Pon Logistics – Dynamic Assembly
Pon Logistics is committed to enhancing both efficiency and sustainability in our operations. Our latest project addresses the significant issue of underutilized space in containers and trucks. To tackle this, we have developed an advanced algorithm that predicts daily container requirements for each dealer and determines the optimal container size.
Every night, our algorithm forecasts the order size for each dealer and simulates the container fill rate. This process ensures that Pon Logistics can avoid repacking containers and prevents the selection of oversized containers, thereby minimizing wasted space. By simulating container fullness at the start of each day, we can accurately assess whether they can accommodate the forecasted volume of unknown orders.
The project’s deliverable is a Tableau dashboard that provides daily predictions for each dealer. This dashboard specifies the containers that need to be prepared each morning and includes historical data on order volumes. It also allows users to adjust the maximum container fill level to reconcile any discrepancies between theoretical and actual volumes.
We plan to launch this tool in September, once the data is live. This initiative marks a significant step toward improving logistics efficiency and supporting our sustainability goals by reducing the number of trucks on the road. Additionally, during our innovation days, we are exploring ways to expand the algorithm to optimize truck loading and integrate it with a route optimization algorithm.
Ellen Mik
Senior Data Scientist
Roy Gomersbach
Data Scientist