• JSTS:Journal of Semiconductor Technology and Science
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• v.8 no.3
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• pp.179-192
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• 2008

A multiphase compensation method with mismatch linearization technique, is presented and demonstrated in a $\Sigma-\Delta$ fractional-N frequency synthesizer. An on-chip delay-locked loop (DLL) and a proposed delay line structure are constructed to provide multiphase compensation on $\Sigma-\Delta$ quantizetion noise. In the delay line structure, dynamic element matching (DEM) techniques are employed for mismatch linearization. The proposed $\Sigma-\Delta$ fractional-N frequency synthesizer is fabricated in a $0.18-{\mu}m$ CMOS technology with 2.14-GHz output frequency and 4-Hz resolution. The die size is 0.92 mm$\times$1.15 mm, and it consumes 27.2 mW. In-band phase noise of -82 dBc/Hz at 10 kHz offset and out-of-band phase noise of -103 dBc/Hz at 1 MHz offset are measured with a loop bandwidth of 200 kHz. The settling time is shorter than $25{\mu}s$.

• Design & Manufacturing
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• v.12 no.2
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• pp.27-33
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• 2018

Korea's automobile industry, which has grown rapidly to become the world's fifth-largest automobile producer, To cope with environmental pollution and energy problems in order to prevail competitive edge in global market We are investing a lot of research personnel and costs. Among them, for realizing alternative light weight It is a part of the automobile module system that has achieved the technological development before the breakthrough in the injection molding process in the press process. Door module PNL was the subject of research. The door module PNL is expected to cause warpage before the mold production due to the thin and flat product characteristics and fiber orientation characteristic of the material. In this paper, CAE analysis and reverse correction tool Design. CAE analysis to obtain the results of weld line position, bending position and deformation value Through the correction tool, think3, the original product was modified before the mold production to improve the completeness of the parts. In fiber orientation, the position and size of the cooling channel in the mold, the position and size of the gate, Temperature, pressure, time, and work environment. Compared with the result of CAE analysis, the product that was reverse-corrected by Think3 was manufactured, and injection molding was performed. Injection molding products were tested 24 hours later. 3.5 mm to 7.0 mm, and under the fixed condition, the deviation was from 1.1 mm to 1.5 mm. Unlike the CAE analysis, the deviation of the actual injection pressure and the cooling temperature, the fiber orientation of the material, In order to solve this problem, it is necessary to compare the injection conditions with the database, I knew I had to catch the standard.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5B
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• pp.974-984
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• 2000

A CMOS voltage driver circuit for voltage down converter is proposed. An adaptive biasing technique is used to enhance load regulation characteristics. The proposed driver circuit uses the NMOS transistor as a driving transistor, so it does not suffer from large Miller capacitances which is one of the problems with conventional PMOS driving transistor, and hence achieves good phase margin and stable frequency response. No additional complex circuit for frequency compensation such as compensation capacitor is required in this implementation. For the same current capability, the size of NMOS transistor in driver circuit is smaller than that of PMOS counterpart. So the smaller die area can be achieved. The circuits is implemented using a 0.8 ${\mu}{\textrm}{m}$ CMOS process and has a die area of 150 ${\mu}{\textrm}{m}$ x 360 ${\mu}{\textrm}{m}$. Proposed circuit has a quiescent power of 60 . In the current driving range from 100 $mutextrm{A}$ to 50 ㎃, load regulation of 5.6 ㎷ is measured.

• Journal of IKEEE
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• v.9 no.1 s.16
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• pp.40-46
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• 2005

A process variation compensation method called 'regulated drain detection' is proposed. This paper also shows the how this newly invented method is applied to a typical differential PLL. The proposed RDD(regulated drain detection) and its PLL application has been designed and tested in a $0.18{\mu}m$ 1-poly 3-metal plain digital process so that its stable performance and higher yield can be proven. The implemented PLL aimed to the operation range of 80MHz - 240MHz and the total die size is only $0.18{\mu}m$ including the internal loop filter. The tracking jitter characteristics is measured to less than 150 peak-to-peak under l.8V supply rail.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.9 s.186
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• pp.134-141
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• 2006

Surface deflections have a great effect on the external appearance of automobiles. Usually, they are occurred on large flat panels containing sudden shape changes and of very small size about $\pm$30$\sim$300$\mu$m. Since the current numerical method is not sufficient for predicting these defects, the correction of these defects still depends on trial and error, which requires a great deal of time and expense. Consequently, developing the numerical method to predict and prevent these defects is very important far improving cosmetic surface qualities. In this study, an evaluation system that can analyze surface deflections using numerical simulation and a visualization system are reported. To calculate the surface deflections numerically, robust algorithms and simulation methodologies are suggested and to visualize them quantitatively, the curvature variation algorithm is proposed. To verify the developed systems, the experimental die of the handle portion of exterior door is analyzed. The results showed that the experimental and simulational visualization are in good agreement. Compensation methods to correct the surface deflections are also tested. The evaluation system proposed in this paper could be used to predict and minimize the occurrence of surface deflections in die manufacturing.

