• Journal of the Semiconductor & Display Technology
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• v.12 no.4
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• pp.9-13
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• 2013

Lapping is a very complicated and random process resulting from the variation of abrasive grains in its sizes and shapes and from the numerous factors having an effect on the process quality. This paper presents a study of a $2^4$ full factorial experimental design and analysis to optimize surface quality in lapping operation. The optimization of the factors to obtain minimum surface roughness was carried out by incorporating effect plots, main effect plots, interaction plots, analysis of variance(ANOVA), surface plots, and contour plots. The statistical design experiments, designed to reduce the total number of experiments required, indicated that, within the selected conditions, all the parameters influenced at a significance level of 5%. In addition, some of the possible interactions between these parameters also influenced the lapping process, especially those that were of third order. A regression model was suggested and fitted the experimental data very well.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.10
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• pp.147-155
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• 2002

In the stereolithography process, the accuracy of product depends on laser power, scan speed, scan width, scan pattern, layer thickness, resin characteristics and so on. Therefore, appropriate process parameters are required for an accurate prototype. This paper presents a method to determine the key process parameters, i.e., laser scan speed, hatching space, and layer thickness based on scan length, scan area, and layer slope. In order to determine these parameters, three neural networks are employed to represent operator’s experience and knowledge. Optimum values on scan speed, hatching space and layer thickness are recommended to improve the surface roughness and build time on the developed SLA machine.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.596-599
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• 2004

The robotic $CO_2$ welding is a manufacturing process to produce high quality joints for metal and it could provide a capability of full automation to enhance productivity. Despite the widespread use in the various manufacturing industries, the full automation of the robotic $CO_2$ welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this research, an attempt has been made to develop an intelligent algorithm to predict the weld geometry (top-bead width, top-bead height, back-bead width and back-bead height) as a function of key process parameters in the robotic $CO_2$welding. To achieve this above objective, Taguchi method was employed using five different process parameters (tip gap, gas flow rate, welding speed, arc current, welding voltage) as a guide for optimization of process parameters.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2001.05a
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• pp.49-53
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• 2001

Recently hydroforming process became a process which is increasingly applied in the automotive industry. As the hydroforming process is a new technology, there is no abundant data to assist manufacturing the products. To investigate the effects of process parameters on the tube hydroforming process, simple bulging, circular bulging and Tee-fitting tests are performed. The optimal leading path to escape the failure modes(bursting, wrinkling) is determined and the effects of the process parameters, the internal pressure and axial feeding on the product quality, such as thickness distribution, forming height and branch dome shape are investigated.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.384-388
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• 1997

Recently,direct rolling process has been drawing increasing interests because production cost be greatly reduced by eliminating subsequent hot rolling processes. Such a process has been characterized to prosuce thin steel strip (thickness 1~5mm) directly from molten metal and to skip over the conventional hot rolling processes. However, since there are several process parameters, which affect the quality of product,and their relationship between the parametersare very complex,it is therefore very difficult to realize the process design and the quality control. To overcome these difficulties quantitative relationship between the parameters are investigated through a numerical analysis. Form these results, it is found that solidification final point is the most important paramter which is critical to quality of the strip. Also,the multiple regression model is obtianed to determine their relationship from the solidification final point and roll separating force which can be easily estimated

• Electrical & Electronic Materials
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• v.7 no.2
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• pp.107-116
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• 1994

In the manufacturing of VLSI circuits, variations of device characteristics due to the slight differences in process parameters drastically aggravate the performances of fabricated devices. Therefore, it is very important to establish optimal process conditions in order to minimize deviations of device characteristics. In this paper, we used one-dimensional process simulator, SUPREM-II, and two dimensional device simulator, MINIMOS 4.0 in order to extract optimal process parameter which can minimize changes of the device characteristics caused by process parameter variation in the case of short channel nMOSFET and pMOSFET device. From this simulation, we have derived the dependence relations between process parameters and device characteristics. Here, we have suggested a method to extract process parameters from design trend curve(DTC) obtained by these dependence relations. And we have discussed short channel effects and device limitations by scaling down MOSFET dimensions.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.2
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• pp.81-88
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• 2014

