Large-Scale Robot-Based Polymer and Composite Additive Manufacturing: Failure Modes and Thermal Simulation.

Area of Science:

• Materials Science and Engineering
• Manufacturing Processes
• Computational Mechanics

Background:

• Additive manufacturing (AM) using robotic arms for large-scale polymer and composite parts is gaining traction.
• Despite advancements, failure modes like delamination and warpage limit applications in aerospace and automotive sectors.
• These failures are primarily caused by thermal gradients and residual stresses during the printing and cooling phases.

Purpose of the Study:

• To investigate and report common failure modes in large-scale additively manufactured polymer and composite parts.
• To demonstrate the utility of process simulation, specifically finite element analysis (FEA), in predicting these failures.
• To highlight the importance of accurate thermal simulations for cost reduction in large-scale robotic AM.

Main Methods:

• Analysis of failure modes in various printed parts, including fuel tanks and car bumpers.
• Implementation of finite element analysis (FEA) for process simulation of large-scale robotic additive manufacturing.
• Validation of simulation results against infrared camera temperature measurements.

Main Results:

• Delamination and warpage were identified as significant failure modes linked to thermal gradients and residual stresses.
• FEA simulations provided reasonable agreement with experimentally measured temperature distributions.
• Cooling times in large-scale AM are significantly longer (two orders of magnitude) compared to small-scale extrusion AM.

Conclusions:

• Process simulation, particularly thermal analysis via FEA, is crucial for mitigating failures in large-scale robotic AM.
• Accurate temperature prediction is the foundational step towards understanding and preventing defects.
• The extended cooling times in large-scale AM necessitate advanced simulation strategies to manage thermal stresses and ensure part integrity.