Closed-loop Tool Path Planning for Non-planar Additive Manufacturing and Sensor-based Inspection on Stationary and Moving Freeform Objects

Additive manufacturing (AM) has received much attention from researchers over the past decades because of its diverse applications in various industries. AM is an advanced manufacturing process that facilitates the fabrication of complex geometries represented by computer-aided design (CAD) models. Traditionally, designed parts are fabricated by extruding material layer-by-layer using a tool path planning obtained from slicing programs by using CAD models as an input. Recently, there has been a growing interest in non-planar AM technologies, which offer the ability to fabricate multilayer constructs conforming to freeform surfaces. Non-planar AM processes have been utilized in various applications and involved objects of varying material properties and geometric characteristics. Although the current state of the art suggests AM can provide novel opportunities in conformal manufacturing, several challenges remain to be addressed. The identified challenges in non-planar AM fall into three categories: 1) conformal 3D printing on substrates with complex topography of which CAD model representation is not readily available, 2) understanding the relationship between the tool path planning and the quality of the 3D-printed construct, and 3) conformal 3D printing in the presence of mechanical disturbances. An open-loop non-planar tool path planning algorithm based on point cloud representations of object geometry and a closed-loop non-planar tool path planning algorithm based on position sensing were proposed to address these limitations and enable conformal 3D printing and spatiotemporal 3D sensing on objects of near-arbitrary organic shape. Three complementary studies have been completed towards the goal of improving the conformal tool path planning capabilities in various applications including fabrication of conformal electronics, in situ bioprinting, and spatiotemporal biosensing: i. A non-planar tool path planning algorithm for conformal microextrusion 3D printing based on point cloud data representations of object geometry was presented. Also, new insights into the origin of common conformal 3D printing defects, including tool-surface contact, were provided. The impact and utility of the proposed conformal microextrusion 3D printing process was demonstrated by the fabrication of 3D spiral and Hilbert-curve loop antennas on various non-planar substrates, including wrinkled and folded Kapton films and origami. ii. A new method for closed-loop controlled 3D printing on moving substrates, objects, and unconstrained human anatomy via real-time object position sensing was proposed. Monitoring of the tool position via real-time sensing of nozzle-surface offset using 1D laser displacement sensors enabled conformal 3D printing on moving substrates and objects. The proposed control strategy was demonstrated by microextrusion 3D printing on oscillating substrates and in situ bioprinting on an unconstrained human hand. iii. A reverse engineering-driven collision-free path planning program for automated inspection of macroscale biological specimens, such as tissue-based products and organs, was proposed. The path planning program for impedance-based spatiotemporal biosensing was demonstrated by the characterization of meat and fruit tissues using two impedimetric sensors: a cantilever sensor and a multifunctional fiber sensor.