• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2006년도 추계공동학술대회
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• pp.293-297
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• 2006

Recently most universities are suffering from students leaving their majors. In order to make a countermeasure for reducing major separation rate, many universities are trying to find a proper solution. As a similar endeavor, this paper uses decision tree algorithm which is one of the data mining techniques which conduct grouping or prediction into several sub-groups from interested groups. This technique can analyze a feature of type on students leaving their majors. The dataset consists of 5,115 features through data selection from total data of 13,346 collected from a university in Kangwon-Do during seven years(2000.3.1 $\sim$ 2006.6.30). The main objective of this study is to evaluate performance of algorithms including CHAID, CART and C4.5 for classification of students leaving their majors with ROC Chart, Lift Chart and Gains Chart. Also, this study provides values about accuracy, sensitivity, specificity using classification table. According to the analysis result, CART showed the best performance for classification of students leaving their majors.

• 산업경영시스템학회지
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• 제47권1호
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• pp.20-27
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• 2024

Determining the number of operators who set up the machines in a human-machine system is crucial for maximizing the benefits of automated production machines. A man-machine chart is an effective tool for identifying bottlenecks, improving process efficiency, and determining the optimal number of machines per operator. However, traditional man-machine charts are lacking in accounting for idle times, such as interruptions caused by other material handling equipment. We present an adjusted man-machine chart that determines the number of machines per operator, incorporating idleness as a penalty term. The adjusted man-machine chart efficiently deploys and schedules operators for the hole machining process to enhance productivity, where operators have various idle times, such as break times and waiting times by forklifts or trailers. Further, we conduct a simulation validation of traditional and proposed charts under various operational environments of operators' fixed and flexible break times. The simulation results indicate that the adjusted man-machine chart is better suited for real-world work environments and significantly improves productivity.

• 한국신뢰성학회지:신뢰성응용연구
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• 제18권1호
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• pp.20-32
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• 2018

Purpose: The purpose of this study is to set up an anomaly detection criteria for sensor data coming from a motorcycle. Methods: Five sensor values for accelerator pedal, engine rpm, transmission rpm, gear and speed are obtained every 0.02 second from a motorcycle. Exploratory data analysis is used to find any pattern in the data. Traditional process control methods such as X control chart and time series models are fitted to find any anomaly behavior in the data. Finally unsupervised learning algorithm such as k-means clustering is used to find any anomaly spot in the sensor data. Results: According to exploratory data analysis, the distribution of accelerator pedal sensor values is very much skewed to the left. The motorcycle seemed to have been driven in a city at speed less than 45 kilometers per hour. Traditional process control charts such as X control chart fail due to severe autocorrelation in each sensor data. However, ARIMA model found three abnormal points where they are beyond 2 sigma limits in the control chart. We applied a copula based Markov chain to perform statistical process control for correlated observations. Copula based Markov model found anomaly behavior in the similar places as ARIMA model. In an unsupervised learning algorithm, large sensor values get subdivided into two, three, and four disjoint regions. So extreme sensor values are the ones that need to be tracked down for any sign of anomaly behavior in the sensor values. Conclusion: Exploratory data analysis is useful to find any pattern in the sensor data. Process control chart using ARIMA and Joe's copula based Markov model also give warnings near similar places in the data. Unsupervised learning algorithm shows us that the extreme sensor values are the ones that need to be tracked down for any sign of anomaly behavior.

• 대한산업공학회지
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• 제34권3호
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• pp.308-317
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• 2008

This research investigates economic characteristics of 2 of 2 runs rules under the Shewhart $\bar{X}$ control chart scheme. A Markov chain approach is employed in order to calculate the in-control average run length (ARL) and the average length of analysis cycle. States of the process are defined according to the process conditions at sampling time and transition probabilities are derived from the state definitions. A steady state cost function is constructed based on the Lorezen and Vance(1986) model. Numerical examples show that 2 of 2 runs rules are economically superior to the Shewhart $\bar{X}$ chart in many cases.

• 산업기술연구
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• 제28권A호
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• pp.149-153
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• 2008

$C_p$ and other process capability indices are used extensively in industry, However, They are inadequate and widely misused. In a practical application, process average ${\mu}$ is almost always drifted by various assignable causes in process. And control charts will not detect these shifts in process average. In this study, incorporating these undetected shifts, a new capability analysis method is introduced.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2008년도 춘계학술대회
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• pp.283-293
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• 2008

Analysis of Means(ANOM) is a visualization tool for comparing several means to the grand mean like control chart type. This paper reviews five ANOM methods for continuous data such as ANOM, ANOME (ANOM for Treatment Effects), ANCON (Analysis of Contrasts), ANOMV (ANOM for Variance), ANOMC (ANOM for Correaltion). Three ANOM tools for discrete data such as ANOMNP (ANOM for Nonconforming Proportions), ANOMNC (ANOM for Nonconforming Unit), ANOMNPU (ANOM for Nonconfirmities Per Unit) are also developed.