Synthetic products such as casting tape and splints are rapidly replacing conventional plaster casts to treat orthopedic patients. Most synthetic products are produced through a polymerization process with related chemical agents. In this study, the effect of the process parameters on the residual NCO content within a prepolymer for casting tape and the hardening temperature for casting tape were experimentally evaluated. In order to verify the effects of the process parameters, an experimental method was adopted. From an S/N ratio analysis, optimal parameter combinations were determined to produce a pre-polymer with a suitable residual NCO content and alower hardening temperature. Prediction models for the NCO content and the hardening temperature were developed and confirmed.

• Structural Engineering and Mechanics
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• v.47 no.3
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• pp.361-381
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• 2013

A Bayesian probabilistic method is proposed for online estimation of the process noise and measurement noise parameters for Kalman filter. Kalman filter is a well-known recursive algorithm for state estimation of dynamical systems. In this algorithm, it is required to prescribe the covariance matrices of the process noise and measurement noise. However, inappropriate choice of these covariance matrices substantially deteriorates the performance of the Kalman filter. In this paper, a probabilistic method is proposed for online estimation of the noise parameters which govern the noise covariance matrices. The proposed Bayesian method not only estimates the optimal noise parameters but also quantifies the associated estimation uncertainty in an online manner. By utilizing the estimated noise parameters, reliable state estimation can be accomplished. Moreover, the proposed method does not assume any stationarity condition of the process noise and/or measurement noise. By removing the stationarity constraint, the proposed method enhances the applicability of the state estimation algorithm for nonstationary circumstances generally encountered in practice. To illustrate the efficacy and efficiency of the proposed method, examples using a fifty-story building with different stationarity scenarios of the process noise and measurement noise are presented.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.10a
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• pp.87-90
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• 2005

The drawbead is used to control the material flow into the die and increase the forming quality during the binder wrap process and the stamping process in the sheet metal forming. Drawbead restraining force (DBRF) is controlled by geometrical parameters and influenced by process parameters such as friction coefficient and blank thickness. In order to inspect the effect of process parameters, parameter studies are performed with the variation of parameters using finite element model of drawbead which is utilized reliably for the calculation of the drawbead restraining force. Drawbead analysis is carried out with 2-D plane-strain element and 3-D shell element. After the verification of the accuracy of the drawbead model with 3-D shell element, it is utilized to the prediction and the investigation of the effect of process parameters. The result of parameter studies can be utilized to the die design in the tryout stage.

• Fibers and Polymers
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• v.7 no.4
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• pp.424-431
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• 2006

Roll drafting, a mechanical operation attenuating fiber bundles to an appropriate thickness, is an important operation unit for manufacturing staple yams. It influences not only the linear density regularity of the slivers or staple yams that are produced, but also the quality of the textile product and the efficiency of the thereafter processes. In this research, the dynamic states of the fiber bundle in the roll drafting zone were analyzed by simulation, based on the mathematical model that describes the dynamic behavior of the flowing bundle. The state variables are the linear density and velocity of the fiber bundles and we simulated the dynamics states of the bundle flow, e.g., the profiles of the linear density and velocity in the draft zone for various values of the model parameters and boundary conditions, including the initial conditions to obtain their influence on the dynamic state. Results showed that the mean velocity profile of the fiber bundle was strongly influenced by draft ratio and process speed, while the input sliver linear density has hardly affected the process dynamics. Velocity variance of individual fibers that could be supposed to be a disturbing factor in drafting was also influenced by the process speed. But the major disturbance occurred due to the velocity slope discontinuity at the front roll, which was strongly influenced by the process speed. Thickness of input sliver didn't play any important role in the process dynamics.