• Proceedings of the Korea Society for Industrial Systems Conference
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• 1998.10a
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• pp.613-622
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• 1998

This study investigates the factors that affect the adoption of object orientation . One major research question is addressed : What are the factors that significantly influeence the adoption of object orientation ? This study especially explores the impact of independent variables on the level of actual usage of object orientation. The independent variables are classified into four categories as follow ; (1) Individual factors : amount of experience in using the structures methods and level of openness toward new technologies ; (2) Managerical factors : perceived management support and training : (3) Organizatinal factors : number of IS professionals in the working group and that in organization ; and (4) Environmental factors ; accessibility to technology champions and software hardware environment supporting object orientation. A Questionnaire measuring the above variables was utilized to investigate the effect of these variables on the dependent variable, the actual usage of object orientation. The structured questionnaire was administered to Data Processing Management Association (DPMA) professionals in U. S. The results of this study revealed several important findings with most results being consistent with expectations based on related theory. The personal openness toward new technologies, perceived management support, training, and hardware/software environment were highly related to the usage of object orientation. This study suggested an empiriclal basis for understanding the early adoption of object orientation in organization.

• Transactions of Materials Processing
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• v.14 no.1 s.73
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• pp.37-42
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• 2005

In order to invstigate the influence of die design variables on the quality of the sheared surface in cutting of sandwich sheet metals, the cut-off operation is carried out, which is the typical shearing process in sheet metal forming technology. For experiments we made the cut-off die which can be easily adjusted for die design variables such as blankholding force, pad force and clearance. The sandwich sheet metals considered are clad304(STS304-Al1050-STS304) and anti-vibration sheet metal. The shearing process is visualized by the computer vision system installed in front of the cut-off die and the sheared surface is measured and quantitatively compared with the help of the optical microscope after cut-off operation. From test results it is shown that the shearing mechanisms are different according the material of which sandwitch sheet metal is composed. The influence of die design variable is explored and we found optimal conditions for both sandwich sheet metals. It is expected that this investigation can be utilized to get the better sheared surface.

• Korean Journal of Food Science and Technology
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• v.24 no.6
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• pp.524-527
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• 1992

To measure of important variables such as temperature, weight, and relative humidity in food processing process, computer-aided data acquisition system was composed of 16 bit microcomputer and PCL-711S interface board. Process variables in dehydration and storage of food were measured through sensors, converters, and computer system which were operated by the PC-LabDAS software for data acquisition, process control, and data analysis. The relationship between measured values of process variables and the output voltages of ADC showed more than 0.99 in $r^2$ value. Response time of sensors was enough fast to measure minute values changed in a moment.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.6
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• pp.579-587
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• 2015

Semiconductor manufacturing industry is a high density integration industry because it generates a vest number of data that takes about 300~400 processes that is supervised by numerous production parameters. It is asked of engineers to understand the correlation between different stages of the manufacturing process which is crucial in reducing production costs. With complex manufacturing processes, and defect processing time being the main cause. In the past, it was possible to grasp the corelation among manufacturing process stages through the engineer's domain knowledge. However, It is impossible to understand the corelation among manufacturing processes nowadays due to high density integration in current semiconductor manufacturing. in this paper we propose a canonical correlation analysis (CCA) using both wafer test voltage variables and fail bit counts variables. using the method we suggested, we can increase the semiconductor yield which is the result of the package test.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.4
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• pp.37-42
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• 2001

This paper resents a biological reaction model of describing processing features in treating wastewater via activated sludge A proposed model is designed by combining fuzzy rules investigating several elements which have influence on variables to be supervised BOD and SS are suggested as common variables in input and output variables, and O$_2$quantity is closed as input variable. We chose triangular type membership functions for input variables and determined the grades in each membership function based upon process data According to simulation result to show the validity of proposed model, fuzzy model's outputs give almost similar data to process output under same input conditions.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.3
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• pp.154-163
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• 2010

Process monitoring of output variables affecting final performance have been mainly executed in semiconductor manufacturing process. However, even earlier detection of causes of output variation cannot completely prevent yield loss because a number of wafers after detecting them must be re-processed or cast away. Semiconductor manufacturers have put more attention toward monitoring process inputs to prevent yield loss by early detecting change-point of the process. In the paper, we propose the method to efficiently monitor functional input variables in multi-phase semiconductor manufacturing process. Measured input variables in the multi-phase process tend to be of functional structured form. After data pre-processing for these functional input data, change-point analysis is practiced to the pre-processed data set. If process variation occurs, key variables affecting process variation are selected using contribution plot for monitoring efficiency. To evaluate the propriety of proposed monitoring method, we used real data set in semiconductor manufacturing process. The experiment shows that the proposed method has better performance than previous output monitoring method in terms of fault detection and process monitoring.

• The KIPS Transactions:PartD
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• v.15D no.6
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• pp.777-784
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• 2008

Recently in the field of model checking, to overcome the state explosion problem, the method of using a SAT-solver is mainly researched. To use a SAT-solver, the system to be verified is translated into CNF and the Boolean cardinality constraint is widely used in translating the system into CNF. In BCC it is dealt with set of boolean variables, but there is no translating method of the sequence among Boolean variables. In this paper, we propose methods for translating the problem, which is extracting a subsequence with length k from a sequence of Boolean variables, into CNF formulas. Through experimental results, we show that our method is more efficient than using only BCC.

• 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.

• The KIPS Transactions:PartD
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• v.16D no.3
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• pp.371-380
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• 2009

Recently, lots of research on automated test data generation has been actively done. However, techniques for automated test data generation presented so far have been proved ineffective for programs with flag variables. It can present problems when considering embedded systems such as engine controllers that make extensive use of flag variables to record state information concerning devices. This paper introduces a technique for generating test data effectively for programs with flag variables. The presented technique transforms the test data generation problem into a SAT(SATisfiability) problem and makes advantage of SAT solvers for automated test data generation(ATDG). For the ends, we transform a program under test into Alloy which is the first-order relational logic and then produce test data via Alloy analyzer.

• Transactions of Materials Processing
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• v.28 no.3
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• pp.159-166
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• 2019

Electromagnetic forming (EMF) simulations consider 3-dimensionally coupled electromagnetic-mechanical phenomenon using LS-DYNA, therefore the calculation cost is normally expensive. In this study, a sensitivity analysis in regard to the simulation variables affecting the calculation time was carried out. The EMF experiments were conducted to form an elliptically protruding shape on a high-strength steel sheet, and it was predicted using LS-DYNA simulation. In this particular EMF simulation case, the effect of several simulation variables, viz., element size, contact condition, EM-time step interval, and re-calculation number of the EM matrices, on the shape of elliptical protrusion and the total calculation time was analyzed. As a result, reasonable values of the simulation variables between the simulation precision and calculation time were proposed, and the EMF experiments with respect to the charging voltages were successfully predicted.