• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.3
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• pp.166-171
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• 2005

With development of the database, there are too many data on process variables and the manufacturing process for the traditional statistical process control methods to identify the process variables related with assignable causes. Data mining is useful in this situation and provides variety of approaches for improving the process. In this paper, we applied control charts to monitor the process and if assignable causes are detected, then we applied the SVM technique and the sequence pattern analysis to find out the process variables suspected. These techniques made possible to predict the behavior of process variables. We illustrated our proposed methods with real manufacturing process data.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.130-139
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• 2016

The purpose of this paper is to analyze the problems and the sources of defective products and draw improvement plans in a small plastic boat manufacturing process using TOC (Theory Of Constraints) and statistical analysis. TOC is a methodology to present a scheme for optimization of production process by finding the CCR (Capacity Constraints Resource) in the organization or the all production process through the concentration improvement activity. In this paper, we found and reformed constraints and bottlenecks in plastic boat manufacturing process in the target company for less defect ratio and production cost by applying DBR (Drum, Buffer, Rope) scheduling. And we set the threshold values for the critical process variables using statistical analysis. The result can be summarized as follows. First, CCRs in inventory control, material mix, and oven setting were found and solutions were suggested by applying DBR method. Second, the logical thinking process was utilized to find core conflict factors and draw solutions. Third, to specify the solution plan, experiment data were statistically analyzed. Data were collected from the daily journal addressing the details of 96 products such as temperature, humidity, duration and temperature of heating process, rotation speed, duration time of cooling, and the temperature of removal process. Basic statistics and logistic regression analysis were conducted with the defection as the dependent variable. Finally, critical values for major processes were proposed based on the analysis. This paper has a practical importance in contribution to the quality level of the target company through theoretical approach, TOC, and statistical analysis. However, limited number of data might depreciate the significance of the analysis and therefore it will be interesting further research direction to specify the significant manufacturing conditions across different products and processes.

• Journal of Aerospace System Engineering
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• v.8 no.4
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• pp.39-43
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• 2014

This paper examines the statistical process that should be performed with caution in the composite material qualification and equivalency process, and describes statistically significant considerations on outlier finding and handling process, data pooling through normalization process, review for data distributions and design allowables determination process for structural analysis. Based on these considerations, the need for guidance on statistical process for aircraft manufacturers who use the composite material properties database are proposed.

• Journal of Internet Computing and Services
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• v.8 no.5
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• pp.151-160
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• 2007

A datawarehouse which extracts and saves the massive analysis data is used for marketing and decision support of business. However, the datawarehouse has the problem of increasing the process time and cost as well as has a high risk of process errors because it integrates vast amount of data from distributed environments. Thus, we propose a metrics for measurement in the area of productivity, process quality and data quality. Also through the evaluation using the proposed metrics, we show that our proposal provides productivity enhancement and process improvement.

• Journal of Technology Innovation
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• v.16 no.2
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• pp.65-94
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• 2008

There has been rapid diffusion of digital innovation technology(DIT) such as 3 D CAD, CAE, simulation software which enable firms to see the future results of intended product designs through 3 D diagram and simulated results. This technology helps firms to reduce trial and error process by solving later stage problems in earlier stages. The DIT being the technology reflecting the real world, as a tool representing the simplified form of the real world, the degree of reflecting the real world(fidelity) is important in utilizing the DIT. This study is an exploratory research examining the process of reviewing the fidelity of the DITs and developing the complementary process necessary for utilizing the DIT with 'not good enough' fidelity. This study could draw out, from its case study, an exploratory hypothesis about the process of developing the complementary process. In the process, there is an analysis of the corresponding relationship between the actual data and the output data of the DIT, e.g. simulated result. Then the input data or output data are adjusted on the basis of the analysis of the corresponding relationship so that the discrepancy between the actual data and the expected interpretation of the output data, through the adjustment, of the DIT, can be reduced. This process is sometimes accompanied by the process of generating experimental data, which reflect the unique situation of the product development process of a company, to be put to the data base of DIT. The complementary process is the process requiring knowledge sharing and adjustment activities across different divisions. This study draw outs implications for effective management of the fidelity of DIT tools.

