Browsing by Subject "Job placement"

Now showing 1 - 1 of 1

Partitioning and placement for cooperative 3D printing
(2022-12-02) Weber, Daniel H.; Sha, Zhenghui; Chen, Dongmei
This thesis proposes novel approaches to fill in several gaps in the emerging Additive Manufacturing (AM) process of Cooperative 3D Printing (C3DP). C3DP is a rudimentary form of Swarm Manufacturing (SM), where mobile 3D printing robots can move around the factory floor and collaborate in the manufacturing environment. Several C3DP sub-processes, such as geometric partitioning for division of labor between the different robots, scheduling of tasks, and path planning of mobile robots, have been partially or fully explored in previous work; however, gaps remain in the process. These gaps include the inability to print tall objects with the current geometric partitioning method, a lack of automation for placing jobs on the factory floor, and a compromised part strength due to geometric partitioning. These must be addressed before C3DP is a viable manufacturing process for a wide variety of projects. To address these gaps, this thesis asks three fundamental research questions: 1) How can the geometric partitioning process be expanded to enable the printing of tall objects? 2) What is the optimal placement of jobs on the factory floor in a multi-print-job context? 3) How can part strength be maintained despite partitioning of the part while increasing the printing speed? To answer the first question, we propose a new Z-Chunking strategy to divide tall projects into multiple, printable jobs that can be further partitioned with the existing methodology for printing. Additionally, we automatically generate Assembly Geometry to facilitate the reconnection of the printed jobs. To show the viability of this approach, we conduct a study in which we utilize the new strategy to autonomously chunk several tall parts and perform physical printing to ensure the feasibility of reassembly. To address the second question, we develop a job placement optimization algorithm that takes into account partitioning, job structure, and the number of robots to minimize makespan. We conduct several simulations in a study to show the efficacy of the algorithm and test the impact of factors such as the number of jobs and robots, among others. For the third question, we develop a novel approach to the generation of space-filling internal cells that validates bonding strength and enables collision-free cooperation of multiple toolheads in the same workspace. By answering these questions, the gaps in the C3DP process are successfully addressed. This thesis improves the state of the art in C3DP and enables it to be successfully used as a manufacturing technique for a wide range of projects. This thesis work also expands the field of SM and brings even more flexibility to AM as a whole.