서지주요정보
사출금형 가공시간 예측에 관한 연구 = A study on the estimation of machining time for injection molds
서명 / 저자 사출금형 가공시간 예측에 관한 연구 = A study on the estimation of machining time for injection molds / 김창용.
저자명 김창용 ; Kim, Chang-Yong
발행사항 [대전 : 한국과학기술원, 2001].
Online Access 원문보기 원문인쇄

소장정보

등록번호

8012400

소장위치/청구기호

학술문화관(문화관) 보존서고

MME 01069

휴대폰 전송

도서상태

이용가능

대출가능

반납예정일

초록정보

Injection molds are made with the highest precision because they have to meet a variety of requirements. They are to some extent produced by greatly time- and cost- consuming procedures. So to make injection molds efficiently, processes have to be planed with estimated machining time before molds are manufactured. But in many shops the system for estimation of machining time, is not in the place to which it should be entitled. The machining time was estimated based on experience or in comparison with molds in the past by experienced workers, but either method has the problem of broad range of error. This paper proposes a new method for estimation of machining time by neural networks. This system can improve the reliability of system as machined data of molds are added that is different from previous method. The selection of input factors is very important for using this system for estimation of machining time by neural networks, therefore this paper recommends few general input factors and special factors for TV molds. Such input factors are divided into shape factors, machining condition factors and machining time factors. The propriety of selected input factors is verified as the machining time of TV molds proposed by this paper is less estimated than error of actual process plan. Using this system, processes of manufacturing molds will be more efficient by reducing range of error and consequently, improve the competitive power of molds industry.

서지기타정보

서지기타정보
청구기호 {MME 01069
형태사항 ix, 71 p. : 삽도 ; 26 cm
언어 한국어
일반주기 저자명의 영문표기 : Chang-Yong Kim
지도교수의 한글표기 : 양민양
지도교수의 영문표기 : Min-Yang Yang
학위논문 학위논문(석사) - 한국과학기술원 : 기계공학전공,
서지주기 참고문헌 : p.70-71
주제 가공시간
사출금형
신경망
machining time
injection mold
neural networks
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