Data- and model-driven digital twins for design and logistics control of product distribution

Abstract

Digital control of product-on-pallet distribution is organized on two layers in logistics systems: the low-level local process automation and the supervision and coordination dual logistic execution system. The paper's scientific contribution consists in a holonic control system for multiple robot palletizing cells for product-on-pallet distribution. In this holonic control approach, data-driven digital twins (DT) are created to optimize palletizing schedules, controlled with situation awareness and resource health monitoring. A model-driven DT configuration with embedded simulation faster than real-time is combined with the data-driven DT in a meta-level control scheme offering predictive situation awareness. The paper also presents a pure model-driven DT mock-up of a robot palletizing cell - simulation with software in the loop - in which the actual holonic control system including digital twins and decision making is used in the simulation as it will be deployed in reality. This configuration is used to design the robot palletizing cells, to experiment in limit conditions, to fine tune and validate the robot control solution.