• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.1
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• pp.33-40
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• 2010

Because sampling interval for data collection tends to be short compared with the overall processing time, in chemical process, instrumental process related tanks or furnace collected data have a significant autocorrelation. Insufficient control technique and frequent control actions cause unstable condition of the process. Traditional control charts which were developed based on iid (independently and identically distributed) among data cannot be applied on the existence of autocorrelation. Also unstable process is difficult to identity or diagnose. Because large-scale process has a lot of measurable variables and multi-step-structures among data, it is difficult to find relation between measurable variables and nonconformity. In this paper, we suggested an appicable model to diagnose the process and to find relation between measurable variables (CTQ) and nonconformity in the process having autocorrelation, unstable condition frequently, a lot of measurable variables, and multi-step-structure. And we applied this model to real process, to verify that the process engineers could easily and effectively diagnose the process and control the nonconformity.

• Journal of Sensor Science and Technology
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• v.30 no.4
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• pp.218-222
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• 2021

Wearable multi-sensors based on nanocrystals have attracted significant attention, and studies on patterning technology to implement such multi-sensors are underway. Conventional patterning processes may affect material properties based on high temperatures and harsh chemical conditions. In this study, we developed an inkjet printing technique that can overcome these drawbacks through the application of patterning processes at room temperature and atmospheric pressure. Nanocrystal-based ink is used to adjust properties efficiently. Additionally, the viscosity and surface tension of the solvents are investigated and optimized to increase patterning performance. In the patterning process, the electrical, electrothermal, and electromechanical properties of the nanocrystal pattern are controlled by the ligand exchange process. Experimental results demonstrate that a multi-sensor with a temperature coefficient of resistance of 3.82 × 10^-3 K^-1 and gauge factor of 30.6 can be successfully fabricated using one-step inkjet printing.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.44-49
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• 2001

This paper is concerned with development of a multi-attribute structured decision model. In this study, we used AHP(analytic hierarchy process) and fuzzy set ranking methodology to overcome the multi-attributes structured decision problems ; such as multi-objective, multi-criterion, and multi-attributes. We proposed a 2-step approach : 1) individual evaluation and 2) integration of individual evaluations. In the first step, we define the performance factors and construct ana]isis structure, and in the second step performance evaluation by individual evaluators, and in second step, the results of individual evaluations are integrate. Also we developed a systematic and practical computer program to solve the problems according to the proposed methods. The proposed approach was known to be effective through a set of sample problems.

• Journal of Powder Materials
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• v.26 no.1
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• pp.11-15
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• 2019

In this study, a method to remove residual powder on a multi-layered graphene and a new approach to transfer multi-layered graphene at once are studied. A graphene one-step transfer (GOST) method is conducted to minimize the residual powder comparison with a layer-by-layer transfer. Furthermore, a residual powder removing process is investigated to remove residual powder at the top of a multi-layered graphene. After residual powder is removed, the sheet resistance of graphene is decreased from 393 to 340 Ohm/sq in a four-layered graphene. In addition, transmittance slightly increases after residual powder is removed from the top of the multi-layered graphene. Optical and atomic-force microscopy images are used to analyze the graphene surface, and the Ra value is reduced from 5.2 to 3.7 nm following residual powder removal. Therefore, GOST and residual powder removal resolve the limited application of graphene electrodes due to residual powder.

• Korean Journal of Computational Design and Engineering
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• v.11 no.5
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• pp.384-392
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• 2006

In this research, the feasibility of distributed finite element analysis system with STEP and CORBA has been investigated. The enabling technologies such as CORBA and Java play key roles in the development of integrated and geographically distributed application software. In addition to the distribution of analysis modules, numerical solution process itself is again divided into parallel processes using multi-frontal method for computational efficiency. In contrast to the specially designed parallel process for specific hardware, CORBA-based parallel process is well suited for heterogeneous platforms over the network. The idea of Web-based distributed analysis system may be applied to the engineering ASP for design and analysis in the product development processes. We believe that the proposed approach for the analysis can be extended to the entire product development process for sharing and utilizing common product data in the distributed engineering environment, thus eventually provide basis for virtual enterprise.

