In packaging, innovation means more than solving technical challenges—it means enabling machines that are easier to commission, more flexible in format changes, and able to adapt to production variability. To achieve this, IMA rethought how machines are designed and controlled, moving beyond traditional logic-based automation
Adaptive and smart machine control
Industrial AI for adaptive packaging
IMA Group, a global leader in packaging machinery, is working with Siemens to bring Industrial AI into machine control— enabling more adaptive, flexible, and future-ready packaging systems.
Expanding the boundaries of machine control
From digital simulation to AI-driven control
Digital twin and synthetic data
Production scenarios are simulated in a digital twin, generating synthetic data to train control models. This approach reduces physical testing and enables faster validation before commissioning.
AI embedded in the PLC
Machine control is no longer based only on programmed instructions. A neural network runs directly within the PLC, enabling real-time motion control and adaptive behavior on the machine.
Flexibility and commissioning efficiency
By combining simulation and AI, the solution reduces commissioning effort and simplifies format changes—making machines more adaptable to different products and production conditions.
Bringing Industrial AI into automation
A new approach to machine intelligence
With Siemens, IMA is introducing a new paradigm in packaging automation: moving from deterministic, instruction-based control to systems that can learn and adapt. Industrial AI becomes part of the machine logic itself, directly influencing how it behaves in real time.
From simulation to real-world performance
Digital twin technology allows the simulation of multiple production scenarios, generating the data needed to train control models before physical deployment. This reduces testing on the real machine and enables a more advanced starting point at commissioning.
Delivering value to end customers
For end users, the impact is tangible: simpler commissioning, easier format changes, and machines that can better adapt to different production needs. This approach reduces complexity while increasing operational flexibility and long-term value.
For us, this is a first step toward the packaging of the future: machines that are not only more performant, but capable of learning, adapting, and evolving.