AUTONOMOUS MOBILE ROBOT SYSTEMS

ORDER FULFILMENT

With the recent spike in ecommerce and consumer expectations for shorter delivery times continuing to grow, companies are looking for automation for fulfilling those demands.

Sorion’s Autonomous Mobile Robot system for order fulfilment fits well with this challenge, by increasing operator productivity and accuracy, while lowering labour costs and operator training time.

CAPABILITIES

The Sorion system is based on MiR autonomous mobile robots, built for maximum agility, performance and safety.

Each robot is fitted with specially engineered attachments to fit your operation.

Sorion’s Fleetware fleet management software ensures optimal resource allocation and process throughput.

APPLICATIONS

  • Directed picking
  • Transport goods from A to B
  • Replenishment

Improved productivity

Fast, accurate picking

Flexibility

Configurable to suit your application

Scalability

Easy to add robots as required

SYSTEM INTEGRATION

Integration with existing warehouse software is a very important part of implementing AMRs for order fulfilment.

Sorion’s Fleetware AMR fleet management software acts as a middleware for SAP / ERP / MRP/WMS to receive and supply order data. It also allows connection to OPC, SQL, barcode scanners file imports and web services.

Fleetware mobile robot service status

INTELLIGENT ROBOT ASSIGNMENT

Fleetware collates orders, defines the route and assigns the most suitable robot for each job.

This ensures optimal AMR movement in the environment, resource allocation, and process throughput.

IMPROVE ACCURACY WITH DIRECTED PICKING

Intuitive task prompts on the ProGlove display guide workers through the entire pick process.

This allows for an easier and faster picking process: operators spend more time picking and less time walking.

ROBOT FLEET MONITORING & ANALYTICS

EMA for Fleetware is a web interface that tracks status events from the robot fleet:

  • Waiting and charge times
  • Stoppage time classification
  • Overview of fleet utilisation and performance with failure and cause statistics

This can be used to trace bottlenecks and problematic robots/positions.

Fleetware robot fleet status

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