Project Description:

This research addresses sustainability in high-performance manufacturing by investigating the full recycling lifecycle of fiber-reinforced thermoplastic composites used in Extruder Deposition Additive Manufacturing (EDAM). The core scientific challenge is to quantify material degradation over multiple use cycles, specifically tracking fiber length reduction during shredding and polymer degradation from thermal cycling. The intern will manage the full material cycle, including hands-on operation of the EDAM printer, feedstock preparation, and rigorous material characterization (mechanical, thermal, physical) of both virgin and recycled parts. Opportunities exist to assist with printing simulations and validation to analyze part performance.

Requirements:

Essential qualifications include a strong hands-on aptitude for laboratory work, proficiency in data analysis using tools like Excel or MATLAB, and a genuine interest in sustainable manufacturing technologies. Prior experience with FDM 3D printing, CAD software, or computational modeling/Finite Element Analysis (FEA) is highly desirable, though not strictly required.

Project Description:

This project addresses a critical bottleneck in sustainable aerospace and automotive manufacturing: the precision machining of 3D-printed Carbon Fiber Reinforced Thermoplastics. Because these materials are prone to melting and fiber pull-out, traditional "trial-and-error" machining fails. Our research aims to develop a physics-informed optimization strategy by analyzing how toolpath kinematics, such as cutting direction and fiber angle, impact thermal buildup and surface quality. The undergraduate intern will join the Cyber-Physical Manufacturing Lab to conduct hands-on CNC experiments, utilizing advanced sensors (thermal cameras, accelerometers) to capture real-time process data. Students will also perform microscopic surface analysis to identify defects, helping to build data-driven process maps for next-generation composite manufacturing.

Requirements:

We are seeking an undergraduate student who has a strong interest in advanced manufacturing. While prior research experience is not required, familiarity with CAD/CAM software (such as Fusion 360, CATIA or Mastercam), machining experience, and basic data analysis skills (using Excel, Python, or MATLAB) are highly preferred. We are looking for a detail-oriented individual with good documentation skills who is eager to learn hands-on experimental techniques in a collaborative lab environment.