• Journal of Korean Academy of Nursing Administration
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• v.10 no.1
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• pp.141-159
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• 2004

Purpose: The purpose of this study was to investigate the degree of information technology application, and to identify the effect of information technology application en knowledge management process in clinical nurses. Method: Participants were 629 regular clinical nurses who had worked for over 1 year in general units of 9 tertiary medical hospitals including 2 national university hospitals, 5 university hospitals, and 2 hospitals founded by business enterprises. Data were collected from March to May 2003 through questionnaires. Thee structured instruments were used to collect the data: Information Technology Application scale, Knowledge Management Process Scale(Jeong, Lee, Lee, & Kim, 2003), and one for general characteristics. The data were analyzed using reliability analysis, descriptive analysis, one-way ANOVA, $Scheff{\acute{e}$ test, correlation analysis, partial correlation analysis, and multiple regression analysis with the SPSS for Windows 10,0 program. Result: 1) The HIS application degree, IT application ability, and IT application frequency were significantly correlated with the degree of knowledge management process activation and 4 elements of knowledge management process, Knowledge Creation, Knowledge Storage, Knowledge Sharing, and Knowledge Utilization(p=.000). 2) The 3 variables, HIS application degree, IT application ability, and IT application frequency explained 47.2% of the total variance of the degree of knowledge management process activation, and 352% of me total variance of Knowledge Storage. And 2 variables, HIS application degree and IT application frequency explained 17.6% of the total variance of Knowledge Creation, 39.9% of the total variance of Knowledge sharing, and 33.8% of the total variance of Knowledge utilization(p=.000). 3) As a result of multiple regression analysis, the key determinant of the degree of knowledge management process activation for nurses was HIS application degree The HIS application degree, IT application frequency, position, IT application ability, and continuous total numbers of years working at the present hospital explained 51.1% of the total variance of the degree of knowledge management process activation(p=.000). Conclusions: These results suggest that the information technology application positively affects the nurses' knowledge management process. From the above findings, information technology application is empirically verified as a useful and effective method to activate knowledge management process, and knowledge management.

• Journal of Practical Engineering Education
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• v.6 no.2
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• pp.127-134
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• 2014

Analyzing test data of a vehicle for evaluating its emission performance is an essential process in automotive development field, yet it is intricate and tedious task. In addition, clear understanding and care are required when the analysis process is carried out. Computer software solutions significantly reduce the time and the effort for such analysis. Developing a computer routine to analyze the emission data in a vehicle test demands a complete understanding of the emissions analysis and its related details. In this paper, the principals to develop a LabVIEW analysis routine (VI) are introduced helping automotive engineers comprehend the emission analysis process of a vehicle test data and instruct them to develop similar routines for such analysis.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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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.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.177-181
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• 2021

With the recent advances in information and communication technology, online management of students' learning data has become the norm. Research on learning analysis that predicts the near future (in a few years) of students' careers using machine learning methods and state transition models has been widely conducted. It is important for educators to evaluate the comprehension stability of students to prevent a decrease in their comprehension rate and dropouts in the class. In this study, we measured the comprehension process of university students in different types of lectures. Herein, we report on the results of data analysis using time series and data statistics, and consider several educational approaches.

• Journal of Microbiology and Biotechnology
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• v.16 no.7
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• pp.1139-1143
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• 2006

Various techniques and strategies have been developed for the identification of intracellular metabolic conditions, and among them, isotope balance-based flux analysis with gas chromatography/mass spectrometry (GC/ MS) has recently become popular. Even though isotope balance-based flux analysis allows a more accurate estimation of intracellular fluxes, its application has been restricted to relatively small metabolic systems because of the limited number of measurable metabolites. In this paper, a strategy for incorporating isotope balance-based flux data obtained for a small network into metabolic flux analysis was examined as a feasible alternative allowing more accurate quantification of intracellular flux distribution in a large metabolic system. To impose GC/MS based data into a large metabolic network and obtain optimum flux distribution profile, data reconciliation procedure was applied. As a result, metabolic flux values of 308 intracellular reactions could be estimated from 29 GC/ MS based fluxes with higher accuracy.