Improved Productivity with Multilaser Rotary Powder Bed Fusion Additive Manufacturing.

Laser powder bed fusion (LPBF) enables the fabrication of intricate, geometrically complex structures with a sufficiently fine surface finish for many engineering applications with a diversity of available feedstock metals. However, the production rate of LPBF systems is not well suited for mass production in comparison to traditional manufacturing methods. LPBF systems measure their deposition rates in 100's of grams per hour, while other processes measure in kilograms per hour or even in the case of processes such as forming, stamping, and casting, 100's of kilograms per hour. To be widely adopted in industry for mass production, LPBF requires a new scalable architecture that enables many orders of magnitude improvement in deposition rate, while maintaining the geometry freedom of additive manufacturing. This article explores concepts that could achieve as much as four orders of magnitude increase in the production rate through the application of (1) rotary table kinematic arrangements; (2) a dramatic number of simultaneously operating lasers; (3) reductions of laser optic size; (4) improved scanning techniques; and (5) an optimization of toroidal build plate size. To theoretically demonstrate the possibilities of production improvements, a productivity analysis is proposed for synchronous reluctance motors with relevance to the electric vehicle industry, given the recent increase in the diversity of printable soft magnetic alloys. The analysis provides insights into the impact of the architecture and process parameters necessary to optimize rotary powder bed fusion for mass production.

Automated Process Planning for Embossing and Functionally Grading Materials via Site-Specific Control in Large-Format Metal-Based Additive Manufacturing.

The potential for site-specific, process-parameter control is an attribute of additive manufacturing (AM) that makes it highly attractive as a manufacturing process. The research interest in the functionally grading material properties of numerous AM processes has been high for years. However, one of the issues that slows developmental progress in this area is process planning. It is not uncommon for manual programming methods and bespoke solutions to be utilized for site-specific control efforts. This article presents the development of slicing software that contains a fully automated process planning approach for enabling through-thickness, process-parameter control for a range of AM processes. The technique includes the use of parent and child geometries for controlling the locations of site-specific parameters, which are overlayed onto unmodified toolpaths, i.e., a vector-based planning approach is used in which additional information, such as melt pool size for large-scale metal AM processes, is assigned to the vectors. This technique has the potential for macro- and micro-structural modifications to printed objects. A proof-of-principle experiment is highlighted in which this technique was used to generate dynamic bead geometries that were deposited to induce a novel surface embossing effect, and additional software examples are presented that highlight software support for more complex objects.

Using Virtual Patients to Teach Empathy: A Randomized Controlled Study to Enhance Medical Students' Empathic Communication.

INTRODUCTION: Physician empathy is a complex phenomenon known to improve illness outcomes; however, few tools are available for deliberate practice of empathy. We used a virtual patient (VP) to teach empathic communication to first-year medical students. We then evaluated students' verbal empathy in a standardized patient (SP) interaction. METHODS: Seventy medical students, randomly assigned to 3 separate study groups, interacted with (1) a control VP portraying depression, (2) a VP with a backstory simulating patient shadowing, or (3) a VP able to give immediate feedback about empathic communication (empathy-feedback VP). Subsequently, the students interviewed an SP portraying a scenario that included opportunities to express empathy. All SP interviews were recorded and transcribed. The study outcomes were (1) the students' verbal response to the empathic opportunities presented by the SP, as coded by reliable assessors using the Empathic Communication Coding System, and (2) the students' responses as coded by the SPs, using a communication checklist. RESULTS: There were no significant differences in student demographics between groups. The students who interacted with the empathy-feedback VP showed higher empathy in the SP interview than did the students in the backstory VP and the control VP groups [mean (SD) empathy scores coded on a 0-6 scale were 2.91 (0.16) vs. 2.20 (0.22) and 2.27 (0.21), respectively). The difference in scores was significant only for the empathy-feedback VP versus the backstory VP group (P = 0.027). The SPs rated the empathy-feedback and the backstory VP groups significantly higher than the control VP group on offering empathic statements (P < 0.0001), appearing warm and caring (P = 0.015), and forming rapport (P = 0.004). CONCLUSIONS: Feedback on empathy in a VP interaction increased students' empathy in encounters with SPs, as rated by trained assessors, whereas a simulation of patient shadowing did not. Both VP interventions increased students' empathy as rated by SPs, compared with the control VP group.