Labor productivity is critical to DCs that are struggling to hire and retain workers amid tight labor markets and growing ecommerce orders. Companies that can’t hire enough workers to fill all of their open positions are turning to autonomous mobile robots, or AMRs. As a result, AMRs are the leading trend in warehouse automation and technology. But many distribution executives are uncertain about the ROI of autonomous mobile robots.
A previous Lucas blog introduced the five principal types of AMRs, including goods-to-person and robot-to-goods picking systems. These picking AMRs minimize travel and maximize throughput and labor productivity. This article summarizes the key advantages of AMRs over traditional automation. We then breakdown the costs and potential return on investment (ROI) of autonomous mobile robots in a hypothetical DC.
Our analysis shows that many DCs will not be able to justify the up front investment costs for picking AMRs, even when doubling productivity. For those facilities, lower-cost approaches to reducing travel can deliver a bigger, faster ROI. For example, Lucas’ AI-based software – Dynamic Work Optimization – can reduce DC travel 30-70% and double productivity at a fraction of the cost of robots. (Learn more about DWO and other leading travel reduction strategies for the DC in our new whitepaper.)
AMRs offer a number of advantages over traditional fixed automation systems, including increased flexibility, scalability, and lower cost.
AMR’s have free reign to travel throughout a facility, so they can often be deployed in existing facilities without changing racking or the DC layout. If your layout changes after deploying robots, the robots can adapt without moving any fixed infrastructure. Likewise, with conveyance robots you can define new drop off or induction points through software changes and the robots will adapt.
Traditional automation systems are sized to handle maximum throughput which may only be reached for a few weeks per year. By contrast, robotic solutions can be scaled up or down by adding or subtracting robots and/or pick-pack stations.
AMRs cost significantly less than conventional automation systems. But at roughly $30,000/robot, they are by no means a low-cost solution. Goods-to-man or robot-to-goods AMRs typically require three or more robots per picker. That makes an initial investment of greater than $1,000,000 for a relatively small operation with 10 pickers.
The ROI of Autonomous Mobile Robots
The table below summarizes AMR costs for a goods-to-person or robot-to-goods picking solution with 10 workers. We are assuming a ratio of 3 or 4 robots per human picker. That is the robot:worker ratio suggested by robotics companies to achieve maximum productivity and throughput. Based on published reports, the cost per AMR is approximately $30,000, plus 20 percent annual maintenance. (Note that these cost and ROI figures do not include implementation costs for WMS integration, development, on-site testing and deployment, and training.)
For purposes of our ROI calculations, we compared the costs for installing AMRs to the labor costs saved by using robots. We estimated average annual labor costs per worker of $35,000 (roughly $17.50/hour including benefits). We used these costs to estimate the time to achieve a 100% return on investment (ROI Horizon, in the chart) in DCs achieving 2X and 3X greater productivity with robots than without.
Our ROI calculations for 2X productivity (a 100% increase in pick rates/hour compared to picking without robots) assumes the same level of production with 20 full time pickers and no robots compared to 10 workers with robots. In that scenario it would take more than five years for a DC to earn a 100 percent ROI.
The 3X productivity figures (a 200% increase) are based on 30 full time pickers with no robots compared to 10 workers with robots. In this case, a DC that triples productivity would see a total return on its investment in 1.5-3 years, depending on the number of robots per picker.
These figures assume there are no other costs associated with deploying AMRs, including new staff to maintain the new equipment.
Compared to the uncertain ROI of autonomous mobile robots, Lucas Systems has taken a different approach to reducing travel and boosting productivity. Our approach builds on lean process engineering and applies math-based optimization technology. Read more about our approach – and other popular technology solutions to reduce travel – in our new whitepaper, Double DC Productivity By Reducing Travel.