Recently, more and more Virtual Reality (VR) and visualization solutions to support the factory layout planning process have been presented. On the one hand, VR enables planners to create cost-effective virtual prototypes and to perform virtual walkthroughs, e.g., to verify proposed layouts. On the other hand, visualization helps to gain insight into simulation results that, e.g., describe the various interdependencies between machines, such as material flows. In order to create truly effective tools based on VR and visualization, the right techniques have to be chosen and adapted to the specific problem. However, the solutions published so far usually do not exploit these technologies to their full potential.
To address this situation, we present a VR-based planning assistant that offers advanced visualization functionality that furthers the understanding of planning-relevant parameters, while also relying on established techniques. In order to realize a useful approach, the assistant fulfills three central requirements:
- A smooth integration of the assistant into existing workflows is essential in order to not disrupt them. Consequently, existing tools need to be properly integrated and a mechanism for data exchange with these tools has to be provided.
- Visualization is the main means of facilitating insight. Instead of only displaying factory models, advanced techniques to visualize more abstract quantities, like material flows or process chains, have to be provided.
- VR systems vary in the degree of immersion they offer, ranging from non-immersive desktop systems to fully immersive Cave Automatic Virtual Environment (CAVE) systems. Scalability among these systems allows adapting high-end installations as well as cost-effective solutions. However, to ensure good scalability, devising a flexible system abstraction and a unified interaction concept are essential.
The base for our planning assistant is an immersive VR (IVR) system in form of a CAVE. Our solution allows performing virtual walkthroughs and offers additional visualization techniques for planning relevant data.