Curved layer process planning for robotic multi-axis additive manufacturing

Abstract

Additive Manufacturing (AM) technology offers tremendous flexibility in fabricating complex geometries and low material wastage in contrast to conventional manufacturing techniques. However, the layer-by-layer build up process and the fixed build direction native to the AM technology cause pronounced staircase effect and requirement of support-structures in fabricating 3D geometries with large overhang areas, thus limiting the true potential of AM. The initial concept of curved multi-axis AM emerged to realise support-structure-free fabrication by exploiting the enhanced build direction flexibility. Since this method allows fabricating along non-planar (i.e., curved) tool paths with a continuously changing nozzle orientation, the possibility of support-free fabrication of geometries with minimised staircase effect has been evident in theory. However, in practice, multi-axis fabrication suffers from a number of manufacturing constraints that diminish the complexity of geometries that could be fabricated in a support-free manner. Local gouging (i.e., collisions induced between the printer nozzle and the printed portions) has been an inevitable constraint that is native to the concave features of the decomposed surface layers. Efforts that have been taken to improve the convexity (i.e., eradicate concavity) in decomposed surface layers have either failed in maintaining support-free quality in curved fabrication or suffered with severe surface artifacts and approximation errors. Furthermore, there has been minimal effort towards enhancing the fabrication surface quality (i.e., surface finish) in 3D geometries fabricated through curve layer decomposition. This thesis presents a new volumetric curved layer decomposition method that generates concavity reduced (if not eradicated) and surface quality improved curved surface layers while maintaining overhang angles below the support-structure-free thresholds to realise multi-axis fabrication. Mathematical modelling frameworks for surface concavity identification, volumetric error approximation and overhang angle condition monitoring are developed to evaluate the impact of manufacturing constraints within a set of decomposed layers. Based on the severity of these impacts, a weighted gradient vector field that represents the 3D volume of the given model is designed by employing the Radial Basis Functions (RBF). Weights are optimised through a genetic algorithm-based optimisation model to find the ideal RBF parameters that would generate the best possible set of decomposed surface layers minimising the manufacturing constraints. Finally, a contour parallel multi-axis fabrication tool path is designed on each decomposed curved surface layer to realise physical fabrication. A novel strategy to plan the nozzle orientation vector is presented to minimise collisions and to achieve safe fabrication. To validate the presented curve layer decomposition method and the tool path, simulations and physical experiments are performed with selected 3D geometries that contain not only complex geometrical features (i.e., high-genus) but also high overhang areas.

Date of Award	2022
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology
Supervisor	Ravindra Stephen GOONETILLEKE (Supervisor) & Kai TANG (Supervisor)