• Transactions of Materials Processing
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• v.22 no.8
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• pp.477-485
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• 2013

This paper aims to evaluate quantitatively the springback characteristics that evolve in the sheet metal forming of an S-rail in order to understand the reasons of shape inaccuracy and to find a remedy. The geometrical springback is classified into six modes: angle change of punch and die shoulders, wall curl, ridge curl, section twist, and axial twist. The measuring method for each springback mode is suggested and quantitative measurements were made to determine the tendency towards shape accuracy. Forming experiments were conducted with four types of steel sheets that have different tensile strengths, which were 340MPa, 440MPa, 590MPa and 780MPa, in order to evaluate the effect of the tensile strength and the bead shape on the springback behavior. Springback tendencies show that they are greatly affected by the tensile strength of the sheet and the shape of the tools. Almost all springback modes except the section twist and the axial twist show a linearly increasing trend as the tensile strength of the sheet increases. The results can be used as basic data for design and for compensation of the press die geometry when forming high strength steels which exhibit large amounts of springback.

• Transactions of Materials Processing
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• v.21 no.8
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• pp.479-484
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• 2012

The objective of this study is to compensate the elastic recovery in the flexible forming process using the predictive models. The target shape was limited to two-dimensional shape having only one curvature radius in the longitudinal-direction. In order to predict the shape error the regression and neural network models were established based on the finite element (FE) simulations. A series of simulations were conducted considering input variables such as the elastic pad thickness, the thickness of plate, and the objective curvature radius. Then, at sampling points in the longitudinal-direction, the shape errors between formed and objective shapes could be calculated from the FE simulations as an output variable. These shape errors were expressed to a representative error value by the root mean square error (RMSE). To obtain the correct objective shape the die shape was adjusted by the closed-loop using the neural network model since the neural network model shows a higher capability of estimating the shape error than the regression model. Finally the experimental result shows that the formed shape almost agreed with the objective shape.

• Transactions of Materials Processing
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• v.10 no.3
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• pp.206-213
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• 2001

Dynamic deformation of metallic materials mostly accompanies substantial amounts of deformation heat. Since the flow stress of deformation is sensitive to temperature, implication of heat due to plastic work is essential to the evaluation of constitutive relations. In this study, a series of compression tests were conducted for SAF 2507 super duplex stainless steel at various temperatures and strain rates. The accumulation of plastic work was calculated through numerical integration and converted into the elevation of temperature. Subsequent logarithmic interpolation deduced isothermal flow surfaces, which were primary input data of finite element analysis. Simple closed die forging process was analyzed and optimized with commercial FEM code applying both raw and calibrated material database. The effect of accounting deformation heat was more noticeable in high-speed forming process.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.1044-1048
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• 1997

Wire-cut EDM is used in Die manufacturing as the part of non-traditional cutting process, But,the determination of it's cutting condition with high efficiency and precision is difficult due to the influence of cutting environment and cutting mechanism. In this study, we examine the cutting performance of the SKD11 and Brass in wire-cut EDM and make the neural network which have the configuration of 5-12-2 and back-propagation learning rule. Through the neural network, we can appraise the cutting performance before working and determine the optimal cutting condition. By introducing this method to the W-cut EDM, we can enhance the cutting efficiency.

• Design & Manufacturing
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• v.14 no.1
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• pp.8-14
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• 2020

In general, auto parts production assembly line is assembled and produced by automatic mounting by an automated robot. In such a production site, quality problems such as misalignment of parts (doors, trunks, roofs, etc.) to be assembled with the vehicle body or collision between assembly robots and components are often caused. In order to solve such a problem, the quality of parts is manually inspected by using mechanical jig devices outside the automated production line. Automotive inspection technology is the most commonly used field of vision, which includes surface inspection such as mounting hole spacing and defect detection, body panel dents and bends. It is used for guiding, providing location information to the robot controller to adjust the robot's path to improve process productivity and manufacturing flexibility. The most difficult weighing and measuring technology is to calibrate the surface analysis and position and characteristics between parts by storing images of the part to be measured that enters the camera's field of view mounted on the side or top of the part. The problem of the machine vision device applied to the automobile production line is that the lighting conditions inside the factory are severely changed due to various weather changes such as morning-evening, rainy days and sunny days through the exterior window of the assembly production plant. In addition, since the material of the vehicle body parts is a steel sheet, the reflection of light is very severe, which causes a problem in that the quality of the captured image is greatly changed even with a small light change. In this study, the distance between the car body and the door part and the door are acquired by the measuring device combining the laser slit light source and the LED pattern light source. The result is transferred to the joint robot for assembling parts at the optimum position between parts, and the assembly is done at the optimal position by changing the angle and step.