Leveraging SysML2 and AI: A Next-Generation MBSE Methodology

About this project 

The evolving complexity of modern engineering projects calls for more sophisticated tools and methodologies to manage system design, analysis, and optimization. SysML2, the latest version of the Systems Modelling Language, offers significant advancements in system representation, consistency, and flexibility, enabling more effective modelling and decision-making across diverse engineering domains. This project aims to harness the power of SysML2 combined with Artificial Intelligence (AI), particularly generative AI, to develop a cutting-edge methodology for improving system design and decision-making in complex projects. The integration of AI into SysML2 enables automation, enhanced analysis and can assist in interpreting system requirements, generating model alternatives, and conducting sophisticated design trade-offs, improving overall system performance. By automating key aspects of system modelling and design evaluation, AI can reduce the time and resources typically required for these tasks, freeing engineers to focus on higher-level strategic decisions.
The central goal of this project is to develop a next-generation model-based systems engineering methodology that leverages the strengths of SysML2 and AI to streamline key engineering processes, such as;
automated requirement analysis; design optimization, and enhanced decision-making: With AI integrated into the SysML2 framework, engineers will have access to real-time decision support, allowing them to explore multiple design options and make data-driven decisions quickly and effectively.
The project will involve the development and prototyping of an AI-assisted MBSE methodology using SysML2, enabling engineers to: 1) generate high-quality system models more efficiently, 2) conduct advanced design analyses with minimal manual intervention, and 3) optimize and validate system designs based on key performance indicators, cost constraints, and operational goals.
This project aligns with UNISA’s strategic interest in defence research. Internal to the UNISA, this project fits within Industrial AI research centre themes and interests. At the national level the project will be well received and perceived with high regard in the defence circles as the problem to be addressed by this research is of crucial importance to teams, groups and organisations within and around department of defence as well as department of transportation. It will also enable growth of UNISA’s systems engineering capacity by building expertise, creating knowledge and tools crucial for staying competitive at the national and international global levels. The outputs align well with Defence's Digital Engineering Strategy (2024), the SA Defence Industry Workforce and Skills Report (2023), the Sovereign Defence Industrial Priorities as outlined in the Defence Industry Development Strategy (2024) and similar international strategies to develop Digital Engineering capabilities.

What you’ll do
 
The outcome of this project ideally includes an MBSE methodology as an explicit set of steps and guidelines on using SysMl2 artifacts in the systems engineering process. The process must be smooth, in a way that each artefact or set of artefacts creates the required information and basic objects used in the next stage of the process. This may include software solutions that automate system model generation, design optimization, and decision-making within a SysML2 framework. Other outcomes of the project include

• Research Publications: Several research papers at top quality journals that explore the integration of AI in systems engineering, highlighting case studies where AI-driven SysML2 models improved system performance and decision-making processes.
• Case Studies and Demonstrations: Testing and validation of the methodology through practical case studies in various industries, including aerospace, automotive, and defence sectors.

The integration of AI with SysML2 in this project will push the boundaries of systems engineering, offering powerful tools to streamline design processes, improve decision-making, and optimize system performance. The resulting methodology will enable engineers to manage complex system requirements and configurations more efficiently and foster greater innovation in system design by allowing teams to rapidly explore and compare different design scenarios.
By focusing on design optimization and decision-making rather than just automating system creation, this project will deliver impactful results that can revolutionize the way complex systems are engineered, making the process more efficient, precise, and adaptable to changing requirements.

Where you’ll be based 

Industrial AI (IAI)

Ady James has experience and a vested interest in MBSE research and practice. In particular, he is interested in easing the path to MBSE adoption in the Space Industry as a facilitator of both industrial growth and system/operation increased efficiency. Ady James has over 20 years experience in the space sector and nearly 20 years teaching and researching in complex project management and systems engineering. 
Mahmoud Efatmaneshnik is actively engaged in MBSE research and teaching. He has designed and currently delivers the first such course ever in Australia at UNISA. He has over 15 years of experience in Systems Engineering research, consulting and teaching. This ambitious project will place the systems engineering team at UNISA at the forefront of Systems Engineering research worldwide. The project will pave the way for UNISA’s team to embark on this important aspect of systems engineering research that is seen a lot of demand from defence industries, particularly from the government sector and, department of Defence.
Markus Stumptner is a global leader in AI research. Markus will bring to this project essential expertise in AI domain. Financial Support  

This project is funded for reasonable research expenses. Additionally, a living allowance scholarship of $35,200 per annum is available to Australian and New Zealand citizens, and permanent residents of Australia, including permanent humanitarian visa holders. Australian Aboriginal and/or Torres Strait Islander applicants will be eligible to receive an increased stipend rate of $52,352 per annum (2025 rate). A fee-offset or waiver for the standard term of the program is also included. For full terms and benefits of the scholarship please refer to our scholarship information. International applicants are not invited to apply at this time.

Eligibility and Selection 

This project is open to applications from Australian or New Zealand citizens, and Australian permanent residents or permanent humanitarian visa holders. International applicants are not invited to apply at this time.
Applicants must meet the eligibility criteria for entrance into a PhD. 
All applications that meet the eligibility and selection criteria will be considered for this project. A merit selection process will be used to determine the successful candidate.
The successful applicant is expected to study full-time, and to be based at our Mawson Lakes Campus in the north of Adelaide. 

Essential Dates 

Applicants are expected to start in a timely fashion upon receipt of an offer. Extended deferral periods are not available. Applications close on 30 April 2025.