Karin Rathsman, ESS

Causal learning challenge at ESS

ESS is a research facility under construct and commission in Lund. When finished in 2027 researchers from all over the world are welcome to bring their specimens to ESS for neutron scattering experiments. Since ESS is dedicated for external users, the demand on availability is a challenge. This talk will brief how machine learning applied to the ESS integrated control system could address operational challenges in general. In particular we will present a dataset with control system data from a cryogenics system at ESS, which is accessible through the WARA-OPS portal and intended for causal learning studies.

Mikael Lindberg, Saab-Kockums

IT-Operations aspects of submarine and surface ship design

The marine platforms of today are complex system-of-systems constructs with significant interactions between components, both local and remote. Operations while at sea must be carried out by crew, sometimes in very adverse conditions. This talk attempts to present some of the specific challenges this introduces in the designs and how we attempt to employ machine learning and AI to overcome them.

Thomas Olsson, Bosch

Modern software engineering with LLMs

At the R&D Center in Lund, we develop software for the next generation mobility solutions. We work in international teams with a DevOps setup, having a highly automated and integrated toolchain for developing, testing, and deploying software. Our developers spend a lot of time analyzing log files, from various sources such as compilers, servers, test simulations and live products in the field. Analyzing log files is a time consuming and far from trivial task, that and can block the progress of development and deployment.

The Lund DevOps teams want to improve the tools around log file analysis by using LLM and Machine Learning. As Bosch is a truly international company with teams across the world, any changes to the toolchain typically requires a lot of education and planning, usually project-specific. In this prototype project, we therefore aim to integrate a log analyzer service as an unobtrusive advisor through a convenient chat interface. We have a large amount of log files for different systems, programming languages, etc.

Despite initial positive results, we are not yet sure how applicable our initial protype is to a wider context. We are now extending our initial work to further research how we can improve performance, compatibility, sensitive to drift, etc. .

Per Runeson, Lund University

Growing a data sharing community

Talk abstract will be added shortly.

Daniel Landström, Ericsson

Collecting live data from a 5G network

Talk abstract will be added shortly. 

Vincent Hardion & Mirjam Lindberg, MAX IV

Towards the Excellence Operation of MAX IV Laboratory Control System

The MAX IV Laboratory, a leading-edge 4th generation synchrotron radiation facility located in Lund, Sweden, has been at the forefront of scientific research since its first operation in 2016. The facility can be described as a super microscope that reveals details about nature’s smallest building blocks. More than 2,000 visiting researchers annually conduct their experiments at MAX IV across its multiple beamlines and experimental stations

As the facility transitions from initial operations to a phase focused on operational excellence, the experiment control systems, crucial interfaces for user interactions, faces increasing complexities. Not only it has to accommodate the uniqueness of diverse experiments but also enhance reliability and performance to minimize operational interruption and maximize research quality. This presentation explores the evolution of MAX IV's operational strategies, particularly the integration of data-driven methodologies within the control systems

Fanny Söderlund, Ola Angelsmark, Advenica

Hidden in plain sight - Intrusion detection in systems logs

Advenica is a Swedish cybersecurity firm quietly safeguarding critical infrastructure, government agencies, and business enterprises alike. Given our role in network segmentation, we often find ourselves at the border between networks of differing levels of sensitivity, putting us in a great position to watch for suspicious activities. In this presentation we will look at how system logs can show evidence of intrusion attempts, hacker reconnaissance, and data exfiltration.

Konstantin Malysh, Lund University

Inter-organizational Data Sharing Processes - an exploratory analysis of incentives and challenges

Talk abstract will be added shortly.

If you're interested in getting involved, or just have questions about WARA-Ops, please get in touch!

WARA-Ops Co-Manager: Paul Townend
WARA-Ops Co-Manager: Johan Eker

Karin Rathsman, ESS

Causal learning challenge at ESS

ESS is a research facility under construct and commission in Lund. When finished in 2027 researchers from all over the world are welcome to bring their specimens to ESS for neutron scattering experiments. Since ESS is dedicated for external users, the demand on availability is a challenge. This talk will brief how machine learning applied to the ESS integrated control system could address operational challenges in general. In particular we will present a dataset with control system data from a cryogenics system at ESS, which is accessible through the WARA-OPS portal and intended for causal learning studies.

Mikael Lindberg, Saab-Kockums

IT-Operations aspects of submarine and surface ship design

The marine platforms of today are complex system-of-systems constructs with significant interactions between components, both local and remote. Operations while at sea must be carried out by crew, sometimes in very adverse conditions. This talk attempts to present some of the specific challenges this introduces in the designs and how we attempt to employ machine learning and AI to overcome them.

Thomas Olsson, Bosch

Modern software engineering with LLMs

At the R&D Center in Lund, we develop software for the next generation mobility solutions. We work in international teams with a DevOps setup, having a highly automated and integrated toolchain for developing, testing, and deploying software. Our developers spend a lot of time analyzing log files, from various sources such as compilers, servers, test simulations and live products in the field. Analyzing log files is a time consuming and far from trivial task, that and can block the progress of development and deployment.

The Lund DevOps teams want to improve the tools around log file analysis by using LLM and Machine Learning. As Bosch is a truly international company with teams across the world, any changes to the toolchain typically requires a lot of education and planning, usually project-specific. In this prototype project, we therefore aim to integrate a log analyzer service as an unobtrusive advisor through a convenient chat interface. We have a large amount of log files for different systems, programming languages, etc.

Despite initial positive results, we are not yet sure how applicable our initial protype is to a wider context. We are now extending our initial work to further research how we can improve performance, compatibility, sensitive to drift, etc. .

Per Runeson, Lund University

Growing a data sharing community

Talk abstract will be added shortly.

Daniel Landström, Ericsson

Collecting live data from a 5G network

Talk abstract will be added shortly. 

Vincent Hardion & Mirjam Lindberg, MAX IV

Towards the Excellence Operation of MAX IV Laboratory Control System

The MAX IV Laboratory, a leading-edge 4th generation synchrotron radiation facility located in Lund, Sweden, has been at the forefront of scientific research since its first operation in 2016. The facility can be described as a super microscope that reveals details about nature’s smallest building blocks. More than 2,000 visiting researchers annually conduct their experiments at MAX IV across its multiple beamlines and experimental stations

As the facility transitions from initial operations to a phase focused on operational excellence, the experiment control systems, crucial interfaces for user interactions, faces increasing complexities. Not only it has to accommodate the uniqueness of diverse experiments but also enhance reliability and performance to minimize operational interruption and maximize research quality. This presentation explores the evolution of MAX IV's operational strategies, particularly the integration of data-driven methodologies within the control systems

Fanny Söderlund, Ola Angelsmark, Advenica

Hidden in plain sight - Intrusion detection in systems logs

Advenica is a Swedish cybersecurity firm quietly safeguarding critical infrastructure, government agencies, and business enterprises alike. Given our role in network segmentation, we often find ourselves at the border between networks of differing levels of sensitivity, putting us in a great position to watch for suspicious activities. In this presentation we will look at how system logs can show evidence of intrusion attempts, hacker reconnaissance, and data exfiltration.

Konstantin Malysh, Lund University

Inter-organizational Data Sharing Processes - an exploratory analysis of incentives and challenges

Talk abstract will be added shortly.

If you're interested in getting involved, or just have questions about WARA-Ops, please get in touch!

WARA-Ops Co-Manager: Paul Townend
WARA-Ops Co-Manager: Johan Eker