How Automation Intelligence Improves Order Fulfillment Efficiency

We have been fielding inquiries from interested customers regarding the impact machine learning and Automation Intelligence can have in the material handling industry, and how these concepts actually relate to real world distribution operations. This blog will give you a brief overview, but don’t hesitate to give us a call anytime to discuss these concepts in more detail. We love to talk about our technology!

Advancements in machine learning and software analytics are driving more informed decision making across all business sectors. Manufacturing and distribution control systems are no exception, with the right control system, your DC can greatly benefit from Automation Intelligence.

Studies conducted by KPMG estimate initiatives like artificial intelligence and machine learning can bring as much as $300 billion to the retail industry alone. Furthermore, market researchers at IDC suggest as much as half of all manufacturing supply chains will boost productivity 15% through intelligent automation by 2021.

As leaders in software development and automation control in warehousing and order fulfillment for over three decades, Numina Group can assist in implementing Automation Intelligence into your DC.

We explore and invest in research to develop and apply machine learning and Automation Intelligence software tools that improve performance in distribution material handling applications. Numina Group has pre-developed software modules within our RDS™ WES-WCS platform that automate decision making in conveyor control systems, order picking processes, and material handling technologies such as ASRS and autonomous mobile robots (AMR).

RDS Automation Intelligence Scanning a Package

RDS Automation Intelligence Scanning a Package

A control system that makes more intelligent decisions can improve order release and reduce travel time. Intelligent control systems enable more intelligent transport and order routing decisions within pick zones and assignment of ready to ship work to packing lanes. To accomplish this, the software needs to take into account several variables that can be measured in real-time to effect order flow and balance labor requirements in distribution operations.

Automation Intelligence or machine learning techniques are embedded prebuilt modules within Numina Group’s Real-time Distribution Software, RDS™ WES-WCS. The modules take into account numerous conditions. For example, when controlling a conveyor system in a goods to man order zone routing pick module, several variables are measured in order to make decisions, such as:

    • Total cartons and totes actively being picked in a zone
    • Releasing orders based on zone visit logic
    • Zone picking performance history/standards
    • Number of pickers within the zone
    • Available inventory slotted in each pick zone 
    • Conveyor speed, zone accumulation capacity, etc.

These are some of the variables used to balance and manage order release. In real-time, the control system can re-route an order to the best zone based on available SKU inventory to eliminate congestion and balance picking in the multi-zone conveyor pick module. RDS™ Automation Intelligence takes traditional automation and makes it smarter. It keeps bottlenecks from occurring, and keeps the order fulfillment process operating at peak design rates.

RDS™ Automation Intelligence software modules enable the warehouse automation control system to make decisions, freeing up the supervisory task of selecting and making manual order release decisions to balance work and decide when to release priority shipments.

RDS Automation Intelligence Used on Conveyor Belt

For example, RDS™ learns the order throughput capacity rate from order start throughout picking, packing, and shipping. Web screens provide the ability to set the carrier shipment pick-up times. At a set time, RDS™ will move the priority order to the front of the line and release these shipments to ensure that they are processed within the known time-window to ship based on the carrier pick-up time.

In an age of increasingly complex supply chains that require a larger percentage of same day orders shipments, having the RDS™ software tool-set constantly measuring order volume, adjusting, and automating order release based on priority, travel path, picking time while accounting for order per hour shipment rates is critical for customer service and your enterprise’s success and profitability.

RDS™ WES-WCS, and its integral RDS™ voice picking suite makes your workforce more productive by:

  • Directing picking with voice commands and hands free barcode scanning to boost productivity 25-30% while increasing primary pick accuracy rates to over 99.98%.
  • Capturing SKU lot and pick by FIFO to minimize missed expiration dates.
  • Directing workers in the most effective pick paths across parallel order fulfillment processes.

The addition of RDS™ Automation Intelligence to DC operations provides many productivity benefits, including: optimized order release and order balancing, improved picking with RDS™ pick by voice and pick to light, high speed print and apply labeling, and efficient sortation solutions.

We assist clients in defining and implementing solutions that optimize every aspect of the DC order fulfillment operation. Our clients benefit from our design team’s expertise in deploying cutting edge automation and enterprise-grade hardware sourced from leading manufacturers like Zebra’s latest Android based wearable picking automation technologies, and TGW conveyor solutions.

To see Numina Group’s automation in action, check out our video from this year’s Modex 2020 Tradeshow.

 

 

 

 

 

 

 

 

 

Find out more about the power of Automation Intelligence with Numina Group’s RDS™ by you speaking with our automation experts. Unite accurate order picking systems and durable enterprise-grade hardware, with RDS™ Automation Intelligence to build an optimized warehouse automation solution that transforms your operations from good to great.


1 Souza, Kim. The Supply Side: Artificial Intelligence is slowly shaping the future of retail. TBP. Feb 15, 2020. 

2 Berman, Jeff. IDC’s 2020 prediction for the supply chain take a deep dive into digital transformation. Modern Materials Handling. Nov 21, 2019.