4 Ways to Unlock the True Potential of Warehouse Automation
In January, I predicted 2020 would kick off the decade of orchestration as the next logical step toward greater operational efficiency in the supply chain. Little did we know all that 2020 would bring in accelerating the push for interoperability and communication amongst warehouse resources.
Now, just months later, there can be no doubt that this decade will be marked by players in the materials handling industry taking a broader look at their existing and future investments. They will quickly discover that Artificial Intelligence (AI) is the key to unleashing automation’s full power for improved productivity and operational throughput, maximizing productivity in an unpredictable age.
Moving forward, all eyes will be on answering unseasonal and relentless demand with greater operational efficiency gains. Automation solutions, like robots, will help increase support and drive this productivity. In fact, ABI Research estimates four million robots are expected to be added to warehouse environments by 2025. These robotic solutions, such as Autonomous Mobile Robots (AMRs), are incredibly skilled at simplifying repetitive and dangerous tasks. Whether it be transporting items cross-dock, moving non-conveyables throughout a large warehouse, or picking and moving inbound and outbound shipments, robots are proven to improve workflows and increase efficiency.
However, automation alone is not the answer to all material handling challenges. Instead, effective orchestration of these assets will be the real factor that may mean success or failure for humans and robots.
To highlight this point, I recently had a conversation with a shipping operations manager who shared an all-too-familiar story. The manager told me about a jam on a loading dock, which they solved by adding more workers. However, that same solution had the opposite effect the next day when a late shipment left those workers standing in the loading dock waiting an hour for it to arrive. That one delay decreased productivity across the plant where those workers could have been better utilized. And this isn’t isolated an incident, the average U.S. warehouse wastes 6.9 weeks a year on unnecessary motion – costing the industry 4.3 billion, or 265 million hours of labor annually, according to data from the U.S. Census Bureau.
This anecdote illustrates that warehouses and distribution centers are continually changing ecosystems, with bottlenecks causing a ripple effect of delays across whole facilities and the downstream chain. While warehouse managers and logistical professionals are great at problem-solving, they often don’t have access to the data that will help them anticipate and even predict the future factors that will impact their operational efficiencies.
AI, however, does and can. Here are four ways AI-powered orchestration engines can help improve productivity and efficiency in warehouse settings moving forward:
Cross-platform orchestration: With a system-wide view, orchestration considers the unique strengths of all agents like workers, manual handling equipment, AMRs, and other systems to optimize processes. Successful orchestration marries the problem-solving, abstract reasoning, and creative capabilities that humans possess along with the precision and real-time data collection that is unique to robotic solutions. Also, orchestration considers all automated solutions within the environment from multiple makers. Through strategic coordination across platforms, form factors, and capabilities, orchestration understands who is available to work, what tasks need to be completed, and how to assign each job to ensure work continues most efficiently. This unleashes the full power of automation and helps companies reap the competitive benefits from their technology and human capital investments.
Synchronous simulation: Much like the driving and navigation app Waze can propose a new route to the driver, AI can propose a new workflow to operations managers. These platforms can constantly run simulations, given real-time data, to find more efficient ways to complete missions given all available resources.
Predictive analytics: Orchestration engines integrate with legacy automation, piece-picking robots, WMS, and MES systems to provide a system-wide view of operations. With this level of insight, the AI engine can use predictive analytics to get ahead of bottlenecks in real-time.
Continuous improvement: AI-powered orchestration engines can collect, analyze, and deliver insights based on data to ensure continuous improvement for robots and task allocation over time. This helps ensure robotic investments continue to learn specific warehouse settings' nuances and deliver enhanced results, rather than stay static from the first deployment date.
While much of this may seem futuristic now, it will be commonplace, and necessary, by 2030. More than providing the opportunity for massive efficiency gains, orchestration enables organizations within the supply chain to be robust and flexible to vulnerabilities, especially in a rapidly changing world.
About Daniel Theobald
Bio: Daniel Theobald is the CEO and Founder of Vecna Robotics, the autonomous mobile robot and workflow orchestration company. Daniel has decades of experience leading research scientists and teams of engineers in developing cutting edge technology. He has 67 issued patents and more than 30 patents pending. Daniel has also been on the forefront of robotics for more than 20 years, working closely with DARPA, DOD, NASA, NIH, USDA and many others to advance the use of robots and AI software to improve warehouse automation. In addition to founding Vecna Robotics, Daniel also co-founded Mass Robotics, a non-profit dedicated to the global advancement of the robotics industry. Daniel is dedicated to the idea that technology can be used to empower people worldwide to live more fulfilling lives.