Additive Manufacturing, using FDM® technology, has provided an innovative method for creating manufacturing aids, tools, and production parts for a wide variety of industries. Substantial investments, both from a supplier and end user perspective, have been directed towards producing and utilizing these solutions for widescale use and diverse applications. In order for any additive manufacturing technology to be thoroughly integrated into a manufacturing workflow, it is essential that the solution combining hardware, software, and material deliver a robust and predictable performance. In particular, the repeatability of the solution to deliver consistent intra- and inter-machine results over time is of paramount interest. This paper characterizes the performance of printed parts, through mechanical property analysis, dimensional repeatability, and various other metrics of print quality, on the Stratasys F370™, Fortus 450mc™, and F900™ systems using multiple materials. The data presented indicates excellent intra-system control of mechanical properties (XZ in-plane) with less than 5% coefficient of variation across each system type, using the entire system build volume and over several months of testing. Similarly, inter-system comparisons show excellent system-to-system consistency, generally within the 5% coefficient of variation for all materials and conditions tested. Properties in the z-axis (ZX) (upright) indicate the expected limitations of layer by layer processing by FDM, increasing variability in mechanical properties to generally less than 10% variance for all materials and conditions tested. Dimensional precision of printed geometry was shown to lie within 2% variation for all systems, materials, and geometries evaluated. Additionally, across the 1200 builds over the 16 systems, three materials, and various geometries used, the FDM systems performed with better than a 92% success rate for first time job completion. The data presented provides a user of these solutions confidence in printed part performance within a system, across multiple systems, and over time.
