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Traditional manufacturing processes such as injection or compression molding are often enclosed and pressurized systems that produce homogenous products. In contrast, 3D printing is exposed to the environment at ambient (or reduced) temperature and atmospheric pressure. Furthermore, the printing process itself is mostly “layered manufacturing”, i.e., it forms a three-dimensional part by laying down successive layers of materials. Those characteristics inevitably lead to an inconsistent microstructure of 3D printed products and thus cause anisotropic mechanical properties. In this paper, the anisotropic behaviors of 3D printed parts were investigated by using both laboratory coupon specimens (bending specimens) and complex engineering structures (A-pillar). Results show that the orientation of the infills of 3D printed parts can significantly influence their mechanical properties.

3D printing is a revolutionary manufacturing method that allows the productions of engineering parts almost directly from modeling software on a computer. With 3D printing technology, future manufacturing could become vastly efficient. However, the procedures used in 3D printing differ substantially among the printers and from those used in conventional manufacturing. The objective of the present work was to comprehensively evaluate the mechanical properties of engineering products fabricated by 3D printing and conventional manufacturing. Three open-source 3D printers, i.e., the Flash Forge Dreamer, the Tevo Tornado, and the Prusa, were used to fabricate the identical parts out of the same material (acrylonitrile butadiene styrene). The parts were printed at various positions on the printer platforms and then tested in bending. Results indicate that there exist substantial differences in mechanical responses among the parts by different 3D printers.

This paper gives an overview and summary of two projects conducted over the past two years. The first project hosted a Web-based Maintenance Resource Management (MRM) Seminar on the Safe Maintenance in Aviation Readiness and Training (SMART) Center for FLSW personnel in the Fall of 1999. The SMART Center utilizes the technical capabilities of the World Wide Web to provide resources and training for the continuing education of aviation maintenance personnel. The second project analyzed and tested the DoD sponsored Advanced Distributed Learning Sharable Content Object Reference Model (ADL SCORM) specification using the SMART Center as the basis for the analysis and testing of the specification. The Naval Postgraduate School in conjunction with the Naval Safety Center is currently conducting an evaluation of the new ADL SMART Center. The results of that evaluation will be presented during the World Aviation Congress conference.

The Maintenance Extension of the Human Factors Analysis and Classification System (HFACS-ME) was employed to categorize errors present in 470 FY 90-97 Naval Aviation Maintenance Related Mishaps (MRMs). HFACS-ME identified common error types present in MRMs: maintenance supervision, crew coordination, maintainer error, and procedural violations. The data derived from classifying maintenance errors was used to develop mathematical models that were then employed to generate notional cost estimates associated with them. These models were then used to forecast the potential impact of maintenance error interventions. Collectively, the taxonomic analysis and model development served to identify common maintenance error forms, and consequently the optimal targets that have the most potential return on investment (ROI).