In this project, I built a digital shadow to evaluate the impact of a new process design for a collaborative robot picking system. The system operated across three key stages: induct, picking, and drop-off.

Key Objectives:
- Build a simple, lightweight model using only timestamp data from bot mission logs
- Track each robots location over time to visualize their flow through the system
- Calculate mission times, processing times, and queue times by tracking robot IDs
- Identify queue lengths and variability
- Track performance patterns

Results:
The digital shadow was developed and deployed in under a day, quickly identifying the system's bottleneck. After the process design change, it was used to validate that the intervention reduced the bottleneck at the drop-off station, resulting in higher overall throughput and improved bot flow. The simplicity of the model provided a fast, effective way to visualize high-level system performance and assess the impact of process changes despite having limited data.