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Developing software intensive industrial systems: Bridging the Gap Between Industry and Academia
2025-06-13
New research challenges the way industrial systems are developed
Researchers from Mälardalen University and the University of Teramo have conducted an in-depth study on the development of cyber-physical systems (CPS) through industry-academia collaboration. This research highlights the challenges and successes of integrating advanced technologies like Model-Based Systems Engineering (MBSE), DevOps, and Artificial Intelligence (AI) into the development of complex CPS. Their findings provide valuable insights into how these collaborations can drive innovation and improve the development processes of CPS, which are essential for modern industries.
Understanding the Breakthrough:
Cyber-physical systems (CPS) are integrated systems that combine computational algorithms and physical components. They are increasingly prevalent in various industries, including automotive, aerospace, and manufacturing. However, developing these systems is complex and requires collaboration between industry and academia to leverage the latest technological advancements and research insights.
The team, led by Johan Cederbladh, Romina Eramo, Vittoriano Muttillo, and Per Erik Strandberg, has explored the integration of MBSE, DevOps, and AI in CPS development. Their research focuses on how these technologies can address the challenges of developing complex CPS, such as data management, modelling, requirements engineering, continuous software and system engineering, and automation.
The study emphasizes the need for continuous collaboration between industry and academia to drive innovation and address the evolving challenges of CPS development. By sharing knowledge and resources, these collaborations can lead to more effective and efficient development practices, ultimately benefiting both industry and society.
"By combining the strengths of industry and academia, we can tackle the complexities of CPS development more effectively," says Johan Cederbladh. "Our research provides insights for successful collaboration and highlights the benefits of integrating advanced technologies into the development process."
How It Works:
The researchers have identified five key challenge areas in CPS development: data management, modelling, requirements engineering, continuous software and system engineering, and intelligence and automation. They have proposed solutions for each of these areas, leveraging the strengths of MBSE, DevOps, and AI.
- Data Management: Efficiently handling the vast amounts of data generated by CPS is crucial. The researchers propose using advanced data processing technologies such as stream processing and real-time analytics to manage and analyse this data effectively.
- Modelling: MBSE emphasises the use of models as the primary artifacts in the development process. The researchers highlight the importance of verifying and validating these models to ensure they accurately represent the system and its behaviour.
- Requirements Engineering: The variability in CPS design requires robust requirements engineering practices. The researchers recommend using model-based requirements engineering (MBRE) to manage the complexity and to ensure that the system meets its intended specifications.
- Continuous Software and System Engineering: Applying DevOps principles to CPS development can improve the efficiency and effectiveness of the development process. The researchers emphasise the need for suitable testing and simulation techniques to support continuous integration and delivery.
- Intelligence and Automation: Integrating AI and automation into CPS can enhance efficiency and decision-making. The researchers propose using AI to assist in design, testing, and optimisation processes, as well as to improve the overall reliability and security of CPS.
Contributions to the UN Sustainable Development Goals (SDGs):
Goal 9: Industry, Innovation and Infrastructure
This research helps build robust and flexible industrial networks. In manufacturing or logistics, SoS principles enable autonomous subsystems to respond to disruptions in real time—improving efficiency and resilience.
Goal 11: Sustainable Cities and Communities
Reliable and efficient CPS are vital for smart city technologies. This work helps improve urban safety, resource efficiency, and quality of life.
Bottom line:
Knowledge gained from this research provides important insights to the field of CPS development, paving the way for more effective and collaborative efforts.
This work on industry-academia collaboration comes from insights in the AIDOaRt research project, which was a European project hosted by MDU.