선택적 레이저 용융 공정의 공정변수 평가를 위한 용융풀 유한요소 모델 (A Finite Element Model of Melt Pool for the Evaluation of Selective Laser Melting Process Parameters)

서지정보

· 발행기관 : 한국군사과학기술학회
· 수록지 정보 : 한국군사과학기술학회지 / 23권 / 3호 / 195 ~ 203페이지
· 저자명 : 이강현, 윤군진

초록

Selective laser melting(SLM) is one of the powder bed fusion(PBF) processes, which enables quicker production of nearly fully dense metal parts with a complex geometry at a moderate cost. However, the process still lacks knowledge and the experimental evaluation of possible process parameter sets is costly. Thus, this study presents a finite element analysis model of the SLM process to predict the melt pool characteristics. The physical phenomena including the phase transformation and the degree of consolidation are considered in the model with the effective method to model the volume shrinkage and the evaporated material removal. The proposed model is used to predict the melt pool dimensions and validated with the experimental results from single track scanning process of Ti-6Al-4V. The analysis result agrees with the measured data with a reasonable accuracy and the result is then used to evaluated each of the process parameter set.

영어초록

Selective laser melting(SLM) is one of the powder bed fusion(PBF) processes, which enables quicker production of nearly fully dense metal parts with a complex geometry at a moderate cost. However, the process still lacks knowledge and the experimental evaluation of possible process parameter sets is costly. Thus, this study presents a finite element analysis model of the SLM process to predict the melt pool characteristics. The physical phenomena including the phase transformation and the degree of consolidation are considered in the model with the effective method to model the volume shrinkage and the evaporated material removal. The proposed model is used to predict the melt pool dimensions and validated with the experimental results from single track scanning process of Ti-6Al-4V. The analysis result agrees with the measured data with a reasonable accuracy and the result is then used to evaluated each of the process parameter set.

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