For decades, the conveyor belt was the backbone of production logistics. It was reliable, predictable, and completely inflexible – which, for most of the 20th century, worked well. But traditional systems built on manual handling and static conveyors are struggling to keep up with today’s demands for high-mix, low-volume production and rapid changeovers that have become table stakes across a wide range of manufacturing operations. To be competitive, not only today but for years to come, manufacturers are realizing they need autonomous systems that can respond to changing production needs, adapt to change in real time, and optimize performance with less manual intervention.  This article explores the technologies enabling this shift and how manufacturers can identify bottlenecks, pilot new approaches without disrupting operations, and scale across facilities.

The Building Blocks of Autonomous Material Flow

Unified control architectures

Historically, robots, conveyors, and safety systems each ran on separate controllers with separate interfaces. That fragmentation made integration expensive and slow. Unified control platforms that manage all of these assets together dramatically reduce deployment complexity and give plant engineers a single view of what's happening across the floor.

Intelligent conveyance

Independent cart technology (ICT) systems use linear motors embedded in a track to drive individual carriers independently. Each cart receives its own velocity and position commands, so one can hold at a workstation while another accelerates through an empty section. Changeovers that once required physical reconfiguration of belts and guides can now be managed through software.

Autonomous mobile robots (AMRs)

Where ICT handles movement within a defined process, AMRs extend that movement across the entire facility. Unlike their predecessors – automated guided vehicles (AGVs) that follow fixed magnetic tracks or floor tape – AMRs can navigate factory floors autonomously using onboard sensors and real-time mapping.  If an unexpected obstacle appears in its planned path, an AMR can reroute in real time and continue operating without manual intervention.

How To Get Started

Start by mapping your current material flow to understand where the bottlenecks are. Where do the materials wait? Where do handoffs between systems require manual intervention? Which segments of the flow are most sensitive to disruption?

Once you know where the flow breaks down, the next question is how to fix it without disrupting operations in the process. Digital twin technology allows you to model your entire material flow virtually before committing to physical infrastructure. This helps catch design flaws early in the process and dramatically shortens the time from concept to commissioning.

Simulation also makes it easier to justify investment. Your business case becomes far more concrete when you can show stakeholders a validated model of how a new material flow strategy performs with real throughput numbers, staffing implications, and changeover times.

From there, start small. Choose one area – a single line, a high-traffic corridor, or a particularly painful manual handoff – and run a focused pilot. Once the pilot validates your approach, you can replicate the model across additional cells, lines, or facilities.

Conclusion

For too long, material movement has been treated as a background function. But advanced motion and robotics are changing that by giving manufacturers the tools to treat material flow as a strategic and competitive lever that they can tune, optimize, and adapt. The manufacturers who embrace these technologies will be better positioned to absorb disruption, respond to change, and keep production moving when conditions shift.

Ryan Gariepy is the Vice President, Robotics for Rockwell Automation and leader of Rockwell’s Robotics Center of Excellence. He was one of the founders of Clearpath Robotics in 2009 and OTTO Motors in 2015, and was instrumental in Rockwell Automation’s acquisition of the companies in 2023. Ryan is a board member of the Open Source Robotics Foundation, co-founder of ROSCon, and co-founder and co-chair of the Canadian Robotics Council. Ryan is also a senior member of the IEEE, holds over 100 granted and pending patents in the field of autonomous systems, and is a leading angel investor in robotics companies worldwide. In 2023, he was honored with the Lifetime Achievement Award by the Canadian Image Processing and Pattern Recognition Society. Ryan holds a B.A.Sc. in Mechatronics Engineering and a M.A.Sc. in Mechanical Engineering from the University of Waterloo.