function is subject to an equality constraint representing the process model that describes the heat transfer and cures kinetic phenomena in a cure press and is subject to inequality constraints representing temperature limits imposed on cure media. Then, the optimization problem was solved to determine optimal condition of the supplied cure media for a tire using the complex algorithm along with a finite element model solver.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1996.10a
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• pp.304-312
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• 1996

Concepts, methods and tools for interactive CAD-based concurrent engineering design optimization of mechanical/structural systems and components which are critical in terms of cost development time, functionality and quality, are presented. The emphasis is on implementation of methods and capabilities for the optimization of composite structural system, and the integration of design process and manufacturing process of composite structures into standard CAD-based concurrent engineering environment The optimization of composite fuselage structures are performed under concurrent engineering environment for the example.

• Coupled systems mechanics
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• v.13 no.3
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• pp.219-229
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• 2024

By introducing optimization algorithms into the machining process, product quality can be improved, time saved, and costs reduced. The cutting speed and feed can be handled by the turning machine. The approach of optimizing is used to manage pyrotechnics, Lawler's, greedy, bacterial colony, elephant herding, ant lion, spiral, auction, and pattern search for these ten odd ways. Ten artificial optimization methodologies were used to investigate the time and cost of a turning machine. It has been discovered how to create the optimal turning machine procedure. The best solution approach for the turning machine process problem is found, and the results are verified using ANSYS.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.3
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• pp.119-124
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• 2017

Machining optimization using typical computer-aided manufacturing (CAM) software mainly depends on tool paths, and it is impossible to predict the behavior of material or cutting force. In this paper, cutting force analysis simulation is performed on the Unibody Case of a mobile phone with the aim of optimizing cutting-force-based machining using the Third Wave Systems' AdventEdge Production Module. Machining time after optimization was shortened by 42% for roughing compared to pre-optimization, and actual machining time was reduced by 36.8%. For finishing, machining time was reduced by 92%, and actual machining time was reduced around 90%. A surface roughness analysis found that the post-optimization surface roughness was $1.16{\mu}m$ Ra, compared to a pre-optimization value of $1.75{\mu}m$ Ra.

• Journal of Mechanical Science and Technology
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• v.20 no.3
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• pp.366-375
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• 2006

In this paper, it is intended to introduce a method to solve multi-objective optimization problems and to evaluate its performance. In order to verify the performance of this method it is applied for a vertical roller mill for Portland cement. A design process is defined with the compromise decision support problem concept and a design process consists of two steps: the design of experiments and mathematical programming. In this process, a designer decides an object that the objective function is going to pursuit and a non-linear optimization is performed composing objective constraints with practical constraints. In this method, response surfaces are used to model objectives (stress, deflection and weight) and the optimization is performed for each of the objectives while handling the remaining ones as constraints. The response surfaces are constructed using orthogonal polynomials, and orthogonal array as design of experiment, with analysis of variance for variable selection. In addition, it establishes the relative influence of the design variables in the objectives variability. The constrained optimization problems are solved using sequential quadratic programming. From the results, it is found that the method in this paper is a very effective and powerful for the multi-objective optimization of various practical design problems. It provides, moreover, a reference of design to judge the amount of excess or shortage from the final object.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.3
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• pp.74-81
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• 2019

Herein, we performed a comparative study on approximate multi-objective design optimization, to realize a structural design to improve the weight and vibration performances of the knuckle - a car suspension component - considering various load conditions and vibration characteristics. In the approximate multi-objective optimization process, a regression meta-model was generated using the response surfaces method (RSM), while Kriging and back-propagation neural network (BPN) methods were applied for interpolation meta-modeling. The Pareto solutions, multi-objective optimal solutions, were derived using the non-dominated sorting genetic algorithm (NSGA-II). In terms of the knuckle design considered in this study, the characteristics and influence of the meta-model on multi-objective optimization were reviewed through a comparison of the approximate optimization results with the meta-models and the actual optimization.