Online Measurement for Parameter Discovery in Fused Filament Fabrication

IF 2.4 3区 材料科学 Q3 ENGINEERING, MANUFACTURING Integrating Materials and Manufacturing Innovation Pub Date : 2024-04-03 DOI:10.1007/s40192-024-00350-w
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Abstract

To describe a new method for the automatic generation of process parameters for fused filament fabrication (FFF) across varying machines and materials. We use an instrumented extruder to fit a function that maps nozzle pressures across varying flow rates and temperatures for a given machine and material configuration. We then develop a method to extract real parameters for flow rate and temperature using relative pressures and temperature offsets. Our method allows us to successfully find process parameters, using one set of input parameters, across all of the machine and material configurations that we tested, even in materials that we had never printed before. Rather than using direct parameters in FFF printing, which is time-consuming to tune and modify, it is possible to deploy machine-generated data that captures the fundamental phenomenology of FFF to automatically select parameters.

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在线测量用于发现熔丝制造中的参数
摘要 介绍一种自动生成不同机器和材料的熔融长丝制造(FFF)工艺参数的新方法。我们使用一台带仪器的挤出机来拟合一个函数,该函数可映射给定机器和材料配置下不同流速和温度下的喷嘴压力。然后,我们开发了一种方法,利用相对压力和温度偏移来提取流速和温度的实际参数。我们的方法使我们能够使用一组输入参数,在我们测试过的所有机器和材料配置中成功找到工艺参数,即使是我们以前从未打印过的材料。在 FFF 印刷中,直接使用参数需要耗费大量时间来调整和修改,而使用机器生成的数据则可以捕捉到 FFF 的基本现象,从而自动选择参数。
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来源期刊
Integrating Materials and Manufacturing Innovation
Integrating Materials and Manufacturing Innovation Engineering-Industrial and Manufacturing Engineering
CiteScore
5.30
自引率
9.10%
发文量
42
审稿时长
39 days
期刊介绍: The journal will publish: Research that supports building a model-based definition of materials and processes that is compatible with model-based engineering design processes and multidisciplinary design optimization; Descriptions of novel experimental or computational tools or data analysis techniques, and their application, that are to be used for ICME; Best practices in verification and validation of computational tools, sensitivity analysis, uncertainty quantification, and data management, as well as standards and protocols for software integration and exchange of data; In-depth descriptions of data, databases, and database tools; Detailed case studies on efforts, and their impact, that integrate experiment and computation to solve an enduring engineering problem in materials and manufacturing.
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