• Journal of the Korean Institute of Gas
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• v.16 no.6
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• pp.41-47
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• 2012

There are PFD(Process Flow Diagram) and P&ID(Piping and Instrument Diagram) for designing and managing chemical process efficiently. They provide the operation condition and equipment specifications of chemical process, but they do not provide the reliability of chemical process. Therefore, in this study, Reliability Flow Diagram(RFD) which provide the cycle and time of preventive maintenance has been developed using Directed Graph Analysis methodology. Directed Graph Analysis methodology is capable of assessing the reliability of chemical process. It models chemical process into Directed Graph with nodes and arcs and assesses the reliability of normal operation of chemical process by assessing Directed Graph sequential. In this paper, the chemical process reliability transition according to operation time was assessed. And then, Reliability Flow Diagram has been developed by inserting the result into P&ID. Like PFD and P&ID, Reliability Flow Diagram provide valuable and useful information for the design and management of chemical process.

• The Korean Journal of Applied Statistics
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• v.34 no.1
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• pp.99-114
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• 2021

With the Fourth Industrial Revolution based on new technology, the semiconductor manufacturing industry researches various analysis methods such as detecting process abnormalities and predicting yield based on equipment sensor data generated in the manufacturing process. The semiconductor manufacturing process consists of hundreds of processes and thousands of measurement processes associated with them, each of which has properties that cannot be defined by chemical or physical equations. In the individual measurement process, the actual measurement ratio does not exceed 0.1% to 5% of the target product, and it cannot be kept constant for each measurement point. For this reason, efforts are being made to determine whether to manage by using equipment sensor data that can indirectly determine the normal state of each step of the process. In this study, the Functional Data Analysis (FDA) was proposed to define a process abnormality detection process based on equipment sensor data and compensate for the disadvantages of the currently applied statistics-based diagnosis method. Anomaly detection accuracy was compared using machine learning on actual field case data, and its effectiveness was verified.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.5
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• pp.521-528
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• 2017

In the combustion treatment of explosive gases with a high heating value such as $H_2$ and $NH_3$ used in semiconductor and chemical processes, the heat recovery modeling and exergy analysis of the process using the Aspen Plus simulator and its thermodynamic data were performed to examine the recovery of high temperature thermal energy. The heat recovery process was analyzed through this process modeling while the exergy results clearly confirmed that the rigorous reaction mainly occurs in the condenser and the chamber. In addition, the process modeling demonstrated that approximately 95% of the exergy is destructed on the basis of the exergies injected and the exergy being exhausted. Using the exergy technique, which can quantitatively analyze the energy, we could understand the energy flow in the process and confirm that our heat recovery process was efficiently designed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.126-134
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• 2019

Nowadays, since there are so many big data available everywhere, those big data can be used to find useful information to improve design and operation by using various analysis methods such as data mining. Especially if we have event log data that has execution history data of an organization such as case_id, event_time, event (activity), performer, etc., then we can apply process mining to discover the main process model in the organization. Once we can find the main process from process mining, we can utilize it to improve current working environment. In this paper we developed a new method to find a final diagnosis of a patient, who needs several procedures (medical test and examination) to diagnose disease of the patient by using process mining approach. Some patients can be diagnosed by only one procedure, but there are certainly some patients who are very difficult to diagnose and need to take several procedures to find exact disease name. We used 2 million procedure log data and there are 397 thousands patients who took 2 and more procedures to find a final disease. These multi-procedure patients are not frequent case, but it is very critical to prevent wrong diagnosis. From those multi-procedure taken patients, 4 procedures were discovered to be a main process model in the hospital. Using this main process model, we can understand the sequence of procedures in the hospital and furthermore the relationship between diagnosis and corresponding procedures.

