News

06 May 2025

AI in logistics and transport: Replica Sistemi's concrete projects

In the field of logistics, Replica Sistemi has launched a series of projects using Artificial Intelligence to combine capabilities to improve the performance of the SMA.I.L:) software.

AI nella logistica e nei trasporti

Studies by the Artificial Intelligence Observatory of the Politecnico di Milano show that the turnover of the AI market and the number of companies that have launched AI projects are also increasing in Italy. 
57% of companies have already started AI processes and 25% of these are already operational.

Artificial Intelligence is not a "fad" or a "trend", but the evolution of a technological progress that began in the 1950s and has now reached an epochal turning point.

AI nella logistica e nei trasporti

Because of favourable infrastructure and market conditions, including

  • THE PROLIFERATION OF DATA CENTRES
  • INCREASED COMPUTER SPEED AND CAPACITY
  • DEVELOPMENT OF SUPER COMPUTERS (thanks to government investment) 

The proliferation of technology is contributing to lower costs, making investment in AI much cheaper than in the past.

According to the OCSE, an “artificial intelligence system” is any implementation model based on “a machine” capable of “deducing from the input it receives”, thanks to the implementation of sophisticated adaptive capacities endowed with different levels of autonomy, a series of processable data aimed at generating various “outputs” (such as, for example, “predictions, recommendations, content, decisions”, etc.), susceptible of influencing “physical or virtual environments”, taking into account a “set of explicit or implicit objectives” concretely pursued, depending on whether they are programmed directly by a human developer, or defined through the use of algorithmic self-learning techniques.

Artificial intelligence systems are software systems or even hardware systems that are able to

  • perceive their environment
  • interpret the data they collect
  • transform it into information or activities
  • reason and possibly make decisions

Humans take in information and learn through the five senses and process it to make decisions, so artificial intelligence also simulates human learning and uses its skills to perform the same functions.

The “senses” of artificial intelligence can be summarised in the following capabilities:

  • MACHINE LEARNING: is machine learning from historical data that involves the creation of patterns by training an algorithm to make predictions or decisions based on the data.
  • DEEP LEARNING: it uses neural networks that more closely simulate the complex decision-making power of the human brain and includes 
    • NATURAL LANGUAGE PROCESSION (NPL): capable of analysing, understanding and generalising human language - (e.g. chatbots)
    • COMPUTER VISION: capable of acquiring and interpreting images and videos
  • ROBOTICS: ability to perform tasks through interaction with the physical world (e.g. AMR autonomous mobile robots)
  • AUTOMATED REASONING: ability to autonomously perform a correct deductive process, i.e. the machine’s ability to analyse data and make decisions
  • KNOWLEDGE REPRESENTATION: ability to shape information in a structural format.

The machine can take input data, which may be numerical data, tables, images, etc., and transform them into the most suitable format for the type of processing to be carried out, thus modelling the information in a structured format.

In the field of logistics, Replica Sistemi has launched a series of projects using Artificial Intelligence, combining capabilities to improve both the performance within warehouses and yards, and the performance of WMS, YMS and TMS software.

AI nella logistica e nei trasporti

TMS with AI-driven planning to ensure maximum efficiency, minimise costs and minimise CO2 emissions

By analysing historical data and using machine learning, the automatic calculation of the best routes both within the warehouse (routes to be taken by the operator or AGV) and on the road (route to be taken by the delivery vehicle) has been improved.

GreenWay, the tool for calculating the carbon footprint of transport, has also been improved.


CHATBOT

We have developed a chatbot that is integrated into our software and is capable of interpreting customers’ service needs by providing first-class answers.

It also has a proactive function, as it can automatically launch certain software functions from a written or spoken command (“place a new order”, “plan a trip from to”).

AI nella logistica e nei trasporti

YMS to automate access with AI

Again, through the chatbot, videos and images can be automatically interpreted to speed up data entry for tax and operational documentation, as well as for security and control, with greater time savings and accuracy (e.g. by taking a photo of a bill of lading, all the data is stored directly in the WMS or management system, or by taking a photo of a driver's licence, ID card or vehicle registration card, all the data related to the documents is imported directly into the YMS or TMS).

AI nella logistica e nei trasporti

WMS with AI to optimise warehouse movements

In the warehouse, we use Real Time Location Systems integrated with the Replica WMS to track in real time the exact position of forklifts, operators or pallets in the warehouse, in order to assign missions to the different areas of operation.

Using various technologies such as lasers, Ultra-Wideband (short-range wireless communication protocol) or beacons (low-frequency radio transmitters using Bluetooth Low Energy technology), chosen according to the warehouse context and the level of precision required for tracking, it is possible to identify the X, Y, Z coordinates of the object or truck.

The vehicle terminals mounted on the forklifts provide the forklift driver with “road” information on the route the vehicle must take in the warehouse to move the tracked object.

AI nella logistica e nei trasporti

AMR

When we wanted to automate the handling of goods in the warehouse, we integrated MiR1200 pallet jacks into the Replica WMS, which move autonomously by mapping the routes to be taken using AI, capable of recalculating the route in the event of obstacles and adapting the width of the forks to the type of pallet to be picked.

In the case of multiple AMRs, fleet management identifies the most suitable robot (in terms of proximity, structure, battery charge) to carry out the mission in that specific section of the warehouse.

In collaboration with other companies in the Zucchetti Group, we are also improving work management for human resources management, and with the Zucchetti AI factory we are testing simulations of TMS planning in the case of autonomous truck driving.

These are the first concrete projects of AI applications in logistics and transport, but every day we receive and provide input to customers in this direction, because it is a reality that will increasingly condition work in every sphere of life, including logistics and transport!

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