A New Approach to
Automating Order Fulfillment

When investing resources and time into selecting and implementing an order fulfillment automation solution, it's important to understand and evaluate which autonomous mobile robot (AMR) system approach aligns to your organization's KPIs, supports your workforce, and enables your operations to meet service level agreements (SLAs) and keep up with demand.

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In fulfillment warehouses, talent is scarce and resources are tight, yet customer expectations remain high. As supply chain leaders look to do more with less, automating traditionally manual processes has shifted from a “nice-to-have” to a “must-have,” safeguarding warehouses from ongoing labor challenges and variations in customer demand. The order picking process is widely reported as one of the most costly and resource-heavy processes within a fulfillment warehouse. 

Current mobile robotic solutions on the market offer various methods to coordinate and connect human and robotic workforces for order picking, however gaps remain in implementing and executing technology that reduces warehouse manager and worker effort as well as click-to-customer turnaround time.

Why Order Picking Automation

Ongoing labor challenges and unpredictable swings in demand have warehouse and DC managers looking for flexible, easy-to-implement and use automated solutions. In Instawork’s annual state of the warehouse report, 64% of respondents said they had to forgo business worth more than 25% of their revenue in 2022 because of staffing issues1.

Instawork Stat

Warehouse jobs boomed with e-commerce growth during the pandemic, but now leaders are shifting investment to automate processes to reduce costs and increase productivity. With temporary or flexible workers in the warehouse on the rise, and layoffs of full-time workers across the industry, relying solely on manual labor to keep up with in an on-demand market is no longer a sustainable or dependable strategy.

As supply chain leaders search for opportunities to increase margins and grow revenue, identifying operational processes to automate that will boost productivity while reducing cost will have the most impact. What activities are most critical in meeting customer expectations and budget? In Peerless Research Group’s 2023 Automation Study, picking efficiency (lines picked per hour) was reported as the top area for improvement in warehouse and DC operations over the next 2 years2. In end-to-end fulfillment processes from induction to packout, accuracy and speed are key to successfully meet SLAs.

Introducing robotics can optimize the picking process, significantly reducing worker travel and errors while providing the agility to adapt when swings in demand occur.

Order picking is widely reported to account for 50% to 55% of total warehouse operational costs and remains a partial manual process to fulfill customer orders as mobile manipulation robotic technology continues to evolve. Therefore, when automating order picking, it is not simply automating manual tasks and determining the proper picking method, but orchestrating and optimizing how human workers and Autonomous Mobile Robots (AMRs) work together. How workflow is assigned, orchestrated and communicated across resources is critical to increasing uptime and pick rates. This is where various AMR system vendors used in warehouses and distribution centers (DCs) begin to differ.

Connecting and Coordinating Resources

With humans and robots working together, task assignment, labor balancing and communication is key to executing efficient and seamless workflows. Legacy person-to-goods AMR warehouse systems have traditionally offered two models of worker/robot workflow orchestration: “follow me” and “find me.” 

Follow Me

Follow MeThe “follow me” model of some AMR solutions requires the human to follow the robot in order to complete picks, directed by the user interface on the tablet mounted on the robot for pick location and instructions. The worker is assigned to one robot and their picking speed is limited by the speed of that robot. Picking speed is also sometimes affected by the mounted tablet: if pickers forget what they need to pick or how many, they have to walk around to the side of the robot to confirm the pick.

Find Me

Find MeIn the “find me” or swarm model, many robots roam a zoned area; workers are required to find and select a robot that has work available, typically indicated by a flashing light or color on the tablet attached to the robot. In both models, human workers are dependent on robots to initiate and complete picks, and operations managers must ensure proper people zoning and management to prevent downtime and maximize resources. Maintaining and increasing productivity can be a challenge if work isn’t continually monitored and allocated properly across zones and robots.

Meet Me™️

yd7610 Meet Me Solutionyd7610 recently announced a new Meet Me™ model driven by Pyxis™ technology that orchestrates humans and robots separately in their own directed workflows. In this unique model, humans are empowered with the picking information they need using the Pyxis™ Point mobile app so they can move independently, meeting their robotic counterparts at the pick location. Since workers don’t need to rely on robots for directions, or pick information, downtime spent waiting on or finding a robot is eliminated.

