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Aeolus Perspectives 15th Edition: Trucks: from freight vehicles to mobile data stations. The road transport jumps on the digital wave


Truck seen from another car at sunset / sunrise

The 4.0 solutions – from data acquisition to data processing - go onboard of truck both increasing the efficiency of road freight transport and enhancing the overall supply chain.

When we talk about Industry 4.0, our imagination flies towards highly innovative production plants, where automation increases efficiency and productivity, robots can replace most of the lowest added value workforce, digital technology makes machines can speak to each other, Artificial Intelligence takes up and sets every performance challenge. Industry 4.0 is a paradigm that is strongly transforming business processes. By now, however, it has no longer be exclusive to manufacturing but also to T&L. The 4.0 solutions have gone into the warehouses with cobots (collaborative robots), AGVs (Automated Guided Vehicles), automated shuttle solutions, drones and so, but they have also gone on board the trucks for many different applications.

The 2019 edition of the Contract Logistics Observatory "Gino Marchet" by Politecnico di Milano analyses the 4.0 solutions applied in the freight road transportation in all the different types of service: Full Truck Load (FTL), Less than Truckload (LTL) or groupage, last-mile. The truck is assumed as a crucial component in the wider and more complex road freight transport system that, however, also includes nodes of origin and destination such as yards for loading and unloading the goods. So, the research describes the different 4.0 solutions applied to road transport using four interconnected levels: physical system, data acquisition, data transmission, and data processing. The first one is mainly represented by the vehicles and all the pick-up and delivery points. The second level includes the technologies for collecting data generated by the physical system. The third level refers to the solutions for the transmission of the data for sharing or further processing. The fourth and final level concerns the transformation of the data into useful and structured information for decision-making purposes.

Technologies supporting data acquisition allow fully automated and real-time collection. The Contract Logistics Observatory identifies several technologies that can be applied to vehicle, transport/handling unit, delivery point, or driver. These are featured by the level of automation (from manual to fully automated) and frequency of the data acquisition process (at state change, periodic, real-time). Here we can find logistics apps, truck smart devices, telematics boxes, onboard sensors, GPS on truck or delivery unit for geofencing, and much more. It is noteworthy that the same technology can present multiple levels of automation and frequency of acquisition anyway. For example, the logistics apps allow the driver to manually enter the delivery status, but they can also be used to automatically acquire the license plate of the vehicles incoming and outcoming of a plant.

Data transmission can be realized through the more traditional Electronic Data Interchange (EDI) or even also some more recent languages such as Application Programming Interface (API).

The solutions for data processing have been defined according to the application area and the level of decentralization. The first parameter refers to the type of decision for which the information can be used: from monitoring the process to supporting the execution up to setting planning decisions and strategic business choices. The second axis concerns the way in which the transformation of data into useful information takes place: there is centralization if data is transferred to a single central node for further processing, but decentralization if before the transfer a pre-processing takes place locally (medium level) or if the processing is performed by the same node collecting data (high level). For example, the so-called "platooning" belongs to the latter category. This is a system that allows vehicles to travel in convoy autonomously, following the decisions made by the driver of the first vehicle in the row based on real-time information relating to travel speed, braking, and handling unexpected events.

Finally, plenty of these solutions can be applied both in the transport activities carried out by a single company (load management, yard management, fleet management) and within wider supply chain processes (booking of loading/unloading slot, delivery traceability, digitalization of information flows and so on).

Thanks to the integration of information between different actors as well as the development of intelligent algorithms to support the execution of processes and business decisions, the 4.0 solutions allow managing the complexity, growing efficiency and resilience of road transport processes and so also the chances to take up the next supply chains challenges.

Source: Osservatorio Contract Logistics ‘Gino Marchet’. “Tecnologia, organizzazione e competenze: la svolta per una logistica 4.0”, Politecnico di Milano, Dipartimento di Ingegneria Gestionale, November 2019.

TAGS: Aeolus perspectives, Transportation, Logistics