• Title/Summary/Keyword: processing condition

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Application of CAE Techinique for the Optimization of Press Forming Condition of Low Arm (로우암 프레스 성형 조건의 최적화를 위한 CAE 기술의 적용)

  • 김영석;이택근;김성태
    • Transactions of Materials Processing
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    • v.9 no.3
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    • pp.257-264
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    • 2000
  • In this study, optimization for press forming condition of low arm was performed with explicit dynamic FEM code, Pam-Stamp. FEM simulation was coupled with the Taguchi's experiment technique having three design variables - friction coefficient, plastic anisotropy parameter, and blank shape - which are chosen to be optimized. The simulation results were compared with those of experiment. We found out the change of blank shape among these three design variables is very effective in optimizing press forming condition of low arm. In addition, the modified blank shape shows high yield of slitting coil.

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Bicubic Patch체 의한 보간곡면의 모델링 및 가공에 관한 연구

  • 이진모;이동주
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1997.04a
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    • pp.1025-1030
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    • 1997
  • In this study,the procedure of interpolation surface modeling on bicubic spline patch equation and NC machining are presented. The procedure consists of three parts : patch modeling,cutter location data generation,post processing and NC milling machining. For generation of the cutter location data,tangent vectors and units normal vectors on the patch must be calculated. In order to investigate the properties of the interpolation surface created by bicubic spline patch, two kinds of end conditions, clamped end condition and relaxed end condition,were applied in this study. The shape of the patch depends on the magnitide of the tangent vectors and twist vectors at the corners of bicubic surface patch. the patch generated by relaxed end condition more approximated to the surface patch which was given.

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A Survey on the Sanitary Condition of Kitchens of School Lunch Program

  • Kim, Jong-Gyu
    • Proceedings of the Korean Environmental Health Society Conference
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    • 2003.06a
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    • pp.174-176
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    • 2003
  • A survey was conducted to investigate the sanitary condition of school kitchens in one region of Korea. A self-administered questionnaire recommended by the Korea Ministry of Education & Human Resources Development (MOEHRD) was offered to a random sample of dieticians of twenty-five elementary schools for food, sanitation and safety inspection of their kitchens. Air temperature, relative humidity, and airborne microbes in the kitchens were monitored during food preparation, processing and service. The inspection results showed their sanitary condition met the level B of the recommendation of the Korea MOEHRD. The range of air temperature of the kitchens was 21.4∼22.4$^{\circ}C$, and the range of relative humidity was 62.4∼69.6%. The microbiological evaluation of kitchen samples indicated aerobic plate count levels from 22.5 to 26.5 CFU/15 min. These results indicate that the levels of sanitary condition of kitchens in the schools were not satisfactory for safe foodservice although the inspection showed good results. This study suggests that the school kitchens should be monitored and strict inspection is necessary.

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Condition Monitoring of Tool wear using Sound Pressure and Fuzzy Pattern Recognition in Turning Processes (선삭공정에서 음압과 퍼지 패턴 인식을 이용한 공구 마멸 감시)

  • 김지훈
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 1998.10a
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    • pp.164-169
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    • 1998
  • This paper deals with condition monitoring for tool wear during tuning operation. To develop economic sensing and identification methods for turning processes, sound pressure measurement and digital signal processing technique are proposed. To identify noise sources of tool wear and reject background noise, noise rejection methodology is proposed. features to represent condition of tool wear are obtained through analysis using adaptive filter and FFT in time and frequency domain. By using fuzzy pattern recognition, we extract features, which are sensitive to condition of tool wear, from several features and make a decision on tool wear. The validity of the proposed system is condirmed through the large number of cutting tests in two cutting conditions.

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A Study on Recognition of Friction Condition for Hydraulic Driving Members using Neural Network

  • Park, Heung-Sik;Seo, Young-Baek;Kim, Dong-Ho;Kang, In-Hyuk
    • KSTLE International Journal
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    • v.3 no.1
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    • pp.54-59
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    • 2002
  • It can be effective on failure diagnosis of oil-lubricated tribological system to analyze operating conditions with morphological characteristics of wear debris in a lubricated machine. And it can be recognized that results are processed threshold images of wear debris. But it is needed to analyse and identify a morphology of wear debris in order to predict and estimate a operating condition of the lubricated machine. If the morphological characteristics of wear debris are identified by the computer image analysis and the neural network, it is possible to recognize the friction condition. In this study, wear debris in the lubricating oil are extracted from membrane filter (0.45 ${\mu}m$) and the quantitative value fur shape parameters of wear debris was calculated through the computer image processing. Four shape parameters were investigated and friction condition was recognized very well by the neural network.