Warehouse managers also save time without the need to plan or coordinate human and robot resources. Pyxis™ technology directed task assignment and labor balancing is catered to each customer’s operational needs–prioritizing and planning resources based on distance, priority of orders, and robot dwell time for continuous and fast fulfillment. This innovative approach doesn’t require a swarm of robots or additional worker travel finding or following robots to maintain productivity, since both individual workflows are optimized.

Working Better Together

Orchestration of resources optimizes workflows, however successful implementation, adoption and ongoing usage of robotic automation also relies on optimal human and robot interaction. Workers filling these roles continue to change, with 69% of businesses leveraging temporary and flexible workers year round in their operations–up from 57% in 20213. Considering increased turnover and temporary labor, onboarding and training needs to be simple, repeatable and quick. Making the repetitive work of order picking easy and engaging increases employee satisfaction, minimizes physical strain, and boosts productivity.

Faster Cycle Times with Visual Task Allocation

Legacy person-to-goods AMR system offerings rely on a combination of a tablet user interface mounted to the robot and lights on the robot to direct the worker to the proper location, SKU and quantity for picking. In both “find me” and “follow me” systems, users need to properly locate their robot counterpart and once picking, determine the proper tote, shelf, and associated quantity for each line item utilizing the user interface and select robot lighting. With the Meet Me™ solution, workers meet their robot at the location specified on their mobile device, and are guided through the pick visually using the Pyxis Point™ user interface and put-to-light shelving to ensure accurate and simple order picking each time. Workers are informed and enabled, resulting in faster cycle times.

More Capacity, Improved Ergonomics

With over 5% of warehouse workers impacted by work-related injuries and over 2% of cases resulting in days away from work4, improving ergonomics with robotic automation can keep workers on the job, happier, and more productive.

Capacity

Manual order picking typically involves workers pushing often heavy carts to complete an order. Current AMR systems offer various robotic platforms that can be configured to accommodate different payload dimensions and weight, however most used in fulfillment have limitations. yd7610 Lumabot™ is capable of handling payloads of up to 500 lb. (226 kg) with configurable shelving that is wide enough to accommodate larger individual SKUs, taking on the physical labor of moving orders throughout the warehouse.

Grab Efficiency

Both the “follow me” and “find me” methods utilize a fixed tablet adhered to the robot to communicate the SKU location and quantity to the picker. yd7610’ Pyxis Point mobile application improves pick efficiency and reduces wasted movement for the worker by providing the information they need as they are picking. They can view the total quantity needed and distribute throughout the assigned totes using patent-pending put-to-light shelving which indicates the proper tote and quantity per tote. Workers are armed with the information they need to pick safely, quickly, and accurately.

Powered Productivity

Robots don’t take breaks, but just like their human team members, they need energy to perform. Continuous fulfillment relies on robots being fully charged to keep moving product throughout the warehouse. Both “find me” and “follow me” AMR systems utilize power recharging stations taking robots off the floor to power up. The Meet Me solution’s Lumabot AMRs use a lithium ion battery that lasts up to two shifts without a charge and can be hot swapped during operations, reducing downtime and keeping fulfillment moving.

Automated Fulfillment is More Accessible Than Ever

yd7610 Meet Me SolutionWhen investing resources and time into selecting and implementing the right robotics solution for the specific needs of a business, it is important to understand and evaluate which AMR system approach aligns to your KPIs, supports your workforce, and enables your operations to keep up with demand and meet service level agreements (SLAs).

yd7610 unique Meet Me™ person-to-goods solution revolutionizes fulfillment: reimagining how humans and robots work together by creating a more collaborative, efficient and flexible fulfillment team that dramatically increases operational efficiency and eliminates downtime in warehousing, distribution, and fulfillment centers.

Learn more about Pyxis™ proprietary technology can transform your fulfillment center directly from one of our experts: contact our sales team today!

SOURCES:

  1. 2023 State of Warehouse Labor Report, Instawork and Logistics Management January 2023
  2. 2023 Automation Study: Usage & Implementation of Warehouse/DC Automation Solutions, Modern Materials Handling March 2023
  3. 2023 State of Warehouse Labor Report, Instawork and Logistics Management January 2023
  4. U.S. Bureau of Labor Statistics 2022

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