Motion Mining is a technology for the automated analysis of manual processes in intralogistics. It is based on wearables and beacons which allow to collect and analyze process data anonymously in a realistic setting. The analysis is performed with state-of-the-art deep learning methods.
Our technology can be used for three different use cases:
1. Process analysis: Process efficiency is one of the key factors for companies to be competitive in their market. As inefficient processes waste time and money, Motion Mining helps analyzing and quantifying manual processes automatically. For example, the process can be decomposed into walking, picking, base or dead time. This allows for the identification of weak points, the improvement of manual processes and ultimately saving money.
2. Ergonomics: Ergonomics and work safety play an important role within manual processes. Motion Mining allows for detection unhealthy movements or in the worst case accidents of employees. Active feedback can inform employees about unhealthy movements. Through the learning effect, these unhealthy movements will be avoided in the future. In the case of drops and collisions, alarms can be sent to the control room.
3. Interaction: The Motion Mining technology and the used mobile sensors enable real-time gesture recognition. An interaction between your employees and your machines as well as systems can be implemented by using pre-defined gestures. For example, AGVs (automated guided vehicles) or pick-by-light systems can be operated and controlled with gestures.
We are currently looking for pilot customers for our Motion Mining solutions. We are looking for companies that have specific questions about their manual processes which can be answered by our technology within a fixed time window in the form of a consulting project.