• International Journal of Control, Automation, and Systems
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• v.4 no.3
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• pp.372-381
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• 2006

The purpose of this study was to develop a process management system to manage ingot fabrication and improve ingot quality. The ingot is the first manufactured material of wafers. Trace parameters were collected on-line but measurement parameters were measured by sampling inspection. The quality parameters were applied to evaluate the quality. Therefore, preprocessing was necessary to extract useful information from the quality data. First, statistical methods were used for data generation. Then, modeling was performed, using the generated data, to improve the performance of the models. The function of the models is to predict the quality corresponding to control parameters. Secondly, rule extraction was performed to find the relation between the production quality and control conditions. The extracted rules can give important information concerning how to handle the process correctly. The dynamic polynomial neural network (DPNN) and decision tree were applied for data modeling and rule extraction, respectively, from the ingot fabrication data.

• Geomechanics and Engineering
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• v.37 no.2
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• pp.135-147
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• 2024

A GIS-based landslide susceptibility mapping (LSM) was carried out using frequency ratio (FR), modified frequency ratio (M-FR), analytic hierarchy process (AHP), and modified analytic hierarchy process (M-AHP) methods to identify and delineate the potential failure zones along the Halong - Vandon expressway. The thematic layers of various landslide causative factors were generated for modeling in GIS, including geology, rainfall, distance to fault, distance to road, slope, aspect, landuse, density of landslide, vertical relief, and horizontal relief. In addition, a landslide inventory along the road network was prepared using data provided by the management department during the course of construction and operation from 2017 to 2019, when many landslides were documented. The validation results showed that the M-FR method had the highest AUC value (AUC = 0.971), which was followed by the FR method with AUC = 0.961. The AUC values were 0.939 and 0.892 for the M-AHP and AHP methods, respectively. The generated LSM obtained from M-FR method classified the study area into five susceptibility classes: very low (0), low (0-1), moderate (1-2), high (2-3), and very high (3-4) classes, which could be useful for various stakeholders like planners, engineers, designers, and local public for future construction and maintenance in the study area.

• Journal of Korean Society for Quality Management
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• v.47 no.3
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• pp.437-451
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• 2019

Purpose: The purpose of this study is to improve the quality of the PGM system by improving the structure and production process of slip-ring rotary joint for radar. Methods: The improvement measures for each cause are established through failure analysis of broken items. Specifically, changing in the housing to improve the heating system. Changing the transportation method to prevent damage to equipment during transport. Changing work process of the attenuator ring to prevent damage. etc. Results: The results of this study are as follows; improving the heating system reduces heat generated by the attenuator by about 7 degrees and obtain additional temperature margins. Reduction of defect rate because of adding X-band rotary joint run-out measurement test, ESS of slip-ring rotary joint and Transportation improvement(reinforced flight boxes, tube protection, etc). Getting stable VSWR values by improving work process of attenuator overheating due to a bad bonding process. Conclusion: Through this study, improvements were made to slip-ring rotary joint that failed repeatedly for various reasons. As a result of the application of the improvements, the same fault does not occur until now, so we can see that the quality of PGM has improved.

• Journal of Korean Society for Quality Management
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• v.50 no.3
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• pp.373-386
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• 2022

Purpose: This study proposes the application of Six Sigma management innovation method for more systematically enhanced execution of Quality by Design (QbD) activities. QbD requires a deeper understanding of the product and process at the design and development stage of the drug, and it is very important to ensure that no fault is fundamentally generated through thorough process control. Methods: Analyzing the background and specific procedures of quality improvement based on the drug design basis, and analyzing the key contents of each step, we have differentated and common points from the 6 Sigma methodology. We propose a new model of Six Sigma management innovation method suitable for pharmaceutical industry. Results: Regulatory agencies are demanding results from statistical analysis as a scientific basis in developing medicines to treat human life through quality improvement activities based on drug design. By utilizing the education system to improve the statistical analysis capacity in the Six Sigma activities and operating the 6 Sigma Belt system in conjunction, it helped systematically strengthen the execution power of quality improvement activities based on pharmaceutical design based on the members of the pharmaceutical industry. Conclusion: By using QbD Six Sigma, which combines quality enhancement based on pharmaceutical design basis and Six Sigma methodology suitable for pharmaceutical industry, it is possible to obtain satisfactory results both by pharmaceutical companies and regulators by using appropriate statistical analysis methods for preparing scientific evidence data required by regulatory.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.510-519
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• 2020

Within an intelligent automated cyber-physical system, the realization of the autonomous mechanism for data collection, data integration, and data analysis plays a critical role in the design, development, operation, and maintenance of such a system. This construct is particularly vital for fault-tolerant route-finding systems that rely on the imprecise GPS location of the vehicles to properly operate, timely plan, and continuously produce informative feedback to the user. More essentially, the integration of digital twins with cyber-physical route-finding systems has been overlooked in intelligent transportation services with the capacity to construct the network routes solely from the locations of the operating vehicles. To address this limitation, the present study proposes a conceptual architecture that employs digital twin to autonomously maintain, update, and manage intelligent transportation systems. This virtual management simulation can improve the accuracy of time-of-arrival prediction based on auto-generated routes on which the vehicle's real-time location is mapped. To that end, first, an intelligent transportation system was developed based on two primary mechanisms: 1) an automated route finding process in which predictive data-driven models (i.e., regularized least-squares regression) can elicit the geometry and direction of the routes of the transportation network from the cloud of geotagged data points of the operating vehicles and 2) an intelligent mapping process capable of accurately locating the vehicles on the map whereby their arrival times to any point on the route can be estimated. Afterward, the digital representations of the physical entities (i.e., vehicles and routes) were simulated based on the auto-generated routes and the vehicles' locations in near-real-time. Finally, the feasibility and usability of the presented conceptual framework were evaluated through the comparison between the primary characteristics of the physical entities with their digital representations. The proposed architecture can be used by the vehicle-tracking applications dependent on geotagged data for digital mapping and location tracking of vehicles under a systematic comparison and simulation cyber-physical system.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2192-2197
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• 2005

