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

• 공학교육연구
• /
• 제9권4호
• /
• pp.71-82
• /
• 2006

학과의 교육목표 달성을 위해서는 순환형 자율 개선 구조를 운영하기 위한 시스템이 필요하며, 설문조사 분석을 통한 교육시스템의 개선은 교육목표 달성을 위한 중요한 요소 중의 하나이다. 일반적으로 설문조사 분석에서는 항목별로 통계적인 분포를 조사하거나 두 개의 항목간의 연관성을 조사하는 분석 방법이 주로 사용된다. 그러나 이러한 분석 방법은 다양한 항목들 간의 상호 연관성을 분석하지 못하는 한계가 있으므로 보다 심층적인 분석방법이 필요하다. 본 논문에서는 데이터마이닝 기법을 적용한 심층적인 분석 기법을 제시한다. 데이터마이닝이란 대용량의 데이터에 숨겨져 있는 지식을 추출해 내는 기법으로 설문분석에도 효과적으로 이용될 수 있다. 본 분석에서는 Clementine 데이터마이닝 도구를 사용하여 숭실대학교 컴퓨터학과의 재학생에 대한 설문자료에 대한 심층 분석을 수행하였다. 분석의 결과로 '학점'과 다른 항목들과의 연관성을 계층적으로 분석할 수 있었으며, '학점'에 대한 학생상담과 학과의 교육 프로그램 개선에 실제적으로 사용할 수 있는 유용한 정보들을 획득할 수 있었다.

• 한국빅데이터학회지
• /
• 제1권2호
• /
• pp.65-78
• /
• 2016

기업 환경의 급격한 변화와 복잡성의 증가에 따라 다양한 장점을 지닌 기업들이 협력을 통해 고객에게 짧은 시간에 최상의 가치를 제공해주는 것이 중요해 지고 있다. 이를 위해 기업은 다양한 공급망에 참여하게 되고, 기업의 공급망 관리에 대한 중요성은 점차 증대되고 있다. 이러한 공급망 관리의 효율성을 높이기 위해 공급망 상에서 생성되는 데이터의 효과적인 분석이 필요하다. 본 연구에서는 프로세스 마이닝 기법을 활용한 공급망 데이터 분석을 제안한다. 프로세스 마이닝 기법이 적용 가능한 공급망 데이터의 분석 범주를 도출하고, 프로세스 마이닝을 활용한 다양한 분석을 제안하다. 이를 통해 기업은 공급망 관리에 대한 인사이트를 얻고 공급망 관리 프로세스의 개선 및 효율화가 가능하다. 사례 연구를 통해 프로세스 마이닝을 활용한 공급망 데이터 분석의 유효성을 검증하였다.

• 한국농공학회지
• /
• 제45권6호
• /
• pp.183-193
• /
• 2003

Most construction works on the soft ground adopt instrumentation to manage settlement and stability of the embankment. The rapid progress of the information technologies and the digital data acquisition on the soft ground instrumentation has led to the fast-growing amount of data. Although valuable information about the behaviour of the soft ground may be hiding behind the data, most of the data are used restrictedly only for the management of settlement and stability. One of the critical issues on soft ground instrumentation is the long-term settlement prediction. Some observational settlement analysis methods are used for this purpose. But the reliability of the analysis results is remained in vague. The knowledge could be discovered from a large volume of experiences on the observational settlement analysis. In this article, we present a database to store settlement records and data mining procedure. A large volume of knowledge about observational settlement prediction were collected from the database by applying the filtering algorithm and knowledge discovery algorithm. Statistical analysis revealed that the reliability of observational settlement analysis depends on stay duration and estimated degree of consolidation.

• 한국전자거래학회지
• /
• 제4권1호
• /
• pp.21-36
• /
• 1999

Using user monitoring techniques on web, marketing decision makers in cyber shopping malls can gather customer behavior data as well as sales transaction data and customer profiles. In this paper, we present a marketing rule extraction technique for customer behavior analysis in cyber shopping malls, The technique is an application of market basket analysis which is a representative data mining technique for extracting association rules. The market basket analysis technique is applied on a customer behavior log table, which provide association rules about web pages in a cyber shopping mall. The extracted association rules can be used for mall layout design, product packaging, web page link design, and product recommendation. A prototype cyber shopping mall with customer monitoring features and a customer behavior analysis algorithm is implemented using Java Web Server, Servlet, JDBC(Java Database Connectivity), and relational database on windows NT.

