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Special Graduate Schools
Graduate School of Science and Technology
Department of Industrial Engineering
3. Theses(Master)
차세대 직접 분말 분사 방식 적층 조형 시스템을 위한 통계 분석 기반 최적 분말 분사 조건 결정
- Alternative Title
- Nanum Lee
- Author(s)
- 이나눔
- Alternative Author(s)
- Nanum Lee
- Advisor
- 고정한
- Department
- 일반대학원 산업공학과
- Publisher
- The Graduate School, Ajou University
- Publication Year
- 2017-02
- Language
- eng
- Keyword
- Direct-write; Powder 3D-Printing; Response Surface Methodology; Functionally Graded Materials
- Alternative Abstract
- The direct-write powder-based additive manufacturing system possesses great potential to produce functionally graded materials (FGM) that require complex material property change within a product. The stable powder deposition is critical for successfully developing a new direct-write powder additive manufacturing system using bio-plastic powders. This thesis focuses on identifying the optimal process conditions of the stable powder deposition for the new additive manufacturing system. This study uses statistical analysis to uncover the relationship of the process parameters with the powder deposition consistency. The statistical analysis considers main process conditions such as the dispensing nozzle diameter, powder size range, powder type, and agitation frequency. The linearity of the cumulative deposition over time is selected as the criteria to compare the deposition consistency. The study identifies the most suitable statistical model and parameter combinations by examining the curvature of the linear model using replicated center points. The statistical analysis also evaluated the lack-of-fitness of the suggested quadratic models. In addition, this study characterizes an appropriate method to handle exceptional cases of no powder flow data by replacing this missing data value with some values in the dataset. Through these statistical analysis, this study presents a response surface model that best describes the optimal parameter combinations of stable linear powder deposition and verifies the optimal conditions. This study will help develop new additive manufacturing systems and create superior FGM structure.
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