• Korean Journal of Computational Design and Engineering
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• v.8 no.3
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• pp.133-140
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• 2003

This paper describes a Multi-step Digitizing Method and Reverse Model generation algorithm for improvement of reverse engineering accuracy. Reverse engineering is the process of reproducing computational model by directly extracting geometric information on the physical objects. For the improvement of measuring data accuracy, we propose a multi-step digitizing method. First, measuring cloud-of-point by use of a laser scanning system. Second, gathering digitizing data by a scanning touch probe. Fine digitizing plan generated from coarse surface model directly from the cloud-of-point and it allows CMM more accurate scanning data. Finally in this paper we propose the algorithm of generating NURB surface from more accurate measuring points.

• Design & Manufacturing
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• v.17 no.4
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• pp.72-78
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• 2023

Injection molding is a process widely used in various industries because of its high production speed and ease of mass production during the plastic manufacturing process, and the product is molded by injecting molten plastic into the mold at high speed and pressure. Since process conditions such as resin and mold temperature mutually affect the process and the quality of the molded product, it is difficult to accurately predict quality through mathematical or statistical methods. Recently, studies to predict the quality of injection molded products by applying artificial neural networks, which are known to be very useful for analyzing nonlinear types of problems, are actively underway. In this study, structural optimization of neural networks was conducted by applying multi-task learning techniques according to the characteristics of the input and output parameters of the artificial neural network. A structure reflecting the characteristics of each process step was applied to the input parameters, and a structure reflecting the quality characteristics of the injection molded part was applied to the output parameters using multi-tasking learning. Building an artificial neural network to predict the three qualities (mass, diameter, height) of injection-molded product under six process conditions (melt temperature, mold temperature, injection speed, packing pressure, pacing time, cooling time) and comparing its performance with the existing neural network, we observed enhancements in prediction accuracy for mass, diameter, and height by approximately 69.38%, 24.87%, and 39.87%, respectively.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.12
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• pp.2055-2067
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• 1997

Values of process parameters in sheet metal forming can be estimated by various one-step inverse methods. One-step inverse methods based on deformation theory, however, cause some amount of error. The amount of error is generally increased as the deformation path becomes more complex. As a remedy, a new three dimensional multi-step inverse method is introduced for optimum design of blank shapes and strain distributions from desired final shapes. The approach extends a one-step inverse method to a multi-step inverse method in order to reduce the amount of error. The algorithm developed is applied to square cup drawing to confirm its validity by demonstrating reasonably accurate numerical results. Rapid calculation with this algorithm enables easy determination of an initial blank of sheet metal forming.

• International Journal of Precision Engineering and Manufacturing
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• v.2 no.2
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• pp.65-72
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• 2001

The design of multi-stage gear drives is a time-consuming process, since on includes more complicated problems, which are not considered in the design of single-stage gear drives. The designer has th determine the number of reduction stages and the gear ratios of each reduction state. In addition, the design problems include not only the dimensional design but also the configuration design of gear drive elements. There is no definite rule and principle for these types of design problems. Thus the design practices largely depend on the sense and the experiences of the designer , and consequently result in undesirable design solution. We propose a new generalized design algorithm to support the designer at the preliminary design phase of multi-stage gear drives. The proposed design algorithm automates the design process by integrating the dimensional design and the configuration design process. The algorithm consists of four steps. In the first step, a designer determines the number of reduction stage. In the second step. gear ratios se chosen by using the random search method. In the third step, the values of basic design parameter are chosen by using the generate and test method. Then, the values of other dimension, such ad pitch diameter, outer diameter, and face width, are calculated for the configuration design in the final step. The strength and durability of a gear is guaranteed by the bending strength and the pitting resistance rating practices by using the AGMA rating formulas. In the final step, the configuration design is carried out b using the simulated annealing algorithm. The positions of gears and shafts are determined to minimize the geometrical volume(size) of a gearbox, while satisfying spatial constraints between them. These steps are carried out iteratively until a desirable solution is acquired. The propose design algorithm has been applied to the preliminary design of four-stage gear drives in order to validate the availability. The design solution have shown considerably good results in both aspects of the dimensional and the configuration design.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.94-99
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• 2001

Theoretical analysis using finite element method are peformed in order to clarify the formation of the flare-shape defect for multi-step tube sinking process. The parameters of concern were the friction between the tube and the die, and geometrical parameters, such as the die inclination angle, the diameters of the die entrance and exit, and the curvature at the corner of the die exit. The effect of the curvature at the comer of the die exit is dominant for determining the flare-shape defect. In order to minimize the flare-shape defect the curvature at the corner of the die exit should be increased up to a certain level(120mm). Using three-step tube sinking die sets which have different curvatures at the comer of the die exit, several numbers of tests were performed and its results are compared with that of theoretical analysis.