• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.6
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• pp.34-40
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• 2000

• Advances in nano research
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• v.12 no.2
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• pp.151-165
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• 2022

Micro-scale serpentine structure fibers are widely used as flexible sensor in the manufacturing of micro-nano flexible electronic devices because of their outstanding non-linear mechanical properties and organizational flexibility. The use of melt electrowriting (MEW) technology, combined with the axial bending effect of the Taylor cone jet in the process, can achieve the micro-scale serpentine structure fibers. Due to the interference of the process parameters, it is still challenging to achieve the precise deposition of micro-scale and high-consistency serpentine structure fibers. In this paper, the micro-scale serpentine structure fiber is produced by MEW combined with axial bending effect. Based on the controlled deposition of MEW, applied voltage, collector speed, nozzle height and nozzle diameter are adjusted to achieve the precise deposition of micro-scale serpentine structure fibers with different morphologies in a single motion dimension. Finally, the influence mechanism of the above four parameters on the precise deposition of micro-scale serpentine fibers is explored.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.3
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• pp.61-66
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• 2008

For the production of urethane prepolymer, the effect of process parameters such as diisocyanate MDI and polyol TDI was tested. In this paper, design of experiments has been adopted for studying the effect of the process parameters on the improvement of NCO and viscosity of pre-polymer. As a result of comparison of different parameters, the effect of polyol was stronger than that of isocyanate in comparison of reactivity according to the amounts of isocyanate and polyol. Especially, NCO and viscosity of pre-polymer affected a product safety.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.6
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• pp.57-63
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• 1998

An adaptive control in the robotic GMA welding is employed to monitor information about weld characteristics and process parameters as well as to modify those parameters to hold weld quality within acceptable limits. Typical characteristics are the bead geometry, composition, microstructure, appearance, and process parameters which govern the quality of the final weld. The main objectives of this thesis are to realize the mapping characteristics of bead width through learning. After learning, the neural estimation can estimate the bead width desired form the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) are chosen from an estimation error analysis. A series of bead of bead-on-plate GMA welding experiments was carried out in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the bead width with reasonable accuracy and guarantee the uniform weld quality.

• 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.3 no.4
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• pp.13-19
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• 2004

This paper deals with the analysis of geometric error and the optimization of process parameters in surface grinding. Taguchi method which is one of the design of experiments has been introduced in achieving the aims. The process parameters were the grain size, the wheel speed, the depth of cut and the table speed. The effect of the process parameters on the geometric error was examined and an optimal set of the parameters was selected to minimize the geometric error within the controllable range of the used grinding machine. The reliability of the results was evaluated by the ANOVA.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.7
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• pp.43-52
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• 2022

Design of a controller for a high-precision servo control system has been a popular topic while finding optimal parameters for multiple controllers is still a challenging subject. In this paper, we propose a practical scheme to optimize multi-parameters for the robust servo controller design by introducing a new cost function and optimization scheme. The proposed design method provides a simple and practical tool for the systematic servo design to reduce the control error with guaranteeing robust stability of the overall system. The reduction of the position error by 24% along with a faster convergence rate is demonstrated using a typical hard disk drive servo controller with 41 parameters.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.1
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• pp.114-120
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• 2010

Optimization of the turning process has been concentrated on the selection of the optimal cutting parameters, such as cutting speed, feed rate and depth of cut. However, optimization of the cutting parameters does not necessarily guarantee the maximum profit. For the maximization of the profit, parameters other than cutting parameters have to be taken care of. In this study, 8 price-related parameters were considered to maximize the profit of the product. Regression equations obtained from RSM technique to relate the cutting parameters and maximum cutting volume with a given insert were used. The experiments with four combinations of cutting inserts and material were executed to compare the results that made the profit and cutting volume maximized. The results showed that the cutting parameters for volume and profit maximization were totally different. Contrary to our intuition, global optimization was achieved when the number of inserts change was larger than those for volume maximization. It is attributed to the faster cutting velocity, which decreases processing time and increasing the number of tool used and the total tool changing time.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.1
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• pp.54-61
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• 2011

Ball screw systems are largely used in industry for motion control and motor applications. But the problem of noise, which really perplexes us, is highly correlated with the quality in ball screw systems all the way. In this paper, machining process parameters were evaluated in respects of technique, business, produce and quality to verify which impact influences the noise most. In order to adjust and compare, two comparison groups were set with the present parameters bench mark. Different ball screws were produced as specimens for the noise tests. Through comparing the noise performance of different parameters in the machining process respectively, a group of optimized machining process parameters were obtained. Another noise test was proceeded to know how noise performance was improved by optimizing the machining process parameters. At last, surface roughness tests have been done to know how surface roughness improved by optimization. The improvement of surface roughness is the main factor influences the noise performances.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.4
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• pp.223-231
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• 2022

Residual stress that can occur during the metal additive manufacturing process is an important factor that must be properly controlled for the precise production of metal parts through 3D printing. Therefore, in this study, the factors affecting these residual stresses were investigated using an experimental method. For the experiment, a specimen was manufactured through an additive manufacturing process, and the amount of deformation was measured by cutting it. By appropriately calibrating the measured data using methods such as curve fitting, it was possible to quantitatively analyze the effect of process parameters and metal powder reuse on deformation due to residual stress. From this result, it was confirmed that the factor that has the greatest influence on the magnitude of deformation due to residual stress in the metal additive manufacturing process is whether the metal powder is reused. In addition, it was confirmed that process parameters such as laser pattern and laser scan angle can also affect the deformation.