The creation of a neural network based capability profile to enable generative design and the manufacture of functional FDM parts
The creation of a neural network based capability profile to enable generative design and the manufacture of functional FDM parts
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DOI：
10.1007/s00170-021-06770-8
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发表时间：
2021-02-27
影响因子：
3.4
通讯作者：
Nassehi, Aydin
中科院分区：
文献类型：
--
作者：
Goudswaard, Mark;Hicks, Ben;Nassehi, Aydin
为了使用丝沉积建模 (FDM) 制造功能部件，有必要了解机器的功能。由于缺乏将制造工艺参数与制造零件的机械性能相关的知识，获得这种理解提出了重大挑战。先前的工作表明，可以通过创建 FDM 机器的功能配置文件来克服这一问题。然而，这种方法尚未实施并纳入整个设计过程。相应地，本文的目标有两个，包括为 FDM 创建全面的功能概况，以及在生成设计方法中实施该概况并评估其实用性。为了为能力概况提供基础，本文首先报告了一个实验测试程序，以表征五个制造参数对零件极限拉伸强度 (UTS) 和拉伸模量 (E) 的影响。该表征用于训练人工神经网络 (ANN)。该 ANN 构成了能力概况的基础，该能力概况能够代表 UTS 为 1.95 MPa 的 RMSEP 和 E 为 0.82 GPa 的 RMSEP 机械性能。为了验证能力概况，它被纳入生成设计方法中，使其能够应用于功能部件的设计和制造。由此产生的方法用于创建两个承载组件，结果表明只需几次迭代即可生成性能令人满意的零件。所报告工作的新颖性在于展示了功能配置文件在 FDM 设计过程中的实际应用，以及它们如何与生成方法相结合，代替用户做出有效的设计决策。
In order to manufacture functional parts using filament deposition modelling (FDM), an understanding of the machine's capabilities is necessary. Eliciting this understanding poses a significant challenge due to a lack of knowledge relating manufacturing process parameters to mechanical properties of the manufactured part. Prior work has proposed that this could be overcome through the creation of capability profiles for FDM machines. However, such an approach has yet to be implemented and incorporated into the overall design process. Correspondingly, the aim of this paper is two-fold and includes the creation of a comprehensive capability profile for FDM and the implementation of the profile and evaluation of its utility within a generative design methodology. To provide the foundations for the capability profile, this paper first reports an experimental testing programme to characterise the influence of five manufacturing parameters on a part's ultimate tensile strength (UTS) and tensile modulus (E). This characterisation is used to train an artificial neural network (ANN). This ANN forms the basis of a capability profile that is shown to be able to represent the mechanical properties with RMSEP of 1.95 MPa for UTS and 0.82 GPa for E. To validate the capability profile, it is incorporated into a generative design methodology enabling its application to the design and manufacture of functional parts. The resulting methodology is used to create two load bearing components where it is shown to be able to generate parts with satisfactory performance in only a couple of iterations. The novelty of the reported work lies in demonstrating the practical application of capability profiles in the FDM design process and how, when combined with generative approaches, they can make effective design decisions in place of the user.