Date of Award

6-2025

Degree Name

MS in Mechanical Engineering

Department/Program

Mechanical Engineering

College

College of Engineering

Advisor

Eric Espinoza-Wade

Advisor Department

Mechanical Engineering

Advisor College

College of Engineering

Abstract

Geometrically and physically accurate 3D models are emerging as essential tools for surgeons in pre-operative planning and training, but current methods of producing these models are not sufficient. Existing solutions have downsides such as high costs, long and tedious production times, high complexity resulting in a lack of scalability, or an inability to meet material requirements for accurately simulating human tissue.

The objective of this work is to develop principles for a low-cost, easy-to-use 3D printing system capable of prototyping with soft tissue-mimicking materials. To pursue this goal, a MyCobot280 robot arm was used as the mechanism to explore the relevant hardware, software, and material requirements for such a system. The first contribution of this work is the design of a robotic end effector that holds a syringe and depresses the plunger on command. Simultaneously, the robot is programmed to parse a given G-code file to move along specific coordinates, creating an extrusion process for any desired structure. The second contribution is to identify a material that meets both the extrudability criteria and the mechanical properties of human soft tissue. Finally, a relationship is to be developed between the two contributions, defining the extrusion parameters required for producing a successful 3D model.

For the first contribution, a mechanically actuated linkage design was implemented for successful depression of the syringe plunger, controlled via velocity control. A Python script was successfully developed to extract coordinates and extrusion data from a G-code file and then send the appropriate motion and end effector commands to the robot at the correct time.For the second contribution, a UV-curing resin and two two-part platinum-cure silicones—selected for their matching Shore Hardness and Young’s Modulus to fibrocartilage, as well as reasonable viscosity—were tested for functionality. Experiments were conducted to determine the optimal syringe size, line overlap, and extrusion speed. This analysis identified BASF’s UltraCur3D as the best selection and defined the parameters and methods necessary for customizing the Python script and slicing process accordingly. The results from robot motion and end effector control, identified material, and extrusion parameters outline a set of important principles for developing a low-cost, multi-material 3D printing process using materials that replicate soft tissue. These principles can be used to establish a design process that can be replicated and customized for use with a variety of machines or robots.

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