中文The Automate 2026 exhibition delivered a clear message to the packaging industry: physical AI — the integration of artificial intelligence with physical systems that enables machines to autonomously sense, reason, and act in the real world — is no longer a laboratory concept but a production-floor reality. Across the show floor, robot manufacturers, vision system providers, and software companies demonstrated how AI-assisted robotics are bringing the flexibility that packaging lines need to handle increasingly complex and variable production demands.
The energy at the four-day event was palpable, and the implications for packaging operations are significant. Several exhibitors showcased partnerships with Nvidia, the AI computing company whose technology is providing the brains for a new generation of packaging machinery. From Lumafield to Cognex to Fanuc, Nvidia’s presence underscored the industry’s conviction that AI will be embedded not in isolated applications but throughout the production ecosystem.
According to Nvidia’s Amit Goel, Director of Autonomous Machine Product Management, the company sees significant opportunity in packaging because the industry’s need for flexibility aligns perfectly with what AI-enabled machines can deliver. “Now you have the tools to handle packaging complexity,” Goel explained, referring to the combination of edge computing, AI models, and robotic hardware that makes adaptive packaging lines possible.
A persistent question around AI-assisted machinery is power consumption. Data centers supporting AI workloads consume enormous amounts of electricity, and packaging professionals are understandably concerned about whether AI-enabled equipment will drive up their energy costs. Goel addressed this directly, noting that most physical AI applications use edge computers that deliver higher performance at the same power draw. Much of the data-intensive training happens in the cloud before models are deployed to edge devices, meaning the on-machine power footprint remains manageable.
Digital twin simulation emerged as a recurring theme across multiple booths. While simulation in packaging is not new — departments have used it for decades — AI has dramatically increased the speed and capability of simulation tools. The ability to test production scenarios, evaluate changeover strategies, and optimize line configurations in a virtual environment before committing to physical changes reduces risk and accelerates commissioning.
On the hardware front, Fanuc introduced three products with direct packaging applications. The M-710 ID robot now features a curved-arm design that allows it to reach several millimeters closer to products — a seemingly small improvement that matters significantly in facilities where floor space is at a premium. The curved-arm version also delivers a 10 percent speed improvement over the straight-arm model. Fanuc also introduced a redesigned SCARA robot with a lower profile, achieved by connecting the second arm below the first rather than above. This configuration enables the robot to operate in height-restricted areas, with particular relevance for pharmaceutical packaging lines.
The third Fanuc introduction, the CRX-30ia collaborative robot for mixed-case palletizing, reflects the broader trend toward standardized cobot solutions that are low-cost, compact, and fast to deploy. The robot features integrated status indicators that eliminate the need for separate tower lights, and the entire Fanuc cobot range was programmed to perform a synchronized dance at the booth — a demonstration that was equal parts marketing and engineering showmanship.
Perhaps the most innovative packaging application came from ABB, which demonstrated an AI-driven mixed-case palletizing system using Jacobi software. The system eliminates the need for expensive upstream sorting equipment by using AI to stage boxes on tiered shelving in real time, creating stable, balanced mixed pallet loads with fill rates between 70 and 90 percent. The system processes approximately 500 cases per hour in a footprint of roughly 20 by 20 feet and, according to ABB, costs significantly less than conventional automated mixed-load palletizers.
Voice-to-text robot training was another technology that generated buzz, though it remains in its early stages. Standard Bots CEO Evan Beard demonstrated how conversational interfaces can simplify robot programming, though the current implementation focuses on converting speech to text rather than enabling true conversational robot control. Still, the direction is promising for packaging operations where operator training time is a constraint.
The MūL MARC mobile autonomous robotic cart offered a low-tech counterpoint to the AI-heavy offerings. Requiring no Wi-Fi or IT setup, the cart can be programmed by walking it through a path once and can transport packaging supplies to production lines, carrying 100 to 200 pounds depending on the model. Its simplicity is a reminder that not every automation challenge requires an AI solution.
For packaging professionals, the Automate 2026 takeaways are clear: physical AI is real, it is arriving on production floors now, and it is being delivered through practical, deployable products rather than abstract concepts. The question for packaging operations is no longer whether to adopt AI-assisted robotics but how quickly and in which applications.
The implications of these robotic advances extend beyond the factory floor. For packaging operations, the ability to automate mixed-case palletizing — historically one of the most labor-intensive and injury-prone tasks in distribution — could transform warehouse economics. ABB’s claim that its AI-driven system costs significantly less than conventional automated mixed-load palletizers is particularly significant because cost has been the primary barrier to automation adoption in mid-size operations. If the price point is genuinely accessible, the technology could diffuse rapidly through the packaging distribution chain.
The show also highlighted the growing maturity of collaborative robotics in packaging. Fanuc’s CRX-30ia, with its integrated status indicators, extended warranty, and standardized palletizing solution, represents the kind of productized cobot application that makes automation accessible to operations without dedicated robotics engineering teams. The fact that Standard Bots reported zero service revenue year-to-date — and extended its warranty from one to three years on that basis — suggests that collaborative robot reliability has reached a level where vendors can confidently stand behind their products. For packaging operations that have been hesitant to adopt robotics due to concerns about maintenance and support, these developments should provide reassurance. As physical AI continues to mature and edge computing becomes more powerful, the gap between what packaging operations are doing today and what they could be doing with AI-assisted robotics will only widen, making early adoption increasingly important for maintaining competitive parity.
Source: Packaging Digest
