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Geometric Manufacturability Analysis for Additive Manufacturing

  • Author(s): Budinoff, Hannah Dawes
  • Advisor(s): McMains, Sara
  • et al.
Abstract

During the development of a new product, it is difficult for designers to predict how their design decisions will impact manufacturability and manufacturing cost of the individual parts in their product. Additive manufacturing is increasingly becoming a viable option to produce high fidelity prototypes and even small-scale production part runs. However, as an emerging technology, there are few resources available to help designers make design decisions regarding quality and manufacturability for additive manufacturing. Most information developed to help designers ensure manufacturability is in the form of general guidelines that designers must interpret and then use their best judgment to scrutinize their design. Designers can only guess, based on previous experience, if the process can produce part features that meet their specified geometric tolerances. However, by using algorithms to analyze part geometry, it is possible to predict additive manufacturing outcomes. This thesis describes the development of two software tools to analyze part geometry in near real-time: one that predicts manufacturability, and another that predicts achievable quality.

These tools are used to explore how automated part geometry analysis influences the effectiveness of design for additive manufacturing feedback. The research hypothesis of this thesis is that part geometry analysis improves the practicality, accuracy, and usefulness of design for additive manufacturing feedback. To test this hypothesis, three research thrusts were conducted: evaluating the performance of the newly developed tools relative to existing tools, experimental verification of the predictions of the tools, and a user study evaluating usage of the manufacturability tool during a design task. Comparison with existing tools indicated that both tools described in this thesis have similar computation time as existing solutions, while providing greater potential to allow designers to analyze manufacturing trade-offs, with a more comprehensive approach to modeling sources of errors in the manufacturing process. A range of parts were printed using fused deposition modeling and then inspected. The experimental results showed that the predictions of both tools were relatively accurate, and highlighted several additional process parameters that can be included in the modeling approach to improve accuracy. Lastly, a user study demonstrated that use of the software tool reduced the number of manufacturability problems in participants' designs while requiring a similar amount of time to use, compared with using a list of design heuristics. The findings of the thesis support the practicality, accuracy, and usefulness of geometry analysis software tools to support design for additive manufacturing.

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