4rd Use Case
Overview
Logistics and warehouse management is a critical part of modern supply chains, especially for sensitive goods like frozen or temperature-controlled products. Catone Group operates a fleet of over 200 refrigerated vehicles, equipped with advanced monitoring and security systems, to ensure quality and compliance throughout the entire distribution process.
Challenges & Objectives
Managing a high-volume, distributed warehouse ecosystem presents several challenges, including the need to ensure efficient planning and the smooth operation of automated storage and transport processes. At the same time, maintaining product quality throughout storage and delivery, especially through precise temperature control, is critical. Equally important is supporting workforce well-being, safety, and motivation within a highly automated environment. Overall, the goal is to streamline operations from order to delivery, reduce energy consumption, and improve the reliability of the entire logistics process.
Technical Approach
This use case applies AI-driven orchestration and automation to manage the entire warehouse ecosystem. Stacker cranes handle automated storage, while predictive models optimize pallet movement, transport schedules, and storage utilization. Human operators remain central in the loop to oversee operations, ensuring safety and compliance while benefiting from smarter tools that make their work more efficient and less repetitive.
Expected Impact
The UniMaaS platform provides real-time monitoring and recommendations, helping manage energy usage, storage space, and delivery performance. Digital Twins allow data-driven insights to improve processes, reduce waste, and enhance workforce conditions. By integrating AI, robotics, and human oversight, the system achieves a balance between efficiency, sustainability, and human-centered operations.
Indicative KPIs
The solution is expected to deliver improved storage efficiency, with storage savings reaching up to 15%. At the same time, better coordination and optimized operations will contribute to a reduction in energy consumption by around 10%, as well as a similar decrease in fuel consumption across the vehicle fleet. In parallel, particular emphasis is placed on workforce conditions, with the aim of achieving high levels of well-being and safety, reflected in a score above 3.5 on a 5-point scale.
Partners
CATONE
National and Technical University of Athens (NTUA)
Queens University of Belfast
(QUB)
