• Korean Journal of Materials Research
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• v.15 no.11
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• pp.705-710
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• 2005

NIL (nanoimprint lithography) technique has demonstrated a high potential for wafer size definition of nanometer as well as micrometer size patterns. During the replication process by NIL, the stiction between the stamp and the polymer is one of major problems. This stiction problem is moi·e important in small sized patterns. An antistiction layer prevents this stiction ana insures a clean demolding process. In this paper, we were using a TCP (transfer coupled plasma) equipment and $C_4F_8$ as a precursor to make a Teflon-like antistiction layer. This antistiction layer was deposited on a 6 inch silicon wafer to have nanometer scale thicknesses. The thickness of deposited antistiction layer was measured by ellipsometry. To optimize the process factor such as table height (TH), substrate temperature (ST), working pressure (WP) and plasma power (PP), we were using a design of experimental (DOE) method. The table of full factorial arrays was set by the 4 factors and 2 levels. Using this table, experiments were organized to achieve 2 responses such as deposition rate and non-uniformity. It was investigated that the main effects and interaction effects between parameters. Deposition rate was in proportion to table height, working pressure and plasma power. Non-uniformity was in proportion to substrate temperature and working pressure. Using a response optimization, we were able to get the optimized deposition condition at desired deposition rate and an experimental deposition rate showed similar results.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.5
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• pp.433-441
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• 2011

The optimization of a centrifugal compressor was conducted. The ANN (Artificial Neural Network) was adopted as an optimization algorithm, and it was learned and trained with the DOE (Design of Experiment). In the DOE, it was predicted the main effect and the interaction effect of design variables to the objective function. The ANN was improved in the optimization process using the GA (Genetic Algorithm). When any output at each generation was reached a standard level, it was re-calculated by the CFD (Computational Fluid Dynamics) and it was applied to develop a new ANN. After 6th generation, the prediction difference between ANN and CFD was less than 1%. A pareto of the efficiency versus the pressure ratio was obtained through the 21th generation. Using this method, the computational time for the optimization was equivalent to the time consumed by the gradient method, and the optimized results of multi-objective function were obtained.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.1511-1516
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• 2007

Because Seaming process of MPJ (Mechanical Press Joining) has various design factors such as thickness, bending radius, seaming width, caulking press width and the dynamic factor such as multistage plastic working, elastic recovery, residual stress, the optimum conditions can't be easily determined. Using a design of experiment based on the FEM, which has several advantages such as less computing, high accuracy performance and usefulness, this study was performed investigating the interaction effect between the various design factor as well as the main effect of the each design factor during drum MPJ and proposed optimum condition using center composition method among response surface derived from regression equation of simulation-based DOE.

• Journal of the Korea Safety Management & Science
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• v.21 no.1
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• pp.17-23
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• 2019

The diesel engine generate many pollutants such as PM(Particulate matter) and NOx(Nitrogen oxide). So the SCR(Selective catalytic reduction) must be required to meet the emission standard. The SCR catalyst market is growing rapidly, and the automobile markets using alternative energy sources are growing rapidly. This study deals with optimization of the calcination process the manufacturing process of SCR catalyst to be competitive. The calcination process is a bottleneck and it is required to optimize productivity and accept to be safety, But we cannot trade off anything in terms of safety. We applied DOE(Design of experiments) among many research methods performed in various fields. In order to achieve quality and productivity optimization. The dependent variables in the DOE were selected as NO Conversion(%). The independent variables were selected as the calcination temperature, soaking time and fan speed RPM. the CCD(Central composite designs) constructs response surface using the data onto experience and finds optimum levels within the fitted response surfaces. Our tests are our stability guarantee and efficient together with operation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.735-741
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• 2011

In the early phase of vehicle development, CAE is conducted as tool for vehicle performance assessment. To maintain acceptable road noise performance, solution for reduced vehicle sensitivity is required. Chassis interface dynamic stiffness characteristics are key component to isolating vibration and noise of road from the vehicle interior. This research provide how to set up the optimized dynamic characteristics under noise effect through DFSS study. CAE-based DOE is performed to build prediction math model, CMS process involves DOE to achieve very fast run times while giving results very comparable. Minimized $95^{th}$ percentile of performance distribution is applied to minimize vehicle sensitivity and road noise levels variation during the optimization process. Finally, the results of optimization were reviewed for performance and robustness.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.7
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• pp.674-681
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• 2011

In the early phase of vehicle development, CAE is conducted as tool for vehicle performance assessment. To maintain acceptable road noise performance, solution for reduced vehicle sensitivity is required. Chassis interface dynamic stiffness characteristics are key component to isolating vibration and noise of road from the vehicle interior. This research provide how to set up the optimized dynamic characteristics under noise effect through DFSS study. CAE-based DOE is performed to build prediction math model, CMS process involves DOE to achieve very fast run times while giving results very comparable. Minimized 95th percentile of performance distribution is applied to minimize vehicle sensitivity and road noise levels variation during the optimization process. Finally, the results of optimization were reviewed for performance and robustness.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.236-240
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• 2005

This paper deals with friction-induced vibration of disc brake system under constact friction coefficient. A linear, finite element model to represent the floating caliper disc brake system is proposed. The complex eigenvalues are used to investigate the dynamic stability and in order to verify simulations which are based on the FEM model, The comparison of experimental and analytical results shows a good agreement and the analysis indicates that mode coupling due to friction force and geometric instability is responsible fur disc brake squeal. And the Front brake system reduced the squeal noise using design of experiment method(DOE). This helped to validate the FEM model and establish confidence in the simulation results. Also they may be useful during real disk brake model.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.1189-1190
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• 2013

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.235-236
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• 2009

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.283-284
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• 2007