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Industrial businesses need solutions that enable them to converge operational and information technology networks, deploy predictive maintenance, and automate processes using robots to raise throughput and eliminate human errors.
A programmable system on module (SOM) can provide a suitable compute platform to solve these challenges. However, additional firmware and software infrastructure are needed and a heterogeneous processing engine and integrated programmable logic can add valuable flexibility to do this.
Network Convergence
Converging Informational Technology (IT) with Operational Technology (OT) networks eases the information flow between systems on the factory floor and enterprise management.
While OT networks require real time, low-latency communications and are difficult to scale, IT networks are easier to scale but not deterministic. Time Sensitive Networking (TSN) facilitates convergence by enabling deterministic communications over Ethernet networks.
Correctly implementing TSN requires a solution that provides a low latency and deterministic response at network endpoints and switches. A suitable platform would comprise an Ethernet MAC, TSN bridge, TSN endpoint logic, and software handle network synchronisation, initialisation, and interfacing functions.
Predictive Maintenance
Predictive monitoring lets operators schedule maintenance for convenient times, maximising uptime and minimizing Total Cost of Ownership (TCO). Processing at the edge and communicating the processed data to the cloud is the most viable solution for many industrial applications due to the volume of data and the resulting critical response time of the decision loop. The use of prognostics at the edge can provide significant benefits.
A challenge when building such systems lies in developing machine-learning (ML) applications for edge deployment. A suitable toolkit can provide ready-to-use high-performance ML algorithms that enable developers to build applications using popular machine learning frameworks such as PyTorch, TensorFlow, and Caffe.
ROS 2-based Robotics
One of the most critical technologies for Industry 4.0 is the use of robotics to automate the production process. In manufacturing, these solutions can cover a wide range of applications from robotic arms working on a production line, to robots moving supplies and logistics around the manufacturing floor.
A high performance, low latency processing system is critical to interact with the environment safely. In particular, it is needed to control the robot’s moving parts, which comprise complex systems of actuators, drives, and mechanics, often called mechatronics. Because robots communicate internally using networks to achieve the required real-time control, a SOM that contains programmable logic brings two advantages. One is the ability to support any-to-any interfacing, which simplifies implementing connections to sensors and drives. Moreover, programmable logic can be used to implement deterministic networks, which is critical for the implementation of robot systems.
Many development projects leverage the Robot Operating System (ROS), which comprises a set of software libraries and tools for creating robot systems. While ROS has been recently updated to ROS 2, its native Continuous Integration/Continuous Delivery (CI/CD) development pipeline is designed explicitly for homogeneous CPU-based processing systems.
In addition, monitoring and automation are added to the CI/CD pipeline to improve the process of application development, particularly at the integration and testing phases and during delivery and deployment. This automation minimises the manual execution of each of the steps of a CI/CD pipeline and roboticists to use the same conventions of ROS 2 with the same tooling for parts that are implemented in software or that are offloaded or accelerated in programmable logic. There is also a mechanism to benchmark the execution of a ROS 2 node application, which helps identify bottlenecks and specifically tailor one or more kernels as offloaded kernels in programmable logic.
Conclusion
High-performance adaptive edge computing is a pillar of industrial digital transformation. Programmable SOMs can simplify the creation of flexible, adaptive computing solutions and, with purpose designed IP including software stacks, can accelerate the development of a production-ready model.
