Machine Learning's Impact on Warehouse Management
Paul MatthewsPaul Matthews
For industries that are truly open to embracing new developments in technology, machine learning and AI can be revolutionary. It effectively means that robots are able to take on tasks that would usually be assigned to humans. This kind of technology greatly improves the productivity of a business, as robots are able to complete tasks at a faster pace than humans. There’s also less margin for human error, such as a parcel being delivered to the wrong address.
Furthermore, machine learning algorithms can be used to forecast demand. It’s proving to be far more effective than existing methods that had no way of calculating demand over time. This means that a warehouse would be better equipped for coping with busier periods such as Black Friday of Christmas.
The Chinese behemoth Alibaba has a total of $248 billion transactions—more than eBay and Amazon combined! So, it’s safe to say that any company as influential as Alibaba must be entirely confident in artificial intelligence in order to use it. They now have the world’s largest automated warehouse—where some 700 robots do all of the work. These robots pick out the stock to send to customers and are now responsible for 70 percent of the work in the warehouse. Alibaba now claims that because of this technology, it'll eventually be able to deliver to anyone in China within 24 hours and within 72 hours for international customers.
Additionally, the robots are able to carry up to 500 kilograms above them as they make their way around the warehouse. Every robot is fitted with sensors, so they avoid colliding with one another. They also include a WiFi feature so they can be summoned at any time by the employees.
Alibaba is perhaps the biggest adopter of enterprise machine learning. They've used ML in warehouses to increase productivity by 70 percent.
For a huge company like Alibaba, supply chain management is crucial. Thanks to app developers, machine learning makes it possible to discover patterns in the chain using algorithms. The computer is able to analyze the existing chain and advise on which areas could be improved. Due to the nature of the computer, it’s also able to identify these flaws far quicker than manual intervention by an external assessor. Alibaba can then control inventory levels, production planning, quality and transport management.
Alibaba is not the only business bringing automation to warehouses. Amazon and food delivery service Ocado also uses robots to transport parcels around their fulfillment centers. With more and more investment being pumped into the technology, it’s likely that machine learning will be utilized more in warehouses and factories across the globe. Its potential to deliver additional value to businesses, and therefore customers, cannot be ignored. For this reason, machine learning and artificial intelligence are predicted to become an essential element in future supply chains.
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