Machine learning article originally published by, and permission to publish here provided by, Adam Robinson at https://cerasis.com.
Machine learning, a branch of artificial intelligence, has already been used across many industries to improve efficiency and productivity.
The technology has been in development for some time, with the uptake being slowed down by some industry’s reluctance to adopt it.
However, it’s now being used by many businesses, including logistics companies and retailers seeking help for warehouse management.
Where Does Machine Learning Currently Stand?
Currently, machine learning is used in a variety of sectors including healthcare, law, education and science. Because of its ability to learn and process information, it is proven to be especially useful for industries that need to comprehend large amounts of data.
In law, the technology is able to filter through large amounts of important information in an impressively short amount of time. This is saving employees hours of work that can then be spent on other tasks, thus greatly improving productivity. In healthcare, it’s being used to for faster diagnosis for patients, while also predicting future problems a patient may face.
Thanks to the advanced technology, it’s also able to scan moles that could potentially be cancerous. Even though it’s still in its infancy, machine learning and artificial intelligence are already having a great impact across many industries.
Supply Chain Management
Machine learning makes it possible to discover patterns in the supply chain by using algorithms that can analyze the success of the chain, while also picking up on aspects that can be improved. These algorithms are able to identify flaws quickly and effectively, much more efficient than manual intervention by an assessor.
Machine learning in supply chain management can especially impact inventory levels, quality, supply and demand, production planning and transport management. This is important for supply chain management moving forward, particularly when applied to warehouse management.
Machine Learning Applied To Warehouse Management
Innovation is thriving thanks to machine learning, even more so in industries who are looking to use robots to take on tasks that would usually be assigned to a human.
Take Alibaba, for example. They now have the world’s largest automation warehouse whereby the robots can pick goods ready to send out to customers. These robots now do 70% of the work in the warehouse. The robots are able to carry up to 500 kilograms above them as they make their way around. Every robot has special sensors so they avoid colliding with one another, and they feature Wi-Fi so they can be summoned at any time by workers.
This kind of technology has the potential to improve the productivity and efficiency of every warehouse while reducing the risk of human error – like a parcel being sent to the wrong address. Machine learning algorithms and the apps running them, made by mobile app development companies, are capable of forecasting demand.
It’s proving to be effective at taking into account factors that existing methods have no way of tracking over time. It means that a warehouse would also be better equipped to cope with particularly busy periods – like Christmas or Black Friday, for example.
Should it continue to develop and grow, it’s likely that machine learning will be utilized more. Machine learning and artificial intelligence have the potential to deliver additional value to customers.
By combining machine learning with advanced analytics, developing apps and IoT sensors, for the first time, it’s conceivable that there could be a whole warehouse operated by robots only.
It’s become an essential element in future supply chain platforms and is likely to revolutionize the way warehouses operate once the technology is adopted on a wider scale.