Robotics and automation will make an incremental contribution towards the rapid industrial revolution and bring the current Indian manufacturing practices at par with global standards.
GreyOrange is a multinational technology company that designs, manufactures and deploys advanced robotics systems for automation at warehouses, distribution and fulfilment centers. The company is helping customers leap forward by simplifying business processes and enhancing productivity to unprecedented levels.
GreyOrange witnessed an early success with e-commerce and logistics industries. They have been early adopters of robotic automation in their warehouses. The company’s marquee solutions Butler (a goods-to person robotics solution, powered by Artificial Intelligence, for inventory management and order fulfillment.) and Sorter (advanced software and robotic sortation system for order profiling, routing and consolidation in fulfilment and distribution centers) are catering to customers across industries and geographies to increase efficiency multifold and improve last mile delivery.
Today, GreyOrange’s marquee solutions Butler and Sorter are being deployed at e-commerce, omnichannel retail, CPG (Consumer Packaged Goods) and logistics industries to help them increase efficiency multi-fold and improve last mile delivery and break bulk cargo process. There are immense opportunities for industrial automation in India, given that the current level of automation remains limited as compared to that of other markets like USA and China. Apart from the sectors mentioned above, there will be immense demand for robotic automation in sectors such as automobile and healthcare/pharmaceuticals in the coming years.
HOW GREYORANGE HAS USED AI TO AUTOMATE INVENTORY MANAGEMENT
Artificial intelligence enabled robots are designed to demonstrate human like decision-making capabilities. These robots are able to react to various expected/ unexpected situations. The reaction also improves with time and experience with capabilities to learn from their usage patterns.
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Denne historien er fra October 2017-utgaven av DataQuest.
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