Optimizing a warehouse without lifting one box
Medi-Market is a Parapharmacist with both online and offline sales points. In order to make this operation run fluently, their warehouses need to be organized efficiently. We built a Digital Twin to help them optimize one of their warehouses, allowing them to assess hotspots, often picked products and possible operational congestion in a much more contextual way. The twin ingests existing data, enriches it through smart (AI-powered) analysis and displays the resulting insights in a 2D and 3D visualization of the particular warehouse. This enables the customer to analyze current workflows and simulate new, more efficient ones.
The project is currently being used by Medi-Market to get used to working with a Digital Twin and discover its potential. On our part, we’re starting a second phase in which we’ll bring it to the next level by adding new features.
Based on the (new) insights it provides, we want to focus further on implementing AI-analysis as well as bringing in more data: Which warehouse layout(s) allow (or even stimulate) the most optimal picking / putaway movements? In general or based on predicted market demands in certain periods? How substantial is the difference between such a “winter” and “summer” layout? And how do we (re)organize a part of the warehouse proactively, based on expected occurrences of heat waves, winter colds, an upcoming flu, habitational new year resolutions, etc…
Once the Digital Twin becomes capable of providing those insights; the only thing left is to make sure its state is being reflected in the real, physical warehouse as efficiënt as possible. Exciting times ahead!