Cisco and Rockwell Unite IT and OT for Advancements in Industrial AI

Key Takeaways

Cisco and Rockwell Automation have introduced a Full-Stack Software-Defined Manufacturing architecture to connect factory data with enterprise systems.
The architecture creates secure pathways for operational data to enhance AI and analytics use in manufacturing.
Edge computing and network reliability are crucial for advancing autonomous operations with real-time data processing.

Connecting Factory Data with Advanced Computing

Cisco and Rockwell Automation are addressing the gap between operational technology (OT) and enterprise IT with their Full-Stack Software-Defined Manufacturing architecture. This integrated system combines Cisco’s software-defined networking with Rockwell’s software-defined automation, facilitating the movement of industrial data from plant floors to computing environments optimized for analytics and artificial intelligence (AI).

The architecture tackles a significant hurdle in the industrial sector: accessing and utilizing isolated industrial data for analytics and AI applications. By creating secure data pathways between plant-floor equipment and cloud-based or edge computing resources, it allows manufacturers to capitalize on the vast amounts of data generated by machinery, sensors, and production systems.

Despite the potential, obtaining accurate and contextualized data from plant floors remains a challenge for many manufacturers. The architecture aims to combine operational data with engineering and enterprise information effectively, improving machine learning and AI capabilities.

The U.S. National Institute of Standards and Technology (NIST) has identified ongoing issues related to industrial data management and integration as barriers to AI deployment in manufacturing. By connecting OT data sources directly with telecommunication networks, Cisco and Rockwell enable a flow of real-time data, which is essential for machine learning and other advanced applications.

The architecture also supports various computing environments—on-premises, hybrid, and public cloud—and emphasizes the importance of low latency and network reliability for increasingly autonomous operations. This combination allows time-sensitive workloads to remain near production equipment while transferring data required for analytics to centralized systems.

Use cases for this advancement include predictive maintenance and digital twin applications. For instance, Rockwell’s GuardianAI leverages equipment data to detect deviations from normal operating baselines, contributing to preemptive maintenance efforts. The architecture also encompasses digital twins, which facilitate the simulation and virtual commissioning of automated systems.

Further enhancing its capabilities, Rockwell has integrated its Plex Quality Management System with FactoryTalk Analytics VisionAI, linking AI-driven visual inspection to quality management processes. This seamless connection supports better traceability and inspection history within manufacturing operations.

However, merging industrial systems with advanced AI frameworks presents several integration challenges. Many legacy systems lack modern communication protocols, complicating compatibility and data exchange with newer technologies.

Security remains a critical concern as interconnectivity expands the potential attack surface, particularly for older equipment that cannot be easily upgraded. To address these issues, the architecture incorporates Cisco Industrial Threat Defense, offering security controls that cover various network aspects and comply with established standards such as ISA/IEC 62443 and NIST security frameworks.

The Full-Stack Software-Defined Manufacturing reference design was formally introduced in India in July, featuring a demonstration environment at Rockwell’s facility in Gurugram. This initiative includes a training program focusing on networking, cybersecurity, and digital skills to prepare employees for working with software-defined industrial environments.

In conclusion, Cisco and Rockwell’s groundbreaking architecture aims to bridge the gap between operational and enterprise systems, unlocking the full potential of industrial data for AI and advanced analytics. This innovative approach not only enhances manufacturing efficiencies but also underscores the significance of securing industry interfaces as data connectivity increases.

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