This paper describes how to diagnose SBR plant equipment using time-series data mining. It shows the equipment diagnostics based upon vibration signals that are acquired from each device for process control. Data transform techniques including two data preprocessing skills and data mining methods were employed in the data analysis. The proposed method is not only suitable for SBR equipment, but is also suitable for other industrial devices. The experimental results performed on a lab-scale SBR plant show a good equipment-management performance.

• Industrial Engineering and Management Systems
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• v.14 no.4
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• pp.392-400
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• 2015

Monitoring of plasma etch processes for fault detection is one of the hallmark procedures in semiconductor manufacturing. Optical emission spectroscopy (OES) has been considered as a gold standard for modeling plasma etching processes for on-line diagnosis and monitoring. However, statistical quantitative methods for processing the OES data are still lacking. There is an urgent need for a statistical quantitative method to deal with high-dimensional OES data for improving the quality of etched wafers. Therefore, we propose a robust relevance vector machine (RRVM) for regression with statistical quantitative features for modeling etch rate and uniformity in plasma etch processes by using OES data. For effectively dealing with the OES data complexity, we identify seven statistical features for extraction from raw OES data by reducing the data dimensionality. The experimental results demonstrate that the proposed approach is more suitable for high-accuracy monitoring of plasma etch responses obtained from OES.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2001.11a
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• pp.130-135
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• 2001

In this study, I have researched into the causes of defects in apartment house, The results of this study are listed below. (1) Water leakages which result from land sinking and cracks, results of misuse of back filling method, are the main reason of defects in civil engineering work and architectural work. (2) Inexperience and unwillingness are the main reason of defects in plaster work. (3) In windows work and painting work, the main reasons are lacks of precision construction and efflorescence resulting from outdoor air, respectively. (4) Defects in waterproofing work and electric work result from fault construction by low unit Costs. (5) Equipment work requires uses of standardized construction materials and management, and landscape architecture work requires minimizing human mistakes, for instance, degin carelessness. For the reasons stated above, the causes of defects in apartment house are insufficient construction labors, inferior construction materials, urgent construction process time, and conscientiousless industrialists who only seek after a profit margin.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.65-70
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• 2022

In manufacturing and semiconductor industries, transfer robots increase productivity through accurate and continuous work. Due to the nature of the semiconductor process, there are environments where humans cannot intervene to maintain internal temperature and humidity in a clean room. So, transport robots take responsibility over humans. In such an environment where the manpower of the process is cutting down, the lack of maintenance and management technology of the machine may adversely affect the production, and that's why it is necessary to develop a technology for the machine failure diagnosis system. Therefore, this paper tries to identify various causes of failure of transport robots that are widely used in semiconductor automation, and the Prognostics and Health Management (PHM) method is considered for determining and predicting the process of failures. The robot mainly fails in the driving unit due to long-term repetitive motion, and the core components of the driving unit are motors and gear reducer. A simulation drive unit was manufactured and tested around this component and then applied to 6-axis vertical multi-joint robots used in actual industrial sites. Vibration data was collected for each cause of failure of the robot, and then the collected data was processed through signal processing and frequency analysis. The processed data can determine the fault of the robot by utilizing machine learning algorithms such as SVM (Support Vector Machine) and KNN (K-Nearest Neighbor). As a result, the PHM environment was built based on machine learning algorithms using SVM and KNN, confirming that failure prediction was partially possible.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.2
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• pp.131-156
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• 1998

Cooperative query answering is a research effort to develop a fault-tolerant and intelligent database system using the semantic knowledge base constructed from the underlying database. Such knowledge base has two aspects of usage. One is supporting the cooperative query answering Process for providing both an exact answer and neighborhood information relevant to a query. The other is supporting ongoing maintenance of the knowledge base for accommodating the changes in the knowledge content and database usage purpose. Existing studies have mostly focused on the cooperative query answering process but paid little attention on the dynamic knowledge base maintenance. This paper proposes a multi-level knowledge representation framework called Knowledge Abstraction Hierarchy (KAH) that can not only support cooperative query answering but also permit dynamic knowledge maintenance. The KAH consists of two types of knowledge abstraction hierarchies. The value abstraction hierarchy is constructed by abstract values that are hierarchically derived from specific data values in the underlying database on the basis of generalization and specialization relationships. The domain abstraction hierarchy is built on the various domains of the data values and incorporates the classification relationship between super-domains and sub-domains. On the basis of the KAH, a knowledge abstraction database is constructed on the relational data model and accommodates diverse knowledge maintenance needs and flexibly facilitates cooperative query answering. In terms of the knowledge maintenance, database operations are discussed for the cases where either the internal contents for a given KAH change or the structures of the KAH itself change. In terms of cooperative query answering, database operations are discussed for both the generalization and specialization Processes, and the conceptual query handling. A prototype system has been implemented at KAIST that demonstrates the usefulness of KAH in ordinary database application systems.