• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.902-905
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• 2000

As the manufacturing processes of automotive engine piston, gravity die-casting, squeeze casting, hot forging and powder forging process are generally used for the various specifications. As the semi-solid forming(SSF) is compared with conventional casting such as gravity die-casting and squeeze casting for the characteristics of its process, the product without inner defects such as gas porosity and segregation can be obtained and its microstructure is globular grain. In SSF process, the materials are heated up to the temperature between the solvus and liquidus line at which the materials exists in the form of liquid-solid mixture. In this time, Discussion is given about reheating process of row material and results are presented regarding accurate temperature and process variables controlling for right solid fractions.

• Journal of Electrochemical Science and Technology
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• 제10권1호
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• pp.14-21
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• 2019

Supported liquid membrane process usually is used for recovering or enrichment of valuable metals in the industrial wastewater. But, even if the metals in the wastewater was separated with high chemical selectivity, it cannot be enough concentrated since separation performance of supported liquid membrane (SLM) process is limited by concentration gradient between feed solution and stripping solution. If metal concentration in the stripping solution to be enough low, transport of metal through membrane can be accomplishment constantly. Therefore, Electrodialysis (ED) has been placed after SLM process and the stripping solution of SLM was used as the feed solution for the ED process. Transport of ions in the solutions is successfully performed by ED process. Thus, the metal concentration in the stripping solution does not rise as to stop ion transport. Besides, valuable metals easily are concentrated by ED process for re-use. In this study, effects of operation parameters like initial Cd(II) concentration, HCl concentration in the feed solution of SLM and applied voltage are investigated on separation efficiency, flux and permeability of the both processes. As the feed solution concentration increased, all performance values has increased. When initial concentration of 100 mg/L is used, separation performances (SP) are 55% and 70%, for SLM and consecutive process, respectively. The best HCl concentration in the feed solution of SLM has determined as 2 M, in this conditions SP are 64% and 72%, for SLM and consecutive process, respectively. With increased of applied voltage on ED process, SP of the consecutive process has been raised from 72% to 83%. According to the obtained experimental data, consecutive process has better separation performance than SLM. When the separation performances of both processes were compared for the same operating conditions, it was determined higher the separation efficiency, permeability and flux values of the consecutive process, 8%, 9% and %10.6, respectively. Consequently, the use of the consecutive process increases the performance efficiency of both processes. The consecutive process studied has quite a good chemical separation efficiency, and enrichment capability. Moreover, this process requires few water and energy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권8호
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• pp.2316-2332
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• 2024

In this paper, we introduce a web-based system that leverages the capabilities of the ρ(rho)-algorithm, which is a Structure Information Control Net (SICN)-oriented process mining algorithm, with open-source platforms, including Django, Graphviz, and Cytoscape, to facilitate the rediscovery and visualization of business process models. Our approach involves discovering SICN-oriented process models from process instances from the IEEE XESformatted process enactment event logs dataset. This discovering process is facilitated by the ρ-algorithm, and visualization output is transformed into either a JSON or DOT formatted file, catering to the compatibility requirements of Cytoscape or Graphviz, respectively. The proposed system utilizes the robust Django platform, which enables the creation of a userfriendly web interface. This interface offers a clear, concise, modern, and interactive visualization of the rediscovered business processes, fostering an intuitive exploration experience. The experiment conducted on our proposed web-based process discovery system demonstrates its ability and efficiency showing that the system is a valuable tool for discovering business process models from process event logs. Its development not only contributes to the advancement of process mining but also serves as an educational resource. Readers, students, and practitioners interested in process mining can leverage this system as a completely free process miner to gain hands-on experience in rediscovering and visualizing process models from event logs.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2003년도 하계학술대회 논문집 Vol.4 No.1
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• pp.370-373
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• 2003

