Model-Based Design The Future of Automation Begins in the Model

Related Vendors

Mathworks Deutschland

FAULHABER Drive Systems

Wuxi InfiMotion Technology Co., Ltd.

Complex machine architectures and increasingly sophisticated control software must come together as a flawless overall system for automation. System models allow plants to be simulated and tested, simplifying the development effort.

Industrial automation pursues a clear goal: to increase throughput and quality, enhance the efficiency of production lines, and standardize processes. However, this progress comes at a cost, as every productivity boost requires considerable development effort. Increasing system integration presents challenges for engineering teams, as mechanics, electronics, and software are so closely intertwined that traditional sequential development approaches reach their limits.

Those who want to achieve efficiency in production must first realize it in development. By using tools like Simulink to create a system model of the plant and control system, engineers can simulate and validate their behavior.

Model-Based Design Creates the Foundation

Such a model-based approach provides a significant added value: control algorithms can be developed and tested within the virtual system, thereby improving software quality and process performance. At the same time, engineers can evaluate the placement of actuators, sensors, and other components, as well as the hardware sizing, long before physical machines are available. The simulation of the system and control prevents integration issues that would otherwise only become apparent in the field. It also allows for testing unusual or faulty operating conditions.

Another advantage is the seamless integration of automated development and testing processes. The model can be directly incorporated into CI/CD workflows (Continuous Integration/Continuous Delivery), resulting in repeatable and reliable software releases. Additionally, production code for PLCs or edge controllers can be automatically generated from the tested system model. Model-Based Design thus delivers immediately deployable control software. Engineers can then use hardware-in-the-loop testing environments, where the previously validated model runs on real-time computers and is connected to the controls of the actual system. This allows various scenarios to be tested before physical implementation occurs. The final commissioning is thus significantly faster, more cost-effective, and less risky.

Furthermore, Model-Based Design helps mechanical engineering companies meet the increasing demands for flexibility and customization in manufacturing. The more sophisticated the machine and its software functions, the greater the potential return on investment. Modular machines, in particular, which need to be adapted to various customer requirements, benefit from model-based development. Different specifications can be tested and optimized directly within the model, reducing development times by up to 50 percent.

Machine Control Becomes A Platform for Optimization

Model-Based Design transforms traditional machine control into a versatile platform where additional analysis and optimization approaches can be interconnected. The initially developed system models serve as a reusable foundation.

Model-Based Design enables the use of anomaly detection and predictive maintenance, identifying potential faults far beyond physical commissioning. With tools like Matlab, engineers can simulate scenarios, generate synthetic data, and validate algorithms. This makes the planning of maintenance strategies more precise and resource-efficient. At the same time, these models can be used to train and test AI-based applications for visual inspections. The models can also provide a realistic environment for deep learning systems. Their robustness can be tested in the simulation before real systems are integrated into inspection processes.

Furthermore, the developed models form the basis for digital twins and virtual commissioning. They accurately mirror the real system and allow for the development and simulation of new operating conditions in a safe environment. This creates an early validation platform and enables complex analyses and optimizations to be performed without disrupting production operations.

Proactive Engineering Instead of Reactive Adjustments

Those who gain their insights only on the real machine today are reacting too late. Model-Based Design transforms the development process from reactive revisions to proactive, data- and model-driven engineering. Furthermore, Model-Based Design creates a flexible, reusable development foundation. Once created, models can be used for digital twins, AI-driven quality inspections, or predictive maintenance. Automatically generated code ensures a reliable and hardware-independent transition from simulation to production. The same model basis can be applied to different control systems without developers having to start from scratch.

The true value of Model-Based Design lies in its strategic impact: companies can adapt production processes more quickly and better meet the increasing demands for customization. Simulation and modeling enable experiments and design variations without endangering real production. With this approach, development times can be halved, integration risks minimized, and production quality continuously improved. At the same time, engineers gain a robust foundation to meet future demands for automation and digitalization.

*Rareş Curatu is Industry Manager for Industrial Automation and Machinery at Mathworks

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