In the automotive industry, short ramp up times and high product quality drive the development toward state-of-the-art solutions both in the research and industrial perspective. In addition to that, a sustainable industry requires optimized equipment utilization, in terms of materials used and consumed energy.
This thesis is a contribution in the never-ending process of achieving the goals above described and has as focus virtual product realization for robot assembly. Virtual methods, indeed, decrease the need for prototyping and can simulate, and thereafter optimize the robotic assembly process.
In order to optimize equipment utilization and assembly time for a new product, this thesis presents algorithms and tools to check geometrical feasibility and minimize cycle time in multirobot stations. Robustness for the assembly process is very important, therefore geometrical variation is also considered during path and assembly planning. In fact, one of the contribution is a tool integrating robot path planning and geometrical variation for robot assembly. The main idea is to let the robot move in the workspace areas where there is less uncertainty. Another tool presented integrates assembly design, sequence optimization and path planning, which can be used in order to evaluate different concepts regarding locating scheme and the robustness in its critical dimensions. The major contribution is a new approach to schedule robot operations to avoid collisions and minimize cycle time for multirobot stations. Two articles present algorithms and tools to distribute the operations workload among several robots and coordinate them.
These new ideas and their implementation in software platforms can improve virtual product realization for robotic applications by requiring less expert knowledge from the user and making automatic optimization not only part of delivering a detailed solution but also letting it be part of the decision making process.