As the integrated circuit device shrinks to the smaller dimension, the chemical mechanical polishing (CMP) process was required for the global planarization of inter-metal dielectric(IMD) layer with free-defect. However, as the IMD layer gets thinner, micro-scratches are becoming as major defects. Chemical-Mechanical Planarization(CMP) of conductors is a key process in Damascene patterning of advanced interconnect structure. The effect of alternative commerical slurries pads, and post-CMP cleaning alternatives are discuess, with removal rate, scratch dentisty, surface roughness, dishing, erosion and particulate density used as performance metrics. Electroplated copper depostion is a mature process from a historical point of view, but a very young process from a CMP persperspective. While copper electrodepostion has been used and stuidied for dacades, its application to Cu damascene wafer processing is only now ganing complete accptance in the semiconductor industry. The polishing mechanism of Cu CMP process has been reported as the repeated process of passive layer formation by oxidizer and abrasion action by slurry abrasives. however it is important to understand the effect of oxidizer on copper pasivation layer in order to obtain higher removal rate and non-uniformity during Cu-CMP process. In this paper, we investigated the effects of oxidizer on Cu-CMP process regarding the additional volume of oxidizer.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2004년도 하계학술대회 논문집 Vol.5 No.1
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• pp.20-23
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• 2004

As the integrated circuit device shrinks to the smaller dimension, the chemical mechanical polishing(CMP) process was required for the global planarization of inter-metal dielectric(IMD) layer with free-defect. However, as the IMD layer gets thinner, micro-scratches are becoming as major defects. Chemical-Mechanical polishing(CMP) of conductors is a key process in Damascene patterning of advanced interconnect structure. The effect of alternative commercial slurries pads, and post-CMP cleaning alternatives are discuss, with removal rate, scratch dentisty, surface roughness, dishing, erosion and particulate density used as performance metrics. Electroplated copper deposition is a mature process from a historical point of view, but a very young process from a CMP perspective. While copper electro deposition has been used and studied for decades, its application to Cu damascene wafer processing is only now gaining complete acceptance in the semiconductor industry. The polishing mechanism of Cu-CMP process has been reported as the repeated process of passive layer formation by oxidizer and abrasion action by slurry abrasives. however it is important to understand the effect of oxidizer on copper passivation layer in order to obtain higher removal rate and non-uniformity during Cu-CMP process. In this paper, we investigated the effects of oxidizer on Cu-CMP process regarding the additional volume of oxidizer.

• 산업경영시스템학회지
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• 제42권4호
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• pp.183-193
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• 2019

Process mining is an analytical technique aimed at obtaining useful information about a process by extracting a process model from events log. However, most existing process models are deterministic because they do not include stochastic elements such as the occurrence probabilities or execution times of activities. Therefore, available information is limited, resulting in the limitations on analyzing and understanding the process. Furthermore, it is also important to develop an efficient methodology to discover the process model. Although genetic process mining algorithm is one of the methods that can handle data with noises, it has a limitation of large computation time when it is applied to data with large capacity. To resolve these issues, in this paper, we define a stochastic process tree and propose a tabu search-genetic process mining (TS-GPM) algorithm for a stochastic process tree. Specifically, we define a two-dimensional array as a chromosome to represent a stochastic process tree, fitness function, a procedure for generating stochastic process tree and a model trace as a string of activities generated from the process tree. Furthermore, by storing and comparing model traces with low fitness values in the tabu list, we can prevent duplicated searches for process trees with low fitness value being performed. In order to verify the performance of the proposed algorithm, we performed a numerical experiment by using two kinds of event log data used in the previous research. The results showed that the suggested TS-GPM algorithm outperformed the GPM algorithm in terms of fitness and computation time.

