Unveiling Circular Value Chains: Insights from AUTO-TWIN's Graph Model Discoveries

by Politecnico di Milano

The Politecnico di Milano (PMI) research team is developing methods and tools for model discovering services and the recent activities on the Auto-Twin first illustrative case have yielded significant findings.

Employing a graph model learning algorithm, the team has systematically delineated the underlying structure of the system, revealing two distinct closed loops:

Loop 1: Commencing from the BoxStation, where items are initially packaged, the sequence progresses through the PalletStation for further processing. Subsequently, the items traverse the Warehouse to the Market for distribution. Upon completion of their lifecycle or return, the items undergo refurbishment, leading them back to the RefurbishedBoxWarehouse and ultimately returning to the BoxStation to initiate a new cycle.

Loop 2: Similar to the preceding loop, this cycle originates from the BoxStation, then proceeds through the PalletStation. However, instead of progressing directly to the Warehouse, the items undergo refurbishment at the RefurbishProcess stage. Post-refurbishment, they are stored at the RefurbishedBoxWarehouse before looping back to the BoxStation.

This discovery underscores the efficacy of the graph model learning algorithm in unraveling intricate systems characterized by multiple interconnected circular value chains.