From food packaging to metal cutting and injection molding, leading companies building production machines use MATLAB and Simulink to address the increasing complexity of their equipment.
- Building mechatronic models of their systems for desktop simulation and virtual commissioning
- Designing and verifying controls and supervisory logic algorithms
- Running hundreds of scenarios in simulation without involving prototypes or production systems
- Generating real-time code (IEC 61131-3 or C/C++) for deployment on different PLC platforms
From initial design to commissioning, machine builders benefit from MATLAB and Simulink to build equipment that is optimized for efficiency, reliability and flexibility
Virtual Commissioning
Virtual commissioning with MATLAB, Simulink, and Simscape enables early testing and verification of machine software by using a digital model of the machine. In desktop and hardware-in-the-loop simulation, the interaction between mechanical assemblies, machine software, and the product being manufactured can be tested in different scenarios before the physical machine is available. This approach lowers costs, produces high-quality products, enables reusability of projects, and speeds up commissioning times in the field.
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Predictive Maintenance
Engineers use MATLAB and Simulink to develop health monitoring and predictive maintenance software for production machines.
Interactive apps make it easy to access data over industrial protocols like OPC UA and to perform pre-processing, without the need of manual programming. Engineers can design algorithms (e.g., for remaining useful life [RUL]) and deploy them on their PLCs or edge devices. This allows optimizing service intervals and reducing maintenance costs when compared to reactive or preventive maintenance.
Customer Success
- Mondi Implements Statistics-Based Health Monitoring and Predictive Maintenance for Manufacturing Processes with Machine Learning
- Baker Hughes Develops Predictive Maintenance Software for Gas and Oil Extraction Equipment Using Data Analytics and Machine Learning
- Krones Develops Package-Handling Robot Digital Twin
PLC Code Generation
Using Model-Based Design, engineers develop machine functionality and can run hundreds of test scenarios in desktop simulation. After verification, they can generate hardware-independent IEC 61131-3 (Structured Text and Ladder Diagram) or C/C++ code from MATLAB and Simulink. The resulting software can be deployed on all major PLC platforms.
Vendor |
IDE |
IEC 61131-3 |
C/C++ |
|---|---|---|---|
| 3S - Smart Software Solutions | CODESYS™ |
|
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| B&R Industrial Automation | Automation Studio™ |
|
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| Bachmann Electronic | SolutionCenter |
|
|
| Beckhoff Automation | TwinCAT® |
|
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| Bosch Rexroth | IndraWorks |
|
|
| Mitsubishi® Electric | CW Workbench |
|
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| Ingeteam | Ingesys IC3 |
|
|
| Omron® | Sysmac® Studio |
|
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| Phoenix Contact® | PC WORX™ |
|
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| Rockwell Automation® | RSLogix™/Studio 5000 |
|
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| Siemens® | TIA Portal/STEP® 7 |
|
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Customer Success
- Metso Develops Controller for Energy-Saving Digital Hydraulic
- Festo Develops Innovative Robotic Arm Using Model-Based Design
- Vintecc Develops PLC System for Multi-Axle Harvesting Machine Using Model-Based Design
- ENGEL Speeds Development of Injection Molding Machine Controllers
- AVL Develops Dynamic Controller for Engine Conditioning System Using Embedded Code Generation for PLCs
- Metso Develops Controller for Energy-Saving Digital Hydraulic System for Papermaking Equipment Using Model-Based Design
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Automated Inspection
MATLAB and Simulink provide a framework for automated inspection in manufacturing. Engineers use functionality for machine learning, deep learning, image processing, and computer vision to develop algorithms that detect and localize various types of abnormalities. The verified algorithms are then deployed through:
- IEC 61131-3 Structured Text and Ladder Diagrams for PLCs and PACs
- C and C++ code optimized for embedded systems
- VHDL® and Verilog® code for FPGAs and ASICs
- CUDA® code for NVIDIA® GPUs
Using MATLAB and Simulink for Industrial Machines
“Using Model-Based Design with MATLAB and Simulink, we achieved multiple goals simultaneously. We developed a sophisticated controller for digital hydraulics that is more reliable, accurate, and efficient than previous systems, and we accelerated development, which gives us a competitive advantage.”
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