Design and manufacturability data on additively manufactured solutions for COVID-19

Rohan Prabhu; Jordan S Masia; Joseph T Berthel; Nicholas A Meisel; Timothy W Simpson

doi:10.1016/j.dib.2021.107012

Design and manufacturability data on additively manufactured solutions for COVID-19

Data Brief. 2021 Mar 27:36:107012. doi: 10.1016/j.dib.2021.107012. eCollection 2021 Jun.

Authors

Rohan Prabhu¹, Jordan S Masia¹, Joseph T Berthel¹, Nicholas A Meisel², Timothy W Simpson^{1

3

2}

Affiliations

¹ Department of Mechanical Engineering, Pennsylvania State University, University Park, PA 16802, USA.
² School of Engineering Design, Technology, and Professional Programs, Pennsylvania State University, University Park, PA 16802, USA.
³ Department of Industrial Engineering, Pennsylvania State University, University Park, PA 16802, USA.

Abstract

Designers around the world have leveraged the rapid prototyping and manufacturing capabilities of additive manufacturing (AM), commonly known as 3D printing, to develop numerous engineering design solutions for the COVID-19 pandemic. This dataset consists of the design and manufacturability data for twenty-six such engineering design solutions spanning three categories: (1) face masks (N = 12), (2) face shields (N = 6), and (3) hands-free door openers (N = 8). The designs were collected from open-source websites such as Thingiverse, GrabCAD, and the NIH 3D Print Exchange. The manufacturability of these designs was simulated using Ultimaker Cura software and three measures were obtained: (1) build time, (2) build cost, and (3) build material. Furthermore, these simulations were performed for multiple materials and infill densities for comparison. Additionally, the manufacturing cost using injection molding was simulated using the Cost Estimation Tool in Solidworks. This dataset comprises (1) the STL files for the designs, (2) the simulated manufacturability data (for additive manufacturing and injection molding), and (3) images that depict the build orientation used in these manufacturability simulations. This dataset can facilitate the development of future innovations that leverage the capabilities of AM processes. Furthermore, this dataset can be used by designers and manufacturers to compare solutions and choose appropriate ones for manufacturing.

Keywords: 3D Printing; Additive manufacturing; COVID-19; Engineering design; Manufacturability.