Artificial intelligence is revolutionizing the way we approach activities across all business sectors.
The topic has come back to the fore strongly after the launch of “generative” applications, in which algorithms are asked not only to work on numerical data, but to produce an output according to the context. It is a completely revolutionary scenario, never explored before, which will pave the way for a revolution in terms of automation and improved efficiency in all areas of industry and work.
The application that has tuned the general public to the use of AI is ChatGPT: an extremely advanced model that works on language and is able to manage millions of parameters in its comprehension and generation of texts. Clearly, language as an element of contact towards the human being has made the approach between the two easier, bringing the machine closer to man: on the other hand, language represents one of the most ancestral aspects of the human being, and observing a machine capable of understanding and answering questions in a natural way is rather surprising.
But there are also applications closer to the industry that are quickly taking place.
For example, automatic pattern recognition allows us to determine whether, in a handling line, we are transferring products into boxes – and of what size – or hanging products and of what type, whether they are outerwear or shirts, based on the depth of the hanger used.
By appropriately training AI models to enhance the movement of goods in the fashion / luxury sector and delivering the results of the calculations performed in real time, we can expect to obtain an acceleration in the execution of usually manual work:
- Counting processes
- Identification of anomalies in the transport or sorting lines
- Optimization of containment in packaging
- Optimized withdrawals
A branch less exploited at the moment is the forecasting area, less touched by the topical moment of generative AI. However, there are excellent chances of obtaining equally amazing results by applying algorithms capable of working on reliable forecasts in the logistics area:
- Wait per period of incoming/outgoing volumes
- prediction of picking activities and consequent optimized preparation of picking missions
- Advance assessment of courier needs and early warning of the same
A warehouse that uses AI equipped, for example, with an Autostore can also work at night in the absence of personnel, making collection missions ready in the morning for the first shipments to be managed at the start of the work shifts.
Or, an automated warehouse with aerial handling systems can move products in the absence of personnel and carry out, working in combination with IoT technologies such as RFID tags, continuous and cyclic inventories.
Artificial intelligence is rapidly gaining ground in the industrial sector, bringing with it a wave of change and innovation. Thanks to it, companies can face great challenges, and knowing how to seize opportunities is crucial to ensure the competitiveness and success of companies in an increasingly interconnected and rapidly changing world.