Save time and costs by automating intralogistics

In an age of immediacy, of wanting and having, where an agile system of logistics flows is essential to satisfy the customer, intralogistics is becoming increasingly important.

What is intralogistics?

This concept, the focus of this post, has gained prominence in recent years with the boom in e-commerce, and refers to the processes involved in internal logistics, which we will look at in more detail throughout this article.

Traditionally, efforts and resources have been devoted to the gradual improvement of the means and modes of transporting goods. Minimizing time, distance, and fleet units have been the major challenges for decades. Later, the birth and rise of e-commerce revealed the great potential for improving internal warehouse processes.

That is precisely what intralogistics focuses on: as its name suggests, it refers to all the movements of materials or products carried out within the company itself, from the receipt of raw materials to the point where the product is ready and its dispatch to the customer is managed.

Space utilization, placement, internal location and mobility systems, product traceability, and the administrative procedures required to validate shipments and manage destinations are all part of these intralogistics processes, which deserve special attention as a means of optimizing and improving the supply chain.

As we can see, the concept of intralogistics is broad, since it does not focus solely on warehouse organization and performance, but extends, as we are seeing, to all types of internal material movement and the associated management tasks, starting from the very moment the raw material is received.

And what is intralogistics 4.0?

Like all 4.0 processes, intralogistics 4.0 involves automating processes to achieve greater efficiency, speed, safety, and profitability. The rapid evolution of Data Science and Artificial Intelligence has made it possible to bring digital transformation to all business operations, and internal logistics is no exception.

Warehouses are no longer disorganized spaces where goods simply wait between production and dispatch. They are now true distribution centers where it is essential to make the most of every available inch of space, have a good product location system, develop internal mobility solutions, and use data exploitation tools that facilitate stock management.

Automating intralogistics

If we start with the most basic aspect, the storage of goods, the first thing that comes to mind is space management—making the most of the available infrastructure capacity. Here, the capabilities of Artificial Intelligence and Big Data are essential, enabling the development of planning tools that organize products to optimize space, save time on internal movements, make items easy to locate, and ensure smooth flows and turnover.

In this regard, code-reading systems, automatic counting with computer vision, goods location, and product traceability are great allies for planners, as they enable full control of SKUs throughout the intralogistics processes—that is, across all the stages involved in internal logistics.

Once products and raw materials have been placed and identified, process automation also makes it easier to move them around the facility quickly and safely. As we can see, warehouse management is far more efficient with the support of technology, to the point that major distribution centers like Amazon handle their internal distribution using smart conveyor belts, in what have come to be known as smart warehouses or warehouses 4.0.

We must also bear in mind that intralogistics is subject to market pressures: demand peaks, sales dips, promotions, seasonality, and so on—all factors that must be taken into account to guide the proper management of internal logistics processes. In this regard, predictive systems such as demand forecasting tools, predictive maintenance, and digital twins help teams stay ahead of what’s to come by establishing forecasts for a given time horizon.

This provides highly reliable predictions of how much product will leave the warehouse within a given timeframe, simplifying decision-making and allowing stock levels to be adjusted to the circumstances outlined above. This makes it possible to manage the inflow and outflow of SKUs based on objective data, rather than relying on the subjective experience of past campaigns.

But all of this must go hand in hand with proper management of every link in the supply chain, which is where Robotic Process Automation (RPA) comes into play. Thanks to artificial intelligence and machine learning, large volumes of desktop tasks can be handled. This simplifies and streamlines administrative tasks of all kinds, including those associated with logistics management that are highly repetitive and low in added value (delivery notes, invoicing, e-CMR, etc.).

Artificial Intelligence, Big Data, and intralogistics

As we have seen, the development of Artificial Intelligence and Data Science has also revolutionized internal logistics. Process automation and the shift toward Industry 4.0 are paving the way for business models that are far more efficient, agile, flexible, and profitable, with a strong capacity to navigate the ups and downs of a globalized, ever-changing market.

Logistics is proving to be a key element in maintaining customer satisfaction levels, based mainly on product quality and delivery time—especially at this time of booming e-commerce. In this context, streamlining internal logistics processes through automation is essential for companies to remain competitive in increasingly complex markets.