The purpose of this project is to design and implement a system that can accurately detect the fill level or blockage of scrap/parts containers used in TRUMPF’s smart factory environment. This device is being built to improve process efficiency, reduce downtime, and enable automated responses such as calling an AGV when containers approach capacity. The finished device will provide real-time monitoring of residual material levels and communicate this information through an API to other factory systems. The data gathered will provide actionable insights that can be used to optimize logistics, anticipate maintenance, and further streamline automated production processes.

Our team collaborated with Computer Science & Engineering 30,Mechanical Engineering 55 on this project.