• The Journal of Society for e-Business Studies
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• v.3 no.2
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• pp.179-202
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• 1998

This study reviews the concept of Integrated Logistic Support(ILS), ILS standards, ILS elements, and the processes of developing ILS elements and Logistics Support Analysis(LSA). It also examines the potentials of applying ILS development process to building CALS systems in commercial sectors in order to accomplish business process innovation and achieve life-cycle cost savings in product and equipment management. In order to utilize the ILS approach for commercial industries, we need customizing the process of Logistics Support Analysis defined in MIL-STD-1388-lA. The success of ILS implementation depends on the determination of the range of ILS elements in relation with the application environment, and the appropriate development of those elements. During the development process, in order to analyze and design logistics flow processes and supporting activities, we suggest the object-oriented logistics process modeling approach with basic concepts and constructs embedded in objects. Several diagrams including Class Diagram, Class-Instance Diagram, and Integrated Instance Diagram, are provided. Simple Steps to follow are suggested for the analysis and design of inter-organizational logistics flow and support processes. The outcomes of the study are expected to contribute to stimulating the utilization of ILS concepts and development process during building commercial CALS systems.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.5
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• pp.30-35
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• 2008

As the quality of a weld feint is strongly influenced by process parameters during the welding process, an intelligent algorithms that can predict the bead geometry and shape to accomplish the desired mechanical properties of the weldment should be developed. This paper focuses on the development of mathematical models fur the selection of process parameters and the prediction of bead geometry(bead width, bead height and penetration) in robotic GMA(Gas Metal Arc) welding. Factorial design can be employed as a guide for optimization of process parameters. Three factors were incorporated into the factorial model: arc current, welding voltage and welding speed. A sensitivity analysis has been conducted and compared the relative impact of three process parameters on bead geometry in order to verify the measurement errors on the values of the uncertainty in estimated parameters. The results obtained show that developed mathematical models can be applied to estimate the effectiveness of process parameters for a given bead geometry, and a change of process parameters affects the bead width and bead height more strongly than penetration relatively.

• Design & Manufacturing
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• v.17 no.3
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• pp.34-40
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• 2023

In this study, real-time collection of mold vibration signals during injection molding processes was achieved through IoT devices installed on the mold surface. To analyze changes in the collected vibration signals, injection molding was performed under six different process conditions. Analysis of the mold vibration signals according to process conditions revealed distinct trends and patterns. Based on this result, cosine similarity was applied to compare pattern changes in the mold vibration signals. The similarity in time and acceleration vector space between the collected data was analyzed. The results showed that under identical conditions for all six process settings, the cosine similarity remained around 0.92±0.07. However, when different process conditions were applied, the cosine similarity decreased to the range of 0.47±0.07. Based on these results, a cosine similarity threshold of 0.60~0.70 was established. When applied to the analysis of mold vibration signals, it was possible to determine whether the molding process was stable or whether variations had occurred due to changes in process conditions. This establishes the potential use of cosine similarity based on mold vibration signals in future applications for real-time monitoring of molding process changes and anomaly detection.

• Proceedings of the Korean Society for Quality Management Conference
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• 2010.04a
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• pp.226-234
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• 2010

In this thesis, we present process that remove mistake of data before statistical analysis. If field data which is not simple examination about validity of data, we cannot believe analyzed statistics information. As statistical analysis information is produced based on data to be input in statistical analysis process, the data to be input should be free of error. In this paper, we study the application of statistical analysis road map that can enhance application on site by organizing basic theory and approaching on initial data exploratory phase, essential step before conducting statistical analysis. Therefore, access to statistical analysis can be enhanced and reliability on result of analysis can be secured by conducting correct statistical analysis.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2008.10a
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• pp.226-229
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• 2008

Hot press forming is an advanced forming technology fur manufacturing of complex and crash-resistant automotive parts using ultra high strength steels. The 3-dimensional FE analysis of hot press forming process, in which process the deformation, heat transfer and phase transformation behavior are fully coupled, is carried out. The vast amount of material properties for the FE analysis is obtained from material properties calculation software which is based on thermodynamic calculations. The overall methodology for the FE analysis of HPF process and the analysis results are discussed here.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2001.11a
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• pp.45-53
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• 2001

Copper bus-bar is made by drawing process and used in many part of industry. When design drawing die for copper bus-bar, design factor is focused on the deformation of die-land by drawing force and shrink fit. In this paper, to determine shrink fit value is analyzed by automatic shrink fit analysis program, APDL/UIDL language in a commercial FEM package, ANSYS, has been developed that enables optimal design of the dies taking into account the elastic deflections generated in shrink fitting the die inserts and that caused by the stresses generated in the process and by using DEFORM software for drawing process analysis. This data can be processed as load input data for a finite element die-stress analysis. Process simulation and stress analysis are thus combined during the drawing die design. The stress analysis of the dies is used to determine optimized dimension of die-land.