Research on hybrid manufacturing using industrial robot
type: CreativeWork
description: "The applications of using industrial robots in hybrid manufacturing overcome many restrictions of the conventional manufacturing methods, such as small part building size, long building period, and limited material choices. However, some problems such as the uneven distribution of motion accuracy within robot working volume, the acceleration impact of robot under heavy external loads, few methods and facilities for increasing the efficiency of hybrid manufacturing process are still challenging. This dissertation aims to improve the applications of using industrial robot in hybrid manufacturing by addressing following three categories research issues. The first research issue proposed a novel concept view on robot accuracy and stiffness problem, for making the maximum usage of current manufacturing capability of robot system. Based on analyzing the robot forward/inverse kinematic, the angle error sensitivity of different joint and the stiffness matrix properties of robot, new evaluation formulations are established to help finding the best position and orientation to perform a specific trajectory within the robot's working volume. The second research issue focus on the engineering improvements of robotic hybrid manufacturing. By adopting stereo vision, laser scanning technology and curved surface compensation algorithm, it enhances the automation level and adaptiveness of hybrid manufacturing process. The third research issue extends the robotic hybrid manufacturing process to the broader application area. A mini extruder with a variable pitch and progressive diameter screw is developed for large scale robotic deposition. The proposed robotic deposition system could increase the building efficiency and quality for large-size parts. Moreover, the research results of this dissertation can benefit a wide range of industries, such as automation manufacturing, robot design and 3D printing"--Abstract, page iv.
abstract: "The applications of using industrial robots in hybrid manufacturing overcome many restrictions of the conventional manufacturing methods, such as small part building size, long building period, and limited material choices. However, some problems such as the uneven distribution of motion accuracy within robot working volume, the acceleration impact of robot under heavy external loads, few methods and facilities for increasing the efficiency of hybrid manufacturing process are still challenging. This dissertation aims to improve the applications of using industrial robot in hybrid manufacturing by addressing following three categories research issues. The first research issue proposed a novel concept view on robot accuracy and stiffness problem, for making the maximum usage of current manufacturing capability of robot system. Based on analyzing the robot forward/inverse kinematic, the angle error sensitivity of different joint and the stiffness matrix properties of robot, new evaluation formulations are established to help finding the best position and orientation to perform a specific trajectory within the robot's working volume. The second research issue focus on the engineering improvements of robotic hybrid manufacturing. By adopting stereo vision, laser scanning technology and curved surface compensation algorithm, it enhances the automation level and adaptiveness of hybrid manufacturing process. The third research issue extends the robotic hybrid manufacturing process to the broader application area. A mini extruder with a variable pitch and progressive diameter screw is developed for large scale robotic deposition. The proposed robotic deposition system could increase the building efficiency and quality for large-size parts. Moreover, the research results of this dissertation can benefit a wide range of industries, such as automation manufacturing, robot design and 3D printing"--Abstract, page iv.
author: Wang, Zhiyuan
keywords: Adaptive Path Compensation, Fused Pellet Extruder, Hybrid Manufacturing, Industrial Robot, Large-scale Robotic Deposition, Stereo Vision, Mechanical Engineering
date modified: 2026-07-24T03:18:50Z
provider: Missouri University of Science and Technology
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Missouri University of Science and Technology