A Gaussian Process Model-Guided Surface Polishing Process in Additive Manufacturing
A Gaussian Process Model-Guided Surface Polishing Process in Additive Manufacturing
复制标题
增材制造中高斯过程模型引导的表面抛光工艺
DOI：
10.1115/1.4045334
复制
发表时间：
2020
期刊：
影响因子：
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通讯作者：
Ding, Yu
中科院分区：
文献类型：
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作者：
Jin, Shilan;Iquebal, Ashif;Bukkapatnam, Satish;Gaynor, Andrew;Ding, Yu
增材制造产品的抛光是一个多阶段的过程，每个阶段使用不同的抛光垫和工艺参数组合。垫改变的决定和终点的确定目前依赖于从业人员的经验和主观目视检查表面质量。对于交付一致性和减少可变性，更需要一个自动化和客观的决策过程。为此，本文提出了一种钛合金工件抛光过程的模型指导决策方案。所使用的模型是一系列高斯过程模型，每个模型都是为收集表面数据的抛光阶段建立的。一系列高斯过程模型似乎能够捕捉表面变化和抛光过程中的变化，从而产生由样品表面上的相关特征通知的决策协议。发现低相关性表明存在可能被认为是表面缺陷的极端粗糙度。在表面关联中明智地使用变化模式可以提供及时行动的洞察力。通过对钛合金样品进行物理抛光并进行仿真，验证了该方法的优越性。
Polishing of additively manufactured products is a multi-stage process, and a different combination of polishing pad and process parameters is employed at each stage. Pad change decisions and endpoint determination currently rely on practitioners’ experience and subjective visual inspection of surface quality. An automated and objective decision process is more desired for delivering consistency and reducing variability. Toward that objective, a model-guided decision-making scheme is developed in this article for the polishing process of a titanium alloy workpiece. The model used is a series of Gaussian process models, each established for a polishing stage at which surface data are gathered. The series of Gaussian process models appear capable of capturing surface changes and variation over the polishing process, resulting in a decision protocol informed by the correlation characteristics over the sample surface. It is found that low correlations reveal the existence of extreme roughness that may be deemed surface defects. Making judicious use of the change pattern in surface correlation provides insights enabling timely actions. Physical polishing of titanium alloy samples and a simulation of this process are used together to demonstrate the merit of the proposed method.
RESER’ FC 90-229 使用轴承面积曲线的新方法
DOI：
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发表时间：
1999
期刊：
影响因子：
--
作者：
Rokeya Begum;Rokeya Begum;M. S. Rahman;A. M. S. Chowdhury;M. M. Rahman;M. Rashid
通讯作者：
M. Rashid