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Abstract The support structures required in many forms of additive manufacturing are often seen as waste that is tolerated as necessary. In metal additive processes, cost is frequently reduced by minimizing the amount of support structures needed to produce a part so that in turn, material use is decreased. However, there still exists the challenge of generating parts that are not deformed by the stresses created in the process. In this case study, support structures were leveraged to address deformation. A part was printed via direct metal laser melting with supports with a high grouping density in areas of high anticipated deformation in order to stiffen the part to prevent deformation. Then, they were printed again with a low grouping density to allow the part to relax and reduce stress. Combinations of support strategy and leaving supports on during post processing were used to investigate the effects of keeping or removing the supports in post-print operations such as surface treatment. The two optimized support strategies saw a lower deformation than the baseline approach to supports, and the releasing strategy was closest to the reference solid model with a 26% reduction in average deformation. The results suggest that the support structures in additively manufactured parts have a different impact on the part than the original intent of the supports to simply alleviate a process requirement. The support structures should be used to impact the final part geometry. 

Manufacturing engineers work in teams with a wide range of skills and credentials. Teamwork and collaborative problem solving (CPS) skills enable higher productivity and efficiency. However, these skills are largely absent from engineering education curricula and research in contexts involving multi-educational teams inclusive of technical college engineering students. We address this gap in research and practice through a qualitative case study exploring the contributions, experiences, and perspectives of technical college students working in multi-educational level teams to solve real-world engineering manufacturing problems. Data analyses resulted in six themes: (1) positive team culture, (2) valuing industry skills, (3) sharing responsibilities to iteratively make changes, (4) applying technical roles, (5) peer interactions, and (6) career preparation. Technical college students’ perceptions of challenges and successes are also discussed. Results imply that to effectively promote CPS and teamwork in similar contexts educators and industry leaders should consider the importance of (1) valuing students’/workers’ current professional identities while promoting productive conflict, (2) respecting differing team roles while encouraging skill development, and (3) fostering future career skills. 

The use of sit-stand desks (SSD) has shown positive results in reducing sitting time for office workers. Different factors can help with the use of the table, such as participatory ergonomics and an SSD reminder system. However, little is known about the influence of social factors at work, such as the influence of peers or supervisors using the device. The aim of this study was to investigate the use of SSDs and how the location and proximity of office workers affects SSD utilization over the course of two months. One-hundred eighty workers with SSDs participated in this study, and their desk locations and utilization were documented. It was observed that office workers spent on average (standard deviation) 7.1% (20.8%) of their time standing at their desks each day. Among these users, 12 participants were categorized as high SSD users, which spent more than two hours a day standing on average. It was found that during the study period, participants located next to high SSD utilizers did not change the SSD usage by increasing or decreasing their time spent standing. The results from the study suggest that the relative locations and proximity of workers do not significantly influence users to increase SSD use, and high users do not impact the SSD use of other users. These results showed that SSD use by peers or supervisors is not a strong social factor in improving the worker’s behavior of using the table and that other combined strategies are necessary. 

Work-related musculoskeletal disorders contribute to significant loss in productivity and higher costs for employers. This research utilizes body-worn motion and hand-worn force sensors to provide non-intrusive and continuous recognition of tasks, estimate force exertion, and evaluate if operators are working in safe ergonomic ranges. Work-related motions such as lifting, carrying, pulling, and pushing are measured with varied loads up to 10 kg, and then recognized performed using the IBM Watson cloud service platform. The experiments use sequential and quasi-static postures and mimic those commonly found in an automotive assembly environment. Classification performance included generating 70 input features based on 6 motion and 4 force inputs and three of the resulting classifier had a greater than 90% accuracy in simultaneously classifying both the weight being carried and the task being completed. Future work includes measuring non-quasi-static motions and integrating additional sensors, such as those from smart tooling, which tracks tool position and orientation, to provide a continuous and unobtrusive evaluation of worker exertion and risk of musculoskeletal disorder. 

Keywords : DMLM, Additive Manufacturing, Support Structures, Gas Turbines