Automated Planning and Optimization of a Draping Processes Within the CATIA Environment Using a Python Software Tool

Abstract

This thesis deals with the challenge of the virtual generation and optimization of complex production processes within the Computer Aided Design (CAD) environment CATIA V5. A flexible robot end-effector (Modular Gripper) is used for automated draping process which serves as an example application. Previous experiments have shown that manually selecting all process parameters that are needed to adapt the grippers geometry is a very time consuming and inaccurate method. For this reason, a tool was developed that is able to determine or optimize the end-effector specific process parameters offline. Since all existing models are available in the CATIA environment, the goal was to perform this optimization process within the same environment. The software tool is based on a hierarchical architecture where all calculations and logic optimization processes are processed in the programming language Python. All commands in the CATIA environment are performed with the help of small, modularized CATScript programs that are able to interact with main Python algorithms. This work is intended to lead to a virtual optimization process that can be universally applied to complex manufacturing processes. Since it is based on a Python framework that is able to interact directly with the CATIA environment, it is flexible enough so that it can be adapted to further processes.