Artificial Intelligence is known to be a growing trend in many industries around the world. And it is no mystery when logistics and transportation are looking for ways to apply such technology for the improvement of all their operations within the supply chain. From back office solutions to IoT control solutions, there are several examples of artificial intelligence in logistics.
However, for people who are not deeply involved in the industry, it is not very clear to them what specific operations AI is involved in. What are the current supply chain issues for the supply chain to be optimized with AI? And what advantages does this technology confer over the competition?
If you want to learn how AI is being applied in supply chain management with these examples of artificial intelligence in logistics, take a look!
Sectors such as e-commerce have gained much relevance in recent years, so the increase in demand and the need for a more efficient storage management call for a solution. For this reason, there has been a notable trend in warehouse automation as one of the notable examples of artificial intelligence in logistics.
Warehouse automation encompasses various operations, from the application of automated storage systems with stacker cranes to warehouse management software. Within it, they use data analysis and demand forecasting to coordinate various processes in the warehouse.
And not only do they perform this step, but they synchronize the tasks of both the operators and the automated systems. In this way, personnel can focus on other tasks.
This operation usually goes hand in hand with warehouse automation and, it seems, is going to be an essential element for companies. Currently, it is known that the volume of shipments is dropping considerably due to inflation, as a result of which stock is accumulating and will take longer than desired to accumulate in the warehouse.
First, the warehouse is stocked with the right amount of inventory according to demand prediction based on previous sales, market analysis, among others. Then, automation systems would be unified with catalog control to improve stock visibility by alerting on low stock levels and detecting defective products and packaging before they are shipped via AI cameras or sensors.
Thanks to one of the examples of artificial intelligence in logistics, it is possible to reduce error margins and time spent on tasks, obtaining high customer satisfaction and competitive advantage over other companies where logistics plays a crucial role.
One of the most popular solutions within the logistics and transportation industry is to optimize delivery routes using AI software. It is also one of the most important in order to ensure on-time deliveries at the most economical price and fuel cost possible.
Among the functions of a route optimizationsoftware is to integrate data from various sources and use algorithms to plan routes according to the constraints to be applied at the time of deliveries. In this way, resources (vehicles and carriers) can be optimally organized, costs can be saved, and competent customer service can be provided.
One of the current problems in the transportation sector is the lack of new vehicles on the market that can replace the old ones, thus requiring constant repairs to be operational. However, predictive maintenance is not as well known as one of the examples of artificial intelligence in logistics.
Using past and present data collected with IoT devices, machine learning algorithms can create predictions and maintenance recommendations for trucks, vans and other vehicles. In this way, the service life of vehicles is increased and further damage can be prevented thanks to these indications.
Several logistics processes are already being successfully automated and optimized thanks to AI. These solutions are key to overcoming the current challenges facing the logistics sector and offering a competitive and efficient service that responds to current trends and needs.
At Hedyla we offer several products and services developed with AI by our in-house engineering team that seeks to respond to the logistics needs of any sector.
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