• 지식경영연구
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• 제20권3호
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• pp.39-47
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• 2019

Response surface methodology (RSM) is a group of statistical modeling and optimization methods to improve the quality of design systematically in the quality engineering field. Its final goal is to identify the optimal setting of input variables optimizing a response. RSM is a kind of knowledge management tool since it studies a manufacturing or service process and extracts an important knowledge about it. In a real problem of RSM, it is a quite frequent situation that considers multiple responses simultaneously. To date, many approaches are proposed for solving (i.e., optimizing) a multi-response problem: process capability function approach, desirability function approach, loss function approach, and so on. The process capability function approach first estimates the mean and standard deviation models of each response. Then, it derives an individual process capability function for each response. The overall process capability function is obtained by aggregating the individual process capability function. The optimal setting is given by maximizing the overall process capability function. The existing process capability function methods usually use the arithmetic mean or geometric mean as an aggregation operator. However, these operators do not guarantee the Pareto optimality of their solution. Moreover, they may bring out an unacceptable result in terms of individual process capability function values. In this paper, we propose a maximin-based process capability function method which uses a maximin criterion as an aggregation operator. The proposed method is illustrated through a well-known multiresponse problem.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2011년도 춘계학술대회 초록집
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• pp.113.1-113.1
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• 2011

PEMS (printed electro-mechanical system) is fabricated by means of various printing technologies. Passive and active compo-nents in 2D or 3D such as conducting lines, resistors, capacitors, inductors and TFT(Thin Film Transistor), which are printed withfunctional materials, can be classified in this category. And the issue of PEMS is applied to a R2R process in the manu-facturing process. In many electro-devices, the vacuum process is used as the manufacturing process. However, the vacuum process has a problem, it is difficult to apply to a continuous process such as a R2R(roll to roll) printing process. In this paper, we propose an ESD (electro static deposition) printing process has been used to apply an organic solar cell of thin film forming. ESD is a method of liquid atomization by electrical forces, an electrostatic atomizer sprays micro-drops from the solution injected into the capillary with electrostatic force generated by electric potential of about several tens kV. ESD method is usable in the thin film coating process of organic materials and continuous process as a R2R manufacturing process. Therefore, we experiment the thin films forming of PEDOT:PSS layer and active layer which consist of the P3HT:PCBM. The organic solar cell based on a P3HT/PCBM active layer and a PEDOT:PSS electron blocking layer prepared from ESD method shows solar-to-electrical conversion efficiency of 1.42% at AM 1.5G 1sun light illumination, while 1.86% efficiency is observed when the ESD deposition of P3HT/PCBM is performed on a spin-coated PEDOT:PSS layer.

• 한국CDE학회논문집
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• 제14권1호
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• pp.60-68
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• 2009

Because of the reduced product life-cycle, industries are making an effort to bring down the process planning time. In the traditional approach, we have to analyze established process planning, then design the time chart based on process information and drawing the formal time chart such as SOP(sequence of operation). Thereafter, it will be converted to PLC code that is a time consuming and redundant job. Similarly, Industrial automated process uses PLC Code to control the factory; however, control information and control code(PLC code) are difficult to understand. Hence, industries prefer writing new control code instead of using the existing one. It shows the lack of information reusability in the existing process planning. As a result, to reduce this redundancy and lack of reusability, we propose SOS-Net modeling method. Unlike past stabilized process planning that is rigid to any change; our proposed SOS-Net modeling method is more adaptable to the new changes. The SOS-Net model is easy to understand and easy to convert into PLC Code accordingly. Therefore, we can easily modify the control information and reuse it for new process planning. The proposed model plays an intermediary role between process planning and PLC code generation. It can reduce the process planning and implementation time as well as cost.

• 한국기계가공학회지
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• 제18권9호
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• pp.36-43
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• 2019

Turning, a main machining process, is a widespread process in metal cutting industries. Many researchers have investigated the effects of process parameters on the machining process. In the turning process, input variables including cutting speed, feed, and depth of cut are generally used. Surface roughness and electric current consumption are used as output variables in this study. We construct a simulation model for the turning process using a neural network, which predicts the output values based on input values. In the neural network, obtaining the appropriate set of weights, which is called training, is crucial. In general, back propagation (BP) is widely used for training. In this study, techniques such as ant colony optimization (ACO) and particle swarm optimization (PSO) as well as BP were used to obtain the weights in the neural network. Particularly, two combined techniques of ACO_BP and PSO_BP were utilized for training the neural network. Finally, the performances of the two techniques are compared with each other.