• 패션비즈니스
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• 제8권4호
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• pp.141-155
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• 2004

The purpose of this study was to arrange the korean women's hair styles of the beginning of 21st century and make hair style image making chart to use personal image making consulting data through analyze actress hair styles of broadcasting TV drama. To accomplish this purposes, picked up the two most popular dramas per each broadcasting stations, KBS1, KBS2, MBC, SBS, in february 2004. and analyzed and arranged hair styles of actress and at the last made the hair style image making chart. The results of the research are as belows. 1. Hair trends of february 2004. were Modern Sophisticated, Active and Romantic. 2. The results of three classifications of hair style trends, form, color, accessory, were as belows. 1) Form : Layer, left part, straight, low wave, long hair, no volme, bang were in vogue. Generally, Modern Sophisticated, Active, Romantic feeling were in vogue. 2) Color : Black, brown, two tone color were in vogue. Generally Modern Sophisticated, Romantic, Active feeling were in vogue. 3) Accessory : Hair bands & pins were in vogue. Generally these gave the Modern, Active feeling. 3. Hair style image making chart manufacturing depends on fashion feeling. 1) Classification of feeling, 2) Analysis of form, 3) Analysis of color, 4) Hair style image making chart manufacturing depends on fashion feeling This research will be a historical data of korean women's hair styles of the beginning of 21st century & can be used the basic data of personal hair style image making consulting.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2004년도 춘계학술대회 논문집
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• pp.275-281
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• 2004

현재 국내에서 활발히 이루어지고 있는 GPS 관측성과가 관측값의 통계적 검증없이 이루어지고 있는 문제점이 있다. 그리고 육지와 해상의 통합지리정보시스템구축을 위한 수치지형도와 수치해도의 통합투영의 필요성이 요구되고 있다. 본 연구를 통하여 GPS 망조정에 사용되는 3점의 기준점에 대한 기하학적인 강도에 따른 정밀도 분석과 분산계수의 변화에 따른 GPS 관측값들의 정밀도 분석방법으로 GPS 관측값의 정밀도 행상을 위한 방법을 제시하였다. 또한, GPS 관측값의 정밀도를 향상시키는 방법과 수치지도와 전자해도의 통합투영으로 GPS 기준점을 이용한 수치지형도와 수치해도의 경계선 오차량을 비교검토하여 수치지형도와 수치해도의 통합관리의 방향을 제시하였다. 그리고 이렇게 산출된 GPS 관측결과를 이용하여 EDM 측량결과를 산출하고 수치지형도와 수치해도를 이 경계값들로 맞추었을 때 전체적인 경계점이 오차량을 비교 검토하였다.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 1998년도 The 12th Asia Quality Management Symposium* Total Quality Management for Restoring Competitiveness
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• pp.198-207
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• 1998

The p chart approximate to the normal distribution has a difficulty to analyze the process condition precisely when the negative LCL is occurred. Furthermore, the probability of Type I error increases compared with using its original binomial distribution. For a long time the p chart has been used as approximated to the normal distribution because of its easy use. However, it becomes rapid and convenient to calculate the binomial distribution through the development of computer and software, so it is strongly suggested to use the binomial distribution determining control limits to reduce the probability of Type I error. In this study, I suggest that the control limits can be designed in use of binomial distribution and they can be utilized without special software by illustrating the certain work for establishing p-chart with the commercial one(EXCEL).

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1993년도 추계학술대회발표논문집; 서강대학교, 서울; 25 Sep. 1993
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• pp.31-39
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• 1993

This paper considers a procedure for the economic design of a cumulative score(CUSCORE) control chart and more sensitive than X-type control chart for small shift to control the mean of a process with a exponentially distributed quality characteristic. An expected loss - cost model as a function of design variables(sample size, sampling interval, scoring limit and decision limit) is derived. Direct search techniques are used to optimize the model subject to ARL in control. Numerical examples and sensitivity analysis of the model are presented. For selected values of situation parameters a comparison study with CUSUM charts is given. CUSCORE control charts compare favourably with CUSUM charts in cost for speedy production process. The proposed control chart can be directly applied for controlling the lifetime characteristics.