Integration and evaluation of robotic fused filament fabrication system

Abstract

Fused filament fabrication (FFF) continues to be among the most widespread additive manufacturing process for making polymeric functional prototypes, and in several cases end-use parts. There is a large installed base of serial-link industrial robots, some of which could be potentially retrofitted with an extruder head as an end-effector to serve as FFF systems with as many as six degrees of freedom compared to 3-axis gantry mechanisms that are typically deployed today. This paper identifies and proposes solutions to key engineering challenges that arise in retrofitting such robotic FFF systems in terms of integrating robot motion controller with extruder controller and evaluating the quality of the fabricated parts. Specifically, we propose an approach for integration and real-time synchronization of controllers to ensure that the extrusion velocity and deposition velocity match closely by building upon an analytical model for predicting road geometry as a function of process parameters. Compared to gantry mechanisms, this is challenging in serial-link industrial robots because of significantly larger and space-variant inertias. Furthermore, to compensate for distortion in the bed surface of the retrofitted robotic FFF system, a bed compensation algorithm based on bilinear interpolation has been developed. We have engineered a fully functional research testbed in which integration and real-time synchronization of controllers is achieved by (1) communicating space-variant process parameters in real-time using TCP/IP sockets, and (2) analog and digital I/O interfacing. Experimental testing shows excellent (R2 = 0.9983) agreement between requested and actual volumetric flow rates and less than 5% errors in extrusion widths and heights in test samples fabricated across the range of physical limits of FFF process parameters. The testbed is also evaluated in terms of the impact of controller synchronization on the part dimensional accuracy for simple and complex geometries. This work can serve as a basis for further engineering innovations towards cost-effectively harnessing the capacity of industrial robots to manufacture geometrically accurate parts using FFF.