A Data Visualization Dashboard for Exploring the Additive Manufacturing Solution Space

Steven Goguelin, Joseph M. Flynn, Wesley P. Essink, Vimal Dhokia

Research output: Contribution to journalArticlepeer-review

5 Citations (SciVal)
256 Downloads (Pure)


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.

Original languageEnglish
Pages (from-to)193-198
Number of pages6
JournalProcedia CIRP
Publication statusPublished - 9 May 2017


  • Additive Manufacturing
  • Data Visualization
  • Design for Additive Manufacturing
  • Generative Design

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering


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