Selecting the Optimum Process Condition Between the Factor Level Using Neural Network (신경망이론을 이용한 어인자의 수준사이를 고려한 최적조건 선정에 관한 연구)

  • 홍정의
    • Journal of Korean Society for Quality Management
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    • v.30 no.2
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    • pp.86-98
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    • 2002
  • Defining the relationship between the quality of injection molded parts and the process condition is very complicate because of lots of factor are involved and each factor has a non-linearity. With the development of CAE(Computer Aided Engineering) technology, the estimation of volumetric shrinkage of injection mold parts is possible by computer simulation even though restricted application. In this research, Neural Network applied for finding optimal processing condition. The percent of volumetric shrinkage compared on each case and show neural network can be successfully applied selecting optimum condition not only within factor level but also between factor level.

Effect of Mixing Condition of Raw Materials on the Thermal Properties of the Exothermic & Insulating (원료 배합조건에 따른 발열보온재의 열적 특성)

  • Kim, D.J.;Shin, D.Y.;Byun, S.Y.;Wi, C.H.;Hong, S.H.;You, B.D.;Oh, S.H.
    • Transactions of Materials Processing
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    • v.18 no.5
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    • pp.401-409
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    • 2009
  • The change of the thermal properties of exothermic and insulating materials with the mixing condition of raw materials which is the most important factor for exothermic & insulating materials was investigated by using the evaluation system of the thermal properties of exothermic and insulating materials. In this study, the effect of the thermal properties of the exothermic & insulating materials such as exothermic properties, endothermic properties, insulating properties, maximum temperature of molten metal, ignition time of exothermic & insulating materials and temperature recovery time on the mixing ratio of reductant and oxidant, types of reductant, and particle sizes of reductants was examined. It could be expected to design the mixing condition of raw materials for various exothermic and insulating materials.

Application of Neural Network to Prediction and estimation of Rolling Condition for Hydraulic members (유압구동부재의 구름운동상태 예지 및 판정을 위한 신경 회로망의 적용)

  • 조연상;김동호;박흥식;전태옥
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2002.10a
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    • pp.646-649
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    • 2002
  • It can be effect on diagnosis of hydraulic machining system to analyze working conditions with shape characteristics of wear debris in a lubricated machine. But, in order to predict and estimate working conditions, it is need to analyze the shape characteristics of wear debris and to identify. Therefor, if shape characteristics of wear debris is identified by computer image analysis and the neural network, it is possible to find the cause and effect of moving condition. In this study, wear debris in the lubricant oil are extracted by membrane filter, and the quantitative value of shape characteristics of wear debris we calculated by the digital image processing. This morphological informations are studied and identified by the artificial neural network. The purpose of this study is In apply morphological characteristics of wear debris to prediction and estimation of working condition in hydraulic driving systems.

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Hardness of Ti alloys by mechanical processing methods (Ti 합금의 기계가공 방법에 따른 경도 변화에 관한 연구)

  • 반재삼;김규하;정상원;기강호;조규종
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2002.10a
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    • pp.792-795
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    • 2002
  • In previous researches, it is reported that Ti-10Ta-10Nb is robuster than Ti-6A1-4V which is used as a biomaterial in a experiment of cytotoxicity. Ti-10Ta-10Nb has enough hardness to be required as a biomaterial because the change of its hardness can be controlled more than 100% according to heat treatment condition and manufacturing condition. There are many hardness changing condition including Cast Homogenization, Solution treatment. Forging, Rolling in this research. The changing form and amount of new Ti-10Ta-10Nb to be developed in this researches, are measured as quantitative. Specially, the changing hardness amount of the specimen that is manufactured in single phase temperature, i.e. 80$0^{\circ}C$, are measured in case of high temperature rolling and high temperature cast condition.

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Development of Condition Monitoring and Diagnosis System for Rotating Machinery (회전기계의 상태감시 및 진단 시스템 개발)

  • 함종석;이종원;박성호;양보석;황원우;최연선;전오성
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.05a
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    • pp.950-955
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    • 2003
  • This paper introduces an enhanced condition monitoring and diagnosis system recently developed for rotating machinery. In the system, the data aquisition/monitoring signal processing, machine condition classifier, case-based reasoning and demonstration modules are effectively integrated with user-friendliness so that machine operators can easily monitor and diagnose the status of rotating machinery in operation. Some of the new features include the directional spectrum, case-based reasoning and neural network techniques. And the demonstrator modules for fault diagnosis of a Bear driving system and for basic understanding of the rotor dynamics are provided to help the potential users better understand the system.

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