Cyber physical approach and framework for micro devices assembly

The emergence of Cyber Physical Systems (CPS) and Internet-of-Things (IoT) based principles and technologies holds the potential to facilitate global collaboration in various fields of engineering. Micro Devices Assembly (MDA) is an emerging domain involving the assembly of micron sized objects and devices. In this dissertation, the focus of the research is the design of a Cyber Physical approach for the assembly of micro devices. A collaborative framework comprising of cyber and physical components linked using the Internet has been developed to accomplish a targeted set of MDA life cycle activities which include assembly planning, path planning, Virtual Reality (VR) based assembly analysis, command generation and physical assembly. Genetic algorithm and modified insertion algorithm based methods have been proposed to support assembly planning activities. Advanced VR based environments have been designed to support assembly analysis where plans can be proposed, compared and validated. The potential of next generation Global Environment for Network Innovation (GENI) networking technologies has also been explored to support distributed collaborations involving VR-based environments. The feasibility of the cyber physical approach has been demonstrated by implementing the cyber physical components which collaborate to assemble micro designs. The case studies conducted underscore the ability of the developed Cyber Physical approach and framework to support distributed collaborative activities for MDA process contexts

Modeling and experimental validation of a parallel microrobot for biomanipulation

The main purpose of this project is the development of a commercial micropositioner's (SmarPod 115.25, SmarAct GmbH) geometrical model. SmarPod is characterized by parallel kinematics and is employed for precise and accurate sample's positioning under SEM microscope, being vacuum-compatible, for various applications. Geometrical modeling represents the preliminar step to fully understand, and possibly improve, robot's closed loop behaviour in terms of task's quality precision, when enterprises does not provide sufficient documentation. The robotic system, in fact, represents in this case a "black box" from which it's possible to extract information. This step is essential in order to improve, consequently, the reliability of bio-microsystem manipulation and characterization. Disposing of a detailed microrobot's model becomes essential to deal with the typical lack of sensing at microscale, as it allows a 3D precise and adequate reconstruction, realized through proper softwares, of the manipulation set-up. The roles of Virtual Reality (VR) and of simulations, carried out, in this case, in Blender environment, are asserted as well as an essential helping tool in mycrosystem's task planning. Blender is a professional free and open-source 3D computer graphics software and it is proven to be a basic instrument to validate microrobot's model, even to simplify it in case of complex system's geometries

Automatic Microassembly of Tissue Engineering Scaffold

Ph.DDOCTOR OF PHILOSOPH

Design and implement a micro assembly machine for mechanical watch movements.

Yang, Fan.Thesis (M.Phil.)--Chinese University of Hong Kong, 2009.Includes bibliographical references (leaves 73-77).Abstracts in English and Chinese.Abstract --- p.I摘要 --- p.IIITable of Contents --- p.VList of Figures --- p.iList of Tables --- p.AChapter 1. --- Introduction --- p.1Chapter 1.1. --- Literature Review --- p.1Chapter 1.2. --- Project Background --- p.10Chapter 1.3. --- Objectives --- p.14Chapter 2. --- Design of the micro assembly machine --- p.16Chapter 2.1. --- Aspects that need to be met --- p.16Chapter 2.2. --- Hardware of the micro assembly machine --- p.17Chapter 2.2.1. --- The vision system --- p.18Chapter 2.2.2. --- The control system --- p.19Chapter 2.2.3. --- The Actuating System --- p.21Chapter 2.2.3.1. --- The gripper --- p.22Chapter 2.2.3.2. --- The three axes --- p.28Chapter 2.2.3.3. --- The workbench --- p.31Chapter 2.2.4. --- The complete structure of the micro assembly machine --- p.32Chapter 2.3. --- The main features of the micro assembly machine --- p.34Chapter 3. --- Implementation --- p.35Chapter 3.1. --- Vision system --- p.35Chapter 3.2. --- Setting up the vision system --- p.36Chapter 3.3. --- Efficiency and form of the transferred data --- p.38Chapter 3.4. --- Control system --- p.39Chapter 3.4.1. --- Structure of the control system --- p.40Chapter 3.4.2. --- System control process --- p.44Chapter 3.4.3. --- The GUI --- p.45Chapter 3.4.4. --- Data processing --- p.48Chapter 3.5. --- Cooperation between the vision system and the control system --- p.49Chapter 4. --- Experimental results --- p.51Chapter 4.1 --- Accuracy in the x and y directions --- p.51Chapter 4.2 --- Effect of the vision system on accuracy --- p.57Chapter 4.3 --- Depth of the assembled ruby bearings --- p.62Chapter 4.4 --- Gradient of the rubies --- p.65Chapter 4.5 --- Analysis of the experimental data --- p.68Chapter 5 --- Conclusion and Future Work --- p.70References --- p.7