Designing a Mobile Application for Evaluating Manufacturability of Parts Using Additive Manufacturing

Restricted (Penn State Only)
Author:
Dinda, Shantanab
Graduate Program:
Industrial Engineering
Degree:
Master of Science
Document Type:
Master Thesis
Date of Defense:
July 24, 2017
Committee Members:
  • Timothy William Simpson, Thesis Advisor
  • Nicholas Alexander Meisel, Committee Member
  • Janis P Terpenny, Committee Member
Keywords:
  • 3D printing
  • Additive Manufacturing
  • Mobile Application
  • Manufacturability Analysis
  • Voxel-based Models
  • Voxelization
  • Build Time Estimation
  • Cost Estimation
Abstract:
Additive Manufacturing has seen a rapid growth in the last few years, with industries considering it as a viable manufacturing process that is redefining product design and supply chain. The recent increase in public awareness and interest in additive manufacturing has been a great boost for material extrusion systems for 3D printing, with such systems becoming readily affordable and easy to use, promoting hands-on experience with polymer printing. Material extrusion has progressed from being a novel process with expensive machinery to a cheap, easy and relatively fast method for 3D printing. This has helped it transition from a cumbersome process to one for teaching additive manufacturing and prototyping at very low costs and lead times. However, the ease of material extrusion may also cause it to become the go-to manufacturing process for the user in every case. This necessitates the user to be aware that material extrusion may not be the ideal process in every case, and more importantly understand how one can make the selection of the appropriate additive manufacturing process. This thesis focuses on the design and implementation of software algorithms and a mobile application to help users evaluate the feasibility of fabricating parts using material extrusion. The algorithm uses novel voxel-based manufacturability analyses, which takes the desired STL file as input and generates a voxelized model with supports. Using the voxelized model and specified machine parameters, the software estimates build time, weight of material required for the part and supports, and the cost of 3D printing the part, allowing users to make an informed decision on process selection. Additionally, the visuals generated by the algorithm also allow the user to determine the appropriate build iv orientation. Experimental benchmarking was performed on the algorithm, where after careful selection of experimental parts to be printed, the algorithm’s predictions are compared to experimental results for validation. The final version of the algorithm and code serves as the backbone for a mobile application, built with an easy to use interface for rapid visual evaluation of parts in terms of orientation, build time, and cost of printing. Ongoing and future work along with potential uses are also discussed, with the final goal of making the application ready to be downloaded and utilized by any user.