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The Effects of Laser and Electron Beam Spot Size in Additive Manufacturing Processes

In this work, melt pool size in process mapped in power-velocity space for multiple processes and alloys. In the electron beam wire feed and laser powder feed processes, melt pool dimensions are then related to microstructure in the Ti-6Al-4V alloy. In the electron beam wire feed process, work by previous authors that related prior beta grain size to melt pool area is extended and a control scheme is suggested. In the laser powder feed process, in situ thermal imaging is used to monitor melt pool length. Real time melt pool length measurements are used in feedback control to manipulate the resulting microstructure. In laser and electron beam direct metal additive manufacturing, characteristics of the individual melt pool and the resulting final parts are a product of a variety of process parameters. Laser or electron beam spot size is an important input parameter that can affect the size and shape of a melt pool, and has a direct influence on the formation of lack-of-fusion and keyholing porosity. In this work, models are developed to gain a better understanding of the effects of spot size across different alloys and processes. Models are validated through experiments that also span multiple processes and alloys. Methods to expand the usable processing space are demonstrated in the ProX 200 laser powder bed fusion process. In depth knowledge of process parameters can reduce the occurrence of porosity and flaws throughout processing space and allow for the increased use of non-standard parameter sets. Knowledge of the effects of spot size and other process parameters can enable an operator to expand the usable processing space while avoiding the formation of some types of flaws. Based on simulation and experimental results, regions where potential problems may occur are identified and process parameter based solutions are suggested. Methods to expand the usable processing space are demonstrated in the ProX 200 laser powder bed fusion process. In depth knowledge of process parameters can reduce the occurrence of porosity and flaws throughout processing space and allow for the increased use of non-standard parameter sets.

Identiferoai:union.ndltd.org:cmu.edu/oai:repository.cmu.edu:dissertations-1948
Date01 May 2017
CreatorsFrancis, Zachary Ryan
PublisherResearch Showcase @ CMU
Source SetsCarnegie Mellon University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceDissertations

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