Description
Ranger GTP Decision-driven science robotic
Goods-to-Person System
In today’s age of immediacy, the buyer is at the wheel. Meeting their rising expectations for choice and speed is the real world challenge facing fulfillment. At GreyOrange we recognize speed-to-fulfill is at the heart of accelerating overall ‘click-to door’ time and the satisfaction it delivers—a challenge that can’t be met with fixed infrastructure and rigid automation built for a previous era with the Ranger GTP.
Features
- Improves speed & accuracy – faster, error-free order fulfillment, decreases order-to-pick time, increases number of orders picked per person.
- Lowers operating costs – reduces order fulfillment time, increases inventory efficiency, decreases days-on-hand stock.
- Empowers workforce – improves job satisfaction by reducing operational inefficiencies, errors and training time.
- Reduces complexity – simplifies warehouse processes and seamlessly adapts to customer business workflows and inventory types.
From fixed, rigid and slow to
Mobile, smart and fast
Ranger™ GTP is an advanced autonomous mobile robot that uses robotic goods-to-person technology for automated put-away, inventory storage, replenishment and order picking in fulfillment and distribution centers.
Developed in concert with GreyMatter™ AI software and purpose-engineered for speed and versatility, Ranger GTP continuously data-shares with GreyMatter while working in collaborative performance with other robots and the human workforce.
The Ranger GTP automation system adapts seamlessly to changing inventory profiles, demand patterns and peaks.
Modular system architecture ensures bi-directional scalability to increase storage volume or fulfillment throughput independently, by adding more storage racks or robots, as needed.
From reducing travel time by 5x that of human workers, to reconfiguring mobile stock units (MSUs), and working in tandem with other GTPs and Ranger Pick, the result is fluid, dynamic optimization.
Click here to learn more!
Comments are closed here.