IMA Group positions "Cognitive Manufacturing" as the next operating model for industrial production

IMA Group debuted a formal operating model it calls Cognitive Manufacturing at Interpack 2026, presenting live production demonstrations of a framework designed to move industrial lines from executing predefined tasks to actively learning and supporting operators in real time. The announcement marks a concrete product and architecture direction from one of the packaging and process equipment sector's largest builders.

The distinction IMA draws is deliberate. Conventional automation runs predetermined sequences. Cognitive Manufacturing, as IMA defines it, creates a feedback loop: data is collected and contextualized, AI extracts meaning from it, decisions are supported under human supervision, and the system updates based on outcomes. People stay in the decision seat; machines take on the interpretation work.

Three-layer architecture: cloud, edge, and robotics

IMA's technical structure for Cognitive Manufacturing is built across three distinct intelligence layers, each addressing a different operational need.

At the cloud level, IMA INTELLECTA serves as the company's proprietary AI platform. It consolidates data across machines, production lines, and plant locations, giving operations and IT teams a centralized knowledge layer that scales across sites and applications. For multi-site manufacturers managing disparate equipment fleets, that cross-plant data integration is a meaningful shift from point-solution diagnostics.

On the production floor, edge AI runs directly on machines. According to IMA, this layer delivers real-time operator guidance, diagnostics, and troubleshooting support without depending on cloud connectivity or latency. The logic is that decisions in a packaging or pharmaceutical line often need to happen in seconds, not the time it takes a round-trip to a data center.

The third layer embeds AI into robotics. Rather than treating robotic cells as isolated automation islands, IMA positions them as active participants in the cognitive system, supporting operators, improving safety, and maintaining process consistency run to run.

Operational outcomes IMA targets

• Reduced unplanned downtime through predictive diagnostics across the machine and line network
• Higher production efficiency via continuous performance feedback loops
• Improved quality consistency tied to real-time AI analysis at the point of production
• Faster and more consistent decision-making supported by data rather than operator intuition alone

These are not novel promises for industrial AI vendors. What differentiates IMA's framing is the explicit architecture backing each claim: a named cloud platform, a defined edge AI layer, and robotics that feed into the same intelligence loop rather than operating separately.

Interpack 2026 as the launch stage

IMA chose Interpack 2026, the packaging industry's flagship global trade event, to move Cognitive Manufacturing from internal roadmap to public demonstration. The company released the fifth edition of its Sensing Future technology magazine at the show, dedicated specifically to the Cognitive Manufacturing direction. A private extranet area gives registered users access to recorded live demos from the show floor.

For operations and engineering leaders evaluating capital equipment in packaging, pharma, food, or adjacent verticals, IMA's positioning reflects a broader industry trajectory: major OEMs are competing not just on machine throughput specs but on the intelligence layer they attach to their hardware. Buying a production line increasingly means buying into a data and AI platform alongside the mechanical equipment.

What this means for your team

• When issuing RFPs or reviewing OEM proposals, ask specifically how vendor AI platforms handle multi-site data aggregation and what the edge AI architecture looks like when cloud connectivity is interrupted.
• Evaluate IMA INTELLECTA's data ownership and integration terms before committing to a line upgrade, particularly if your plant runs a mixed-vendor equipment floor.
• Request documented downtime and efficiency benchmark data from Interpack 2026 demonstrations before using vendor claims in internal business cases.
• Confirm how robotics within a Cognitive Manufacturing cell connect back to the broader intelligence platform, and what operator retraining or change-management support the vendor provides.