Project Goal
The project aims to enhance the efficiency and intelligence of the industrial control systems utilized by the CERN’s accelerator complex. One of the main goals is to create a device monitoring platform, incorporating a web application prototype that uses edge computing technologies and real-time analytics to monitor control devices. Another goal is to test and deploy advanced control algorithms on an industrial edge device, aiming to boost the energy efficiency of control processes. As part of this initiative, Siemens’ solutions will be assessed and fine-tuned to meet the particular requirements of the end-users at CERN.
Background
The planned HL-LHC upgrade is set to increase the particle collision data sample by tenfold relative to the existing LHC program. The associated control systems will grow in complexity with these enhancements. As a result, enhancing the current systems’ functionality and sustainability becomes critical. This task encompasses several interconnected initiatives. One key subproject is devoted to developing a device monitoring platform that will oversee the hardware components of the industrial control system, employing edge computing technologies and real-time analytics. Additionally, another critical subproject aims to test and deploy sophisticated control algorithms on an industrial edge device to augment and optimize the control devices within the plant.
Progress
In 2023, several key milestones were achieved within the project. A working prototype of the web application was co-created with members from CERN and Siemens. The frontend component of the application enables end-users to configure and categorize control devices into a hierarchical tree-like structure and design rules for the individual categories or tree nodes. These rules are executed in real time, serving a crucial function: they hierarchically display the status of the entire control system. This real-time display facilitates easy navigation and efficient identification of errors within the system. A backend component of the application, based on finite state machines, was developed for rule execution. The application was designed to support third-party integrations, including compatibility with software for device monitoring developed by Siemens. Moreover, several Siemens monitoring software programs such as SINEC NMS, Machine Insight, and SIMATIC Automation Tool were evaluated for potential integrations using a test bench set up in the control systems laboratory at CERN.
In another subproject, we utilized industrial edge computing technology to operate an advanced control algorithm based on Model Predictive Control. This setup allows the algorithm to run directly on the edge computing device within a containerized environment, simplifying the algorithm development process and reducing the need for extensive control system components. This setup significantly lowers latency and decreases the load on the control system, consequently enhancing overall system efficiency.
Next Steps
The device monitoring project is set to continue in the upcoming years. Nonetheless, specific subprojects may transition to different focus areas based on the priorities established in collaboration with the company. These new areas include the application of large language models in the development of control software or the implementation of predictive maintenance for devices using historical data. A joint workshop between CERN and Siemens has been scheduled to outline specific use cases for the forthcoming year and the objectives for the eighth phase of CERN openlab.
Project Coordinator: Fernando Varela Rodriguez
Technical Team: Jan Andrzej Bugajski, Abhit Patil, Fernando Varela Rodriguez, Jeronimo Ortola Vidal
Siemens AG Collaboration Liaisons: Thomas Kaufmann, Christian Kern, Daniel Schall, Axel Sundermann
In partnership with: Siemens
