• 대한산업공학회지
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• 제42권6호
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• pp.370-376
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• 2016

Manufacturing data analysis and its applications are getting a huge popularity in various industries. In spite of the fast advancement in the big data analysis technology, however, the manufacturing quality data monitored from the automated inspection system sometimes is not reliable enough due to the complex patterns of product quality. In this study, thus, we aim to define the level of trusty of an automated quality inspection system and improve the reliability of the quality inspection data. By correlation analysis and feature selection, this paper presents a method of improving the inspection accuracy and efficiency in an SVM-based automatic product quality inspection system using thermal image data in an auto part manufacturing case. The proposed method is implemented in the sealer dispensing process of the automobile manufacturing and verified by the analysis of the optimal feature selection from the quality analysis results.

• 한국안광학회지
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• 제12권4호
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• pp.87-90
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• 2007

polycarbonate(PC)용 안경렌즈를 생산하는데 사용되는 몰드(mold)를 가공하기 위해서는 코아(core)의 가공이 필요하다. 코아의 가공은 Diamond Turning Machine(DTM) 또는 Computer Numerical Control(CNC) 선반으로 이루어지는데 이러한 장비의 운용을 위해서는 렌즈 코아 형상에 대한 수치 데이터가 필요하게 된다. 이에 우리는 렌즈 코아 형상에 대한 수치 데이터를 산출하는 프로그램을 개발하였다. 프로그램은 일반 비구면 식의 계수를 사용하여 수치 데이터를 산출할 수 있도록 개발하였으며, 형상 그래프를 보여줄 수 있도록 하였고, 필요한 수치 데이터 파일을 저장할 수 있도록 하였다.

• 한국생산제조학회지
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• 제9권1호
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• pp.119-127
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• 2000

In this study the classified researches the artificial and natural flaws in welding parts are performed using the pattern recognition technology. For this purpose the signal pattern recognition package including the user defined function was developed and the total procedure including the digital signal processing feature extraction feature selection and classifi-er selection is teated by bulk,. Specially it is composed with and discussed using the statistical classifier such as the linear discriminant function the empirical Bayesian classifier. Also the pattern recognition technology is applied to classifica-tion problem of natural flaw(i.e multiple classification problem-crack lack of penetration lack of fusion porosity and slag inclusion the planar and volumetric flaw classification problem), According to this result it is possible to acquire the recognition rate of 83% above even through it is different a little according to domain extracting the feature and the classifier.

• 대한기계학회논문집
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• 제18권1호
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• pp.223-231
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• 1994

When manufacturing mold dies, an operation sheet is required for each part of the mold dies. The consistent estimation of standard operation time in the operation sheet is difficult, because the estimation is mainly based on subjective judgement. In order to resolve it, concept of feature is introduced in this study. For CAD/CAPP integration, feature technology is being implemented to represent geometrical and technological information of part drawings. A feature database has already been designed, and then used to generate data for process and operation planning modules. Related to this former research, standard operation time is calculated using the feature information and tables used in a real factory.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.702-706
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• 1995

Integration of CAM and CAM information is important in the CIM era. For a CIM system, the feature representation can be a solution to the integration of product model data. These are geometry feature, functional feature, and manufacturing feature in the feature context. This paper proposes a framework to integrate the configuration design method, parametric modeling and the feature modeling method. The concept of design unit which is one level higher than functional feature and parametric modeling concept with functional features have been proposed.

• 대한안전경영과학회지
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• 제8권2호
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• pp.51-59
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• 2006

So far, there is no technique of quantitative evaluation on danger related to industrial accidents. Therefore, as an endeavor for obtaining technique of quantitative evaluation, this study presents feature analysis of industrial accidents in manufacturing field using QUEST algorithm. In order to analyze feature of industrial accidents, a retrospective analysis was performed in 10,536 subjects (10,313 injured people, 223 deaths). The sample for this work chosen from data related to manufacturing businesses during three years $(2002\sim2004)$ in Korea. The analysis results were very informative since those enable us to know the most important variables such as occurrence type, company size, and occurrence time which can affect injured people. Also, it is found that classification using QUEST algorithm which was performed in this study is very reliable.

• Smart Structures and Systems
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• 제29권6호
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• pp.767-775
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• 2022

Metal additive manufacturing (AM), also known as metal three-dimensional (3D) printing, produces 3D metal products by repeatedly adding and solidifying metal materials layer by layer. During the metal AM process, products experience repeated local melting and cooling using a laser or electron beam, resulting in product defects, such as warpage, cracks, and internal pores. Such defects adversely affect the final product. This paper proposes the in situ monitoring-based warpage prediction of metal AM products with experimental feature extraction. The temperature profile of the metal AM substrate during the process was experimentally collected. Time-domain features were extracted from the temperature profile, and their relationships to the warpage mechanism were investigated. The standard deviation showed a significant linear correlation with warpage. The findings from this study are expected to contribute to optimizing process parameters for metal AM warpage reduction.

• 한국생산제조학회지
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• 제6권4호
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• pp.46-53
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• 1997

This paper presents a method of detection localized defects on tapered roller bearing in main spindle of machine tool system. The feature vectors, i.e. statistical parameters, in time-domain analysis technique have been calculated to extract useful features from acoustic emission signals. These feature vectors are used as the input feature of an neural network to classify and detect bearing defects. As a results, the detection of bearing defect conditions could be sucessfully performed by using an neural network with statistical parameters of acoustic emission signals.

• 한국정밀공학회지
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• 제20권3호
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• pp.105-111
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• 2003

This paper presents an approach to automate process planning of press dies for manufacturing of car bodies. Considering that the press-dies used at the same press operations regardless of the panels they produce or the car models of which they produce panels have similar shapes except for the forming part of the dies, general approaches to recognize manufacturing features from CAD models are not necessary. Therefore, a hybrid approach is proposed combining feature-based design and feature-extraction approaches. The proposed method recognizes features by parsing the parameters extracted from CAD models and finds proper operations by querying the database by the recognized features. An internet-based process planning system is developed to demonstrate the proposed approach and to suggest a new paradigm of process planning system that utilizes an internet access to the CAD system.

• International Journal of Precision Engineering and Manufacturing
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• 제7권1호
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• pp.18-23
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• 2006

Cutting by a high speed laser cutting machine is one of most effective technologies to improve productivity. This paper has presented the cutting characteristics and optimal cutting conditions in a high speed feeding type laser cutting machine by using Tacuchi method in the design of experiment. An L9(34) orthogonal array is adopted to study the effect of adjustment parameters. The adjustment parameters consist of cutting speed, laser power, laser output duty and assistant gas pressure. The surface roughness of sheet metal is regarded as a quality feature. Analysis of variance is performed in order to evaluate the effect of adjustment parameters on the quality feature of laser cutting process.