Mixed Digital/Physical Simulation Models for PI Networks

The key objective of this report is to develop the digital and physical simulation models necessary to assess different scenarios with central focus on the evaluation and design of the Generic Physical Internet Case Study (GPICS) simulation components. The components are designed sufficiently generic to ensure that the Generic Physical Internet scenario can be fully represented, taking also into account Living Lab specific requirements.
This document explains a methodology of analysis of business cases through simulation which has been defined based on the approach identified by Law and Kelton . The main steps include designing and developing a simulation model, designing a simulation experiment, and finally performing simulation analysis.
Previous versions of this document primarily focused on the simulation modelling activities. In order to design the models, multiple face-to-face and virtual meetings were held, to determine the specific requirements of each of the living labs in the Physical Internet (PI) context.
This third version of the document contains the description of the physical simulation model developed to be integrated with the PI services. The living labs selected to test the digital simulation are LL1 (PI Hub-centric
Network) and LL2 (Corridor-centric PI Network). The document also contains updated scenarios from LL3 (eCommerce centric PI Network) and LL 4 (Warehousing as a Service). According to the iterative methodology
defined, the simulation model begins with the description of the model making multiple assumptions, and progressively evolves by adding real constraints.
Simulation models include real data from the living labs. They are based on the actual logistics processes from the companies. Additionally, they contain some modifications to execute the movement of goods according to
the Physical Internet principles. This report has initial KPI evaluation in the Living Lab selected, and for the initial version of the GPICS. The simulation scenarios are evaluated with the key performance indicators defined. The simulation model helps to evaluate operational factors like the fill rate of the transport or the lead time. Economic factors like the transport cost and the handling cost and environmental factors like the CO2 emissions estimation.
Further evolution of the simulation model will include additional information coming from the services and architecture defined in other project tasks. Actual data from real-life physical components will also be integrated in the simulation to formalized the Physical Simulation.

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This project is funded from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 769119

The views expressed by the ICONET Consortium do not necessarily represent the views of the EU Commission/INEA.
The Consortium and the EU Commission/INEA are not responsible for any use that may be made of the information it contains
EU-flag-(high-resolution)

This project is funded from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 769119

The views expressed by the ICONET Consortium do not necessarily represent the views of the EU Commission/INEA.
The Consortium and the EU Commission/INEA are not responsible for any use that may be made of the information it contains