Model Based Systems Engineering

An introduction to core concepts, model development, and process implementation

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Duration

2 days

Delivery mode

Hybrid

Location

UNSW Canberra City Campus

Standard price

$2,090.00

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Overview

This course is designed to provide you with a solid grasp of MBSE fundamentals and its advantages of over traditional systems engineering methods. Throughout the course, you will embark on a journey that demystifies the core concepts of MBSE. From understanding its foundational principles to diving into the processes involved, the course offers a holistic view of how MBSE is revolutionizing the engineering landscape.

You will engage in practical exercises that cover the various stages and tasks involved in contracting MBSE models, helping you to understand the nuances of building systems’ models. Furthermore, you will gain skills in interpreting and querying existing models and employing them to examine and manage systems effectively.

By the end of this course, participants will understand the MBSE lifecycle, model applications, and learn how to evaluate the quality of MBSE models, methods, and tools. They will also acquire insights into workforce requirements for MBSE, emphasizing the role of model artifacts throughout a system’s lifecycle.

Course content

This course covers the following topics:

-          Introduction to MBSE and overview of its significance to systems’ development.

-          Economic analysis of MBSE processes.

-          Basic concepts and terminology of MBSE.

-          Quality of MBSE elements.

-          Understanding model artifacts and their usages.

-          Workforce development in MBSE contexts.

-          MBSE adoption – challenges and strategies.

-          MBSE as part of the digital enterprise. 

Learning outcomes

By completing this course, you will be able to: 

  • Apply core concepts and principles of MBSE to hypothetical engineering scenarios, showcasing the advantages of model-based approaches.

  • Implement the stages of the MBSE process to a given system, illustrating the lifecycle from conceptualization to validation.

  • Construct basic models using specific tools and software.

  • Understand the main MBSE methodologies and approaches.

  • Collaborate in a team setting to coordinate and manage an MBSE project.

Who should attend

  • Systems Engineers looking to modernise their approach and stay current with the latest methodologies in their field.

  • Project managers who oversee engineering projects and want to better understand MBSE approach to ensure smoother project execution and transition from conventional SE.

  • Technical leads who aim to integrate modern systems engineering practices within their teams.

  • Organisational decision-makers who consider the adoption of MBSE for their engineering processes and wanting to comprehend its benefits and implementation. 

     

    Prerequisites

    Basic understanding of systems engineering: familiarity with traditional systems engineering concepts and practices


Facilitator

Dr Ebrahim Aly

Dr. Ebrahim Aly is currently a research associate at UNSW Canberra’s Capability Systems Centre. Dr. Aly has an MSc in modelling of complex systems from Kyushu University, Japan, and a PhD in Systems Engineering from UNSW Canberra. His research interests include improving the efficiency of complex systems’ models, integrating MBSE processes with systems models, and exploring AI’s role in MBSE. He utilizes various methodologies in his research such as causal inference, Bayesian methods, system dynamics, statistical modelling, and MBSE.

Cancellation policy

Courses will be held subject to sufficient registrations. UNSW Canberra reserves the right to cancel a course up to five working days prior to commencement of the course. If a course is cancelled, you will have the opportunity to transfer your registration or be issued a full refund. If registrant cancels within 10 days of course commencement, a 50% registration fee will apply. UNSW Canberra is a registered ACT provider under ESOS Act 2000-CRICOS provider Code 00098G.