A Data Visualization Dashboard for Exploring the Additive Manufacturing Solution Space
A Data Visualization Dashboard for Exploring the Additive Manufacturing Solution Space
复制标题
用于探索增材制造解决方案空间的数据可视化仪表板
DOI：
10.1016/j.procir.2017.01.016
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Goguelin S
中科院分区：
文献类型：
--
作者：
Goguelin S
本文将研究使用数据可视化工具作为探索增材制造（AM）解决方案空间的方法。增材制造的挑战之一是理解在设计空间中发生的权衡。如果有许多性能指标，那么理解设计的整体性能通常是具有挑战性的。本文提出了一种增材制造数据可视化仪表板，其特点是三个阶段的过滤过程。第一阶段利用平行坐标图按类别搜索解组并减小解空间的大小。其次，过滤后的解决方案显示在散点图上，为设计师提供了检查AM特定设计变量之间相关性的能力。最后，设计师能够从散点图中选择设计，进一步使用条形图和雷达图来评估单个部件的性能。还显示了部件的可视化表示。以增材制造零件为例，探讨了增材制造零件的解空间。参数化模型用于生成一系列设计方案，以便使用交互式可视化仪表板进行探索。执行了三次设计迭代，每次迭代的结果用于通知下一个参数化模型的开发。本研究的结果表明，交互式数据可视化工具是探索增材制造解决方案空间的关键，它有助于设计师更深入地理解问题陈述，并允许生成改进的设计解决方案。
This paper will examine the use of data visualisation tools as a method for exploring the additive manufacturing (AM) solution space. One of the challenges of AM is understanding the trade-offs that occur within the design space. It is often challenging to understand the overall performance of a design if there are many performance indicators. This paper presents an AM data visualisation dashboard which is characterised by a three stage filtering process. The first stage utilises a parallel coordinate plot to search through groups of solutions by category and reduce the size of the solution space. Secondly, the filtered solutions are displayed on a scatter plot, providing the designer with the ability to check for correlations between AM specific design variables. Finally, the designer is able to select designs from the scatter plot to evaluate an individual part performance further using both a bar and radar chart. A visual representation of the part is also shown. A case study is presented in which the solution space for an additively manufactured part is explored. A parametric model was used to generate a series of design alternatives to be explored using the interactive visualization dashboard. Three design iterations were performed with the results from each iteration used to inform the development of the next parametric model. The results from this study show that interactive data visualization tools are key to exploring AM solution spaces, assisting designers to gain a deeper understanding of the problem statement and allowing for the generation of improved design solutions.
增材制造设计：自动构建方向选择和优化
DOI：
--
发表时间：
2016
期刊：
影响因子：
--
作者：
M. Zwier;W. Wits
通讯作者：
W. Wits
影响因子：
2.4
作者：
Yassin Ashour;Branko Kolarevic
通讯作者：
Branko Kolarevic