• International Journal of Advanced Culture Technology
• /
• 제11권4호
• /
• pp.279-285
• /
• 2023

This study provides academic implications by considering trends of domestic research regarding therapy for Mental disorder schizophrenia and psychosocial. For the analysis of this study, text mining with the use of R program and social network analysis method have been used and 65 papers have been collected The result of this study is as follows. First, collected data were visualized through analysis of keywords by using word cloud method. Second, keywords such as intervention, schizophrenia, research, patients, program, effect, society, mind, ability, function were recorded with highest frequency resulted from keyword frequency analysis. Third, LDA (latent Dirichlet allocation) topic modeling result showed that classified into 3 keywords: patient, subjects, intervention of psychosocial, efficacy of interventions. Fourth, the social network analysis results derived connectivity, closeness centrality, betweennes centrality. In conclusion, this study presents significant results as it provided basic rehabilitation data for schizophrenia and psychosocial therapy through new research methods by analyzing with big data method by proposing the results through visualization from seeking research trends of schizophrenia and psychosocial therapy through text mining and social network analysis.

• 한국경영과학회지
• /
• 제39권4호
• /
• pp.1-17
• /
• 2014

The functions of stocking and releasing in logistics center consist of three major procedure such as receiving, shipping and stock managements. Each process includes various sub-processes which are complicatedly connected with each other. Furthermore, lots of operators execute various tasks in the different sub-processes, simultaneously. It makes difficult to standardize, monitor, and analyze the processes. This paper proposed the quantitative methodology using process mining approach to discover and analyze receiving and shipping processes. For this purpose, the PDA operation log data is analyzed to build a realistic process model. The deduced model has been compared with official process model. In addition, task assignment and social networks analysises are carried out by utilizing process mining tools. Also, it has been proposed how to improve the processes with the analytical simulation model based on the results of process mining.

• Earthquakes and Structures
• /
• 제18권1호
• /
• pp.97-111
• /
• 2020

Cylindrical steel tanks are important components of industrial facilities. Their safety becomes a crucial issue since any failure may cause catastrophic consequences. The aim of the paper is to show the results of comprehensive FEM numerical investigation focused on the response of cylindrical steel tanks under mining tremors and moderate earthquakes. The effects of different levels of liquid filling, the influence of non-uniform seismic excitation as well as the aspects of diagnosis of structural damage have been investigated. The results of the modal analysis indicate that the level of liquid filling is really essential in the structural analysis leading to considerable changes in the shapes of vibration modes with a substantial reduction in the natural frequencies when the level of liquid increases. The results of seismic and paraseismic analysis indicate that the filling the tank with liquid leads to the substantial increase in the structural response underground motions. It has also been observed that the peak structural response values under mining tremors and moderate earthquakes can be comparable to each other. Moreover, the consideration of spatial effects related to seismic wave propagation leads to a considerable decrease in the structural response under non-uniform seismic excitation. Finally, the analysis of damage diagnosis in steel tanks shows that different types of damage may induce changes in the free vibration modes and values of natural frequencies.

• 한국해양공학회지
• /
• 제20권3호
• /
• pp.54-60
• /
• 2006

For optimal design of a deep-sea ocean mining collector system, based on self-propelled mining vehicle, it is imperative to develop and validate the dynamic model of a tracked vehicle traveling on soft deep seabed. The purpose of this paper is to evaluate the fidelity of the dynamic simulation model by means of response surface methodology. Various statistical techniques related to response surface methodology, such as outlier analysis, detection of interaction effect, analysis of variance, inference of the significance of design variables, and global sensitivity analysis, are examined. To obtain a plausible response surface model, maximum entropy sampling is adopted. From statistical analysis and prediction for dynamic responses of the tracked vehicle, conclusions will be drawn about the accuracy of the dynamic model and the performance of the response surface model.

• 품질경영학회지
• /
• 제49권1호
• /
• pp.97-112
• /
• 2021

Purpose: The purpose of this paper is to analyze the technology convergence and its characteristics, focusing on the defense technologies in South Korea. Methods: Patents applied by the Agency for Defense Development (ADD) during 1979~2019 were utilized in this paper. Information Entropy analysis has been conducted on the patents to analyze the usability and potential for development. To analyze the trend of technology convergence in defense technologies, Social Network Analysis(SNA) and Association Rule Mining Analysis were applied to the co-occurrence networks of International Patent Classification (IPC) codes. Results: The results show that sensor, communication, and aviation technologies played a key role in recent development of defense science and technology. The co-occurrence network analysis also showed that the convergence has gradually enhanced over time, and the convergence between different technology sectors largely emerged, showing that the convergence has been diversified. Conclusion: By analyzing the patents of the defense technologies during the last 30 years, this study presents the comprehensive perspectives on trends and characteristics of technology convergence in defense industry. The results of this study are expected to be used as a guideline for decision making in the government's R&D policies in defence industry.