• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.611-612
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• 2006

Many data mining techniques have been proved useful in revealing important patterns from large data sets. Especially, data mining techniques play an important role in a customer data analysis in a financial industry and an electronic commerce. Also, there are many data mining related research papers in a semiconductor industry and an automotive industry. In addition, data mining techniques are applied to the bioinformatics area. To satisfy customers' various requirements, each industry should develop new processes with more accurate production criteria. Also, they spend more money to guarantee their products' quality. In this manner, we apply data mining techniques to the production-related data such as a test data, a field claim data, and POP (point of production) data in the automotive parts industry. Data collection and transformation techniques should be applied to enhance the analysis results. Also, we classify various types of manufacturing processes and proposed an analysis scheme according to the type of manufacturing process. As a result, we could find inter- or intra-process relationships and critical features to monitor the current status of the each process. Finally, it helps an industry to raise their profit and reduce their failure cost.

• Journal of the Korean Data and Information Science Society
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• 제16권4호
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• pp.823-833
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• 2005

This paper deals the TFT-LCD process and quality, process control problems of the process. For improvement of the process quality and yield, we apply a data mining technique to the LCD industry. And some unique quality features of the LCD process are also described. We describe some preceding researches first and relate to the TFT-LCD process and the problems of data mining in the process. Also we tried to observe the problems which need to solve first and the features from description below hazard must be considered a quality mining in LCD industry.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.143-146
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• 2005

Many data mining techniques have been proved useful in revealing important patterns from large data sets. Especially, data mining techniques play an important role in a customer data analysis in a financial industry and an electronic commerce. Also, there are many data mining related research papers in a semiconductor industry and an automotive industry. In addition, data mining techniques are applied to the bioinformatics area. To satisfy customers' various requirements, each industry should develop new processes with more accurate production criteria. Also, they spend more money to guarantee their products' quality. In this manner, we apply data mining techniques to the production-related data such as a test data, a field claim data, and POP (point of production) data in the automotive parts industry. Data collection and transformation techniques should be applied to enhance the analysis results. Also, we classify various types of manufacturing processes and proposed an analysis scheme according to the type of manufacturing process. As a result, we could find inter- or intra-process relationships and critical features to monitor the current status of the each process. Finally, it helps an industry to raise their profit and reduce their failure cost.

• 한국산업정보학회논문지
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• 제10권4호
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• pp.128-136
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• 2005

The use of technology is increasing within the service industry, but there is some doubt as to whether the benefits of employing this technology have been efficiently harnessed such as data mining. Data mining is the process of extracting certain predictive information from databases that can evolve from currently used restaurant management systems. The potential of harnessing this predictive information can have an enormous impact on the restaurant's operation on the whole, particularly in the area customer retention and competition. Since there is insufficient literature on the use of data mining in the restaurant industry, this study is both seminal and investigative, done via a Delphi survey to explore and describe the current and future applications of this process.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.37-38
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• 2015

A number of documents containing important and useful knowledge have been generated over time in the construction industry. Such text-based knowledge plays an important role in the construction industry for decision-making and business strategy development by being used as best practice for upcoming projects, delivering lessons learned for better risk management and project control. Thus, practical and usable knowledge creation from construction documents is necessary to improve business efficiency. This study proposes a knowledge creating system from construction documents using text mining and the design comprises three main steps - text mining preprocessing, weight calculation of each term, and visualization. A system prototype was developed as a pilot study of the system design. This study is significant because it validates a knowledge creating system design based on text mining and visualization functionality through the developed system prototype. Automated visualization was found to significantly reduce unnecessary time consumption and energy for processing existing data and reading a range of documents to get to their core, and helped the system to provide an insight into the construction industry.

• Safety and Health at Work
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• 제12권3호
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• pp.317-323
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• 2021

Background: The surface mining industry has one of the highest fatality rates among private industries in the United States. Despite recent decreases in the fatality rates of comparable industries, the fatality rate in the surface mining industry has increased. Meanwhile, a lack of safety research in surface mining has hindered efforts to improve safety strategies in the surface mining workplace. Method: This study examined quarry workers' hazard identification skills by conducting a case study of a surface mining facility in the Mid-Atlantic region of the United States. Semistructured interviews were conducted with eight quarry workers who were employed at the mine facility. In addition to the interviews, data were collected through field notes, notes from an expert meeting with safety managers, and site photographs to explore quarry workers' safety behaviors in the workplace. Results: The results showed that quarry workers identified hazards and improved their safety performance by translating safety knowledge learned from training into practice, acquiring hands-on work experience, learning from coworkers, and sharing responsibilities among team members. Conclusion: This study contributes to understanding quarry workers' safe performance beyond what they have learned in safety training to include their interaction with other workers and hand-on experience in the workplace. This study informs practitioners in the surface mining industry to build a safe work environment as they design effective safety programs for employees.

