Robotically automated 3D printing and testing of thermoplastic material specimens

Abstract

The process of development of new thermoplastic polymers, both with or without property-enhancing additives, requires preparation of test specimens to be used for subsequent characterization of materials' mechanical, fire and other properties. One of the techniques that can be employed to produce such specimens is fused deposition modeling (3D printing) though it is heavily dependent on the processing parameters that need to be adjusted for each considered material. Herein, we present an automated robotized workflow that can take polymer pellets as the input, identify 3D printing parameters to produce quality specimens and perform their mechanical property testing via the Charpy impact test. The workflow involves pellet-based 3D printers working in parallel, a collaborative robot manipulator to handle the printed specimen, a balance and camera vision system to monitor the quality of the specimen, and an analog impact tester instrument, the operation of which has been fully automated with the aid of the robot and do-it-yourself accessories. We investigate two approaches to control the workflow to identify acceptable 3D print parameters. The design of experiment approach, based on Latin hypercube sampling, can identify specimens of sufficient quality within 10 3D prints while Bayesian optimization can reach a comparable quality in fewer experiments and further improve the quality, though this comes at a much higher cost due to the experimental noise (greater or equal than 1%), the required estimation of the hyperparameters and the structure–property relationship.