Cloud-Based Design and Manufacturing is a service-oriented networked product development model in which service consumers are enabled to configure, select and utilize customized product realization services ranging from computer-aided engineering software to reconfigurable manufacturing systems. So far, this paradigm has mainly been tested for digital design and fabrication processes including the usual steps of designing an artefact with a CAD system to then have a prototype manufactured with a 3D printer. Unfortunately, a common mishap that can often be observed is that artefacts that look perfectly fine on the CAD computer screen come out severely misshaped on the 3D printer. In this paper, we first investigate and document this phenomenon and explain its root cause, which concerns a) the data transmitted to the 3D printer, b) inappropriate design features, and c) a mismatch between geometry requirements and printer capabilities. As more and more entrepreneurs, hobbyists in maker communities, and other not always fully trained individuals pursue their design and make ideas, there is a need for smart computer-based support to facilitate a successful design-to-print process. Such a digital DfM assistant might pop up to prompt a designer to modify identified critical areas of the design so that it can be printed with a chosen printer or alternatively propose another type of printer that may have the technical capabilities to accommodate the design in its current form. Acknowledging this need, we propose a two-stage smart manufacturability assistant. The first stage decomposes the digital model into a series of part features; the second stage of the model involved defining the capabilities of the 3D-printer. Finally, we begin to realize this manufacturability assistant by creating and evaluating a bespoke test part which can be used to define a machine-material capability map for an example FDM process.
Goguelin, S., Colaco, J., Dhokia, V., & Schaefer, D. (2017). Smart Manufacturability Analysis for Digital Product Development. In Procedia CIRP (Vol. 60, pp. 56–61). Elsevier B.V. https://doi.org/10.1016/j.procir.2017.02.026