• Safety and Health at Work
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• 제10권2호
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• pp.151-165
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• 2019

Background: Despite improvements in safety performance, the number and severity of mining-related injuries remain high and unacceptable, indicating that further reduction can be achieved. This study examines occupational accident statistics of the Ghanaian mining industry and identifies priority areas, warranting intervention measures and further investigations. Methods: A total of 202 fatal and nonfatal injury reports over a 10-year period were obtained from five mines and the Inspectorate Division of the Minerals Commission of Ghana, and they were analyzed. Results: Results of the analyses show that the involvement of mining equipment, the task being performed, the injury type, and the mechanism of injury remain as priorities. For instance, mining equipment was associated with 85% of all injuries and 90% of all fatalities, with mobile equipment, component/part, and hand tools being the leading equipment types. In addition, mechanics/repairmen, truck operators, and laborers were the most affected ones, and the most dangerous activities included maintenance, operating mobile equipment, and clean up/clearing. Conclusion: Results of this analysis will enable authorities of mines to develop targeted interventions to improve their safety performance. To improve the safety of the mines, further research and prevention efforts are recommended.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.253-255
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• 2004

The mining-related damages such as ground subsidence, acid mine drainage(AMD), and deforestation in the abandoned underground coal mine areas become an object of public concern. Therefore, the system to manage the miningrelated damages is needed for the effective drive of rehabilitation activities. The management system for Abandoned Underground Coal Mine using GIS includes the database about mining record and information associated with the mining-related damages and application programs to support mine damage prevention business. Also, this system would support decision-making policy for rehabilitation and provide basic geological data for regional construction works in abandoned underground coal mine areas.

• 한국전자거래학회지
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• 제19권3호
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• pp.51-64
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• 2014

기업은 생존을 위해 수많은 정보 속에서 빠르게 상황을 인식하고 미래를 예측하기 위해 정량데이터 분석뿐만 아니라 비정형데이터 분석에 대한 관심이 높아지고 있으나, 철강산업에서는 아직 활발하게 활용되지는 못하고 있다. 이에 본 연구에서는 글로벌 철강회사인 P사(社)의 사례를 중심으로 텍스트 마이닝을 이용한 산업트렌드 분석을 시도해 경쟁사 전략, 관심국가의 시장변화, 해외사업장 여론 등을 파악 하는데 기여할 수 있다는 가능성을 발견하였다. 사례 분석은 철강산업을 10개의 카테고리로 분류하고 각각 10개의 주제를 선정하여 분석을 시도하고, 이중 의미 있는 변화를 발견하면 심층 분석하는 형태로 진행하였다. 이번 P사(社)의 사례를 통해 텍스트 마이닝을 통한 산업트렌드 분석이 더 의미 있기 위해서는 목적을 명확히 하고, 관련 키워드를 체계화한다면 경쟁사 전략 파악, 리스크관리, 정량데이터 예측 보정 등 많은 부분에 기여할 수 있을 것으로 기대한다.

• 한국컴퓨터정보학회논문지
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• 제23권4호
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• pp.17-24
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• 2018

This paper proposes data mining models relevant to the serial publication periods and mobile gamification likelihood of webtoon contents which were either serialized or completed in platform. The size of the cartoon industry including webtoon takes merely 1% of the total entertainment contents industry in Korea. However, the significance of webtoon business is rapidly growing because its intellectual property can be easily used as an effective OSMU (One Source Multi-Use) vehicle for multiple types of contents such as movie, drama, game, and character-related merchandising. We suggested a set of data mining classifiers that are deemed suitable to provide prediction models for serial publication periods and mobile gamification likelihood for the sake of webtoon contents. As a result, the balanced accuracies are respectively recorded as 85.0% and 59.0%, from the two models.