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Mitigating Material Mist in “Polyjet” 3D Printing for Improved Print Quality
ME-C-31
Erel Ron; erelron@email.com Shoval Dry; shoval.dry@gmail.com
Advisors: Ms. Nataliya Dvoskin1, Mr. Jonathan Balter2 1SCE - Shamoon College of Engineering, Be’er-Sheva 2Stratasys, Ltd.
“PolyJet” 3D printing technology enables high-resolution, multi-material printing, but suffers from material mist formation, where tiny droplets spread uncontrollably, affecting print precision and surface quality. This project explores engineering solutions to reduce material mist by optimizing airflow and implementing cooling mechanisms. Our research examines factors, such as jetting parameters, chamber ventilation, and temperature fluctuations, that contribute to mist formation. Proposed solutions include improved airflow design, active and passive cooling systems, and thermoelectric cooling (TEC) for precise temperature control. Additionally, the integration of passive cooling fins is explored towards enhanced heat dissipation and reduced reliance on high-speed fans. The goal is to develop an effective solution that minimizes turbulence, ensures thermal stability, and significantly enhances print accuracy and part consistency.
Keywords: 3D printing, cooling, material mist, “Polyjet”, print quality
Autonomous Medical Logistics Robot
ME-D-32
Shahar Tarshish; shahar1106@gmail.com Nathanel Garsholker; natigarsholker@gmail.com
Advisor: Dr. Etan Fisher
SCE - Shamoon College of Engineering, Be’er-Sheva
In large hospitals like Soroka/University Medical Center, manual transport of medical equipment, medications, and lab samples increases staff workload and delays. Autonomous systems using AI and Robotics can optimize logistics, reducing transport times and errors.
Our project goal is to develop an autonomous medical transport robot with ‘light detection and ranging’ (LiDAR), depth cameras, and advanced sensors for navigation. This involves mechanical and electrical design, sensor integration, and navigational algorithms. Initial tests show successful obstacle detection and path planning. After refining navigation and conducting real-world trials, this system should enhance hospital logistics, reduce burdens, and improve response times.
Keywords: autonomous robot, medical equipment transport, navigational algorithms, sensor integration