Artificial Intelligence and Logistics 4.0 Are Transforming the Way We Manage Inventory by@peternavarro

Artificial Intelligence and Logistics 4.0 Are Transforming the Way We Manage Inventory

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Peter Navarro

Peter Navarro is responsible for employer branding at Sixt SE.

Logistics 4.0 is revolutionizing the way operators in the sector optimize their activities. This is reflected in the use of Artificial Intelligence (AI) in inventory management. So, how can this technology be used in this aspect?

To understand more about the topic, I spoke with Christiano Galesi, a software engineer at Resight, retail execution and monitoring platform for industries. Let's check it out.

What is Artificial Intelligence?

For those who are not yet fully familiarized with the new technologies that make up Logistics 4.0, terms like Artificial Intelligence may even seem like something from science fiction movies. But it does exist and has already been used by large companies and start-ups in the sector that are looking for a qualitative differential in existing processes in logistics.

“Artificial intelligence happens when machines and systems learn, on their own, things relevant to a given function”, explains Galesi.

The expert goes on to highlight how the technology works in more detail.

“To have this capability, AI systems have robust technology, such as artificial neural networks, algorithms, learning systems, and others. Thus, human capabilities are simulated and "copied" to be transformed into a solution that will help people and companies to draw logical reasoning, which is fundamental for decision making and strategy development.”

How is Artificial Intelligence used in inventory management?

Now that you know what AI is, it's time to understand its role in inventory management. With the new processes made possible by new technologies, what was previously done analogically, subject to human errors, communication problems, and other eventualities, is now more efficient with the use of Artificial Intelligence.

In this context, Galesi cites four good examples of how AI is used to contribute to the daily lives of industries. They are:

Demand control and prevention: If we have the dimension of the quantity of production and consumption of goods, AI systems help to determine how much labour, hours of work, and inputs will be needed. I would also add that this technology is ideal for considering different variables and situations, which allows for an even more assertive, safe projection that is feasible for that company. All of this is part of the lean production concept, in which work is carried out with the aim of mitigating errors and waste.

The great benefits of all this are: saving resources and reducing costs - priority points for companies.

Measurement of stock levels: Still talking about lean production: reducing the number of inputs is essential for more efficient and economical work in every way. Thus, using advanced AI technology to control the input and output of stock, input/output counting errors are drastically reduced.

This is true both for pull manufacturing, which uses the just-in-time technique for production (that is, with production based on the customer's order) and for push manufacturing, in which the production process is designed from the behavior of the market and consumers.

Product location and availability: Here, the AI ​​helps to trace, optimize and calculate routes for the distribution of goods at the POS, as well as the costs involved in this operation. Intelligently, the solution will make several calculations per second until it arrives at the ideal suggestion of clusters, portfolios, and routes.

Product transport automation: Thinking about the organization of inventories, AI is a very important technology for forklifts, storage systems, stacker cranes, and conveyors, which move correctly, precisely, and integrated into the storage/logistics flow without the need for operators.

As an example of Artificial Intelligence on transport automation, it is possible to highlight the advance of automated and operator-less forklifts, automatic storage systems such as stacker cranes and intelligent conveyors, digital picking systems, Internet of Things in logistics, among others.

Examples of the use of Artificial Intelligence in inventory management

As we have seen, Artificial Intelligence is a very important ally for inventory management, and market trends indicate that those who do not adapt to this and other new 4.0 logistics technologies run the risk of falling behind in the market.

Benefits of optimized inventory management for sales

The adoption of AI technology can benefit other sectors of the supply chain, such as the sellers responsible for carrying out negotiations and ensuring the delivery of orders with customers.

In this case, the application ensured that negotiations were made much more quickly and without calculation errors, as the application of discounts is done automatically with predefined models and orders are now made automatically, thus eliminating losses and the loss of important information.

Sales representatives are able to access inventory information at the time of the visit to see if the inventory can meet that demand, or through the AI ​​they can rely on predictive capabilities.

With this, the risks of the seller selling more or less than what they actually have are negligible - and, in this case, they only happen if the stock data is not updated by those responsible.

And not only that: other sales channels are also benefited, such as telesales or the B2B Portal, which also manage to inform the buyer instantly what can be delivered and what is out of stock, making it easier to do business.

As we have seen, using AI in inventory management is extremely important today for logistics operators who want to continue to stand out in the competitive market.

High-tech warehouses: risk control with Artificial Intelligence

The use of technology in warehouse management is a reality in large companies and, increasingly, its application is also being extended to small and medium-sized businesses, showing that the role has really come to an end, especially in processes in which mistakes could cause great inconvenience or loss.

The trend is to transform people into activity managers in which machines can perform operational functions more accurately – which contributes to increasing productivity and reducing the risk of work accidents.

In this new scenario, tools such as voice command, whose technology recognizes speech to allow workers to communicate with the system; or augmented reality glasses, which can assist in item checking routines, for example, appear to assist in the management and control of possible failures. Digital sensors enable entry into the new 4.0 industry model and begin to develop artificial intelligence for storage management. This opens up possibilities for more precise control, in real-time, of indicators that guarantee the quality and safety of products and installations, maximizing profits in spaces where greater quantities and variety of goods are a reality.

Final Words

Learning more about Artificial Intelligence and its application in the supply chain is a differential that is here to stay, and those who are already taking this step are getting ahead.

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