By Nick Lung    Photo：CANVA

Since the outbreak, third-party logistics (3PL) organizations have faced a more challenging operating environment. Whether it is the Suez Canal incident, the Panama Canal drought, the Red Sea crisis and the recent Baltimore bridge being hit by a container ship, they have repeatedly shown the instability of the supply chain. It is expected that the number of orders in 2024 is increasing rapidly, and more of them are This is a small batch order, which may overwhelm the information processing system. Customers expect a reliable delivery process in a world where knowledge is increasingly mobile and substitutes are scarce, not to mention the rising incidence of delays in delivery caused by natural disasters and other force majeure factors.

A forward-looking logistics company should plan in advance to introduce systems based on artificial intelligence (AI) to meet customers’ expectations for better end-to-end logistics services or even exceed them! The following aspects are the application of artificial intelligence in the logistics industry:

Route optimization and transportation management: AI can optimize traffic routes, reduce traffic congestion, and reduce transportation time and costs by analyzing big data and real-time information. Through AI algorithms, routes and transportation arrangements can be dynamically adjusted to respond to emergencies and changes in demand.

Predictive maintenance: AI technology can monitor and analyze the operating status of logistics equipment (such as transportation vehicles, warehouse facilities, etc.) to predict potential failures or problems. Such predictive maintenance can help companies perform repairs and maintenance before problems occur, reducing downtime and maintenance costs.

Inventory management and demand forecasting: AI can predict product demand and inventory levels by analyzing historical sales data, market trends, and other relevant information. This helps companies better plan production and inventory management to avoid overstock or out-of-stock situations.

Smart warehousing and automation: AI technology can be applied in smart warehousing systems, such as robotic automatic picking systems and automated shelf management. These systems can improve warehousing efficiency, reduce labor costs, and increase order processing speed and accuracy.

Traffic and freight management: AI can be applied to traffic management systems and logistics transportation, such as intelligent traffic signal control, intelligent fleet management and real-time road condition monitoring. These applications can help increase transportation efficiency, reduce congestion, and improve traffic safety.

In general, the application of AI technology in the logistics field can help companies improve efficiency, reduce costs, improve service quality, and achieve more flexible and sustainable logistics management.
 

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