Robotics & Automation News

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GreyOrange launches Butler PickPal for auto-fulfilment in logistics centres

Robotics and supply chain automation company GreyOrange announced its beta launch of the new-gen Butler PickPal, an autonomous picking solution, at LogiMat 2018 in Stuttgart, Germany.

The Butler PickPal is powered by Artificial Intelligence (AI) and Machine Vision. It works with the goods-to-person GreyOrange Butler™ robotics system which enables warehouses to manage high-speed operations by automating order picking and fulfilment.

It addresses the challenges arising from the global boom in e-commerce as orders need to be fulfilled faster and accurately with more cost-efficiency as competition intensifies.

Vertical and horizontal e-commerce industries that operate with a huge number of high-mix SKU inventory, require the shortest order-to-dispatch time and accurate piece-picking.

Akash Gupta, Chief Technology Officer, GreyOrange, said, “The order picking process for e-commerce products take up a high percentage of the resources of warehouse staff. As companies face increasing challenges in hiring employees, the adoption of automation is the answer to increase productivity, reduce costs and improve the turnaround time.”

The PickPal reduces remarkably the time taken during order fulfilment, by identifying and picking products from shelves quickly and accurately, says the company.

The PickPal is a collaborative robot, which works alongside a warehouse operator to pick, consolidate and fulfill orders, and together can achieve 500-600 picks per hour; doubling the throughput from the same picking station.

The combination of a scanning system and a 6-axis robotic arm delivers a solution that cuts down the time required for processing and picking orders. The PickPal uses Machine Vision algorithms to identify the SKU to be picked from the shelves. Using AI-based order processing, it can manage up to 48 orders at the same time.

It can handle different packaging types such as boxes, pouches, bottles and vacuum-sealed packages. It can grasp items up to 4kg (8.8 pounds). Using Machine Learning it devises the strategy to pick each item from the densely packed SKU inventory using a versatile gripper.

It can identify and handle over 100,000 SKUs of the most popular products commonly found in its e-commerce operations.