Date of Award
Mechanical, Automotive, and Materials Engineering
3D Vision System, Adaptable, Robot
Today’s automotive manufacturing facilities use different robotic systems with the specifically designed end of arm tooling (EOAT). Regardless of how accurate these robotic systems may be, they are programmed to repeat the same task and move to the same position repeatedly. As convenient as this process may be, it does not allow robots to automatically readjust to different part variations without the human assistance. This situation is especially noticeable in the plastics manufacturing industry, e.g., fuel tank welding. This thesis describes the systematic design methodology of an adaptable tooling system for a part to part variations processing aimed at automotive plastic fuel tank manufacturing. By combining a 3D vision system with a PLC, and a Fanuc R-2000iB/165F 6 axis robot, the system provides the robot with the ability to automatically readjust the processing unit to different part variations. The design approach specifies programming and device correlation by using Siemens S7, Fanuc TP, and SICK AG software. A case study using a fuel tank sample was developed to check the system for functionality and performance. Results of the study indicate that the system is accurate within ±0.25 mm, which is well suited for fuel tank manufacturing. The study signifies a new approach to vision guided robotics (VGR). It utilizes existing equipment for applications where part variation may be present. Three patent applications were published during the course of this research. They each cover plastic fuel tank welding applications.
Novakovic, Boris, "Design of an Adaptable Tooling System for Part to Part Variation Processing" (2017). Electronic Theses and Dissertations. 6006.
Available for download on Tuesday, June 19, 2018