ENG 7020 - Complex Systems Engineering PG

North Terrace Campus - Semester 2 - 2023

Most interesting engineering interventions occur in complicated and complex systems. These systems display emergent behaviour that cannot always be foreseen or forecast. This course will build upon fundamental systems engineering knowledge, exploring the theory of complex systems and introducing structured systems engineering methodologies to help understand and manage systems design and evolution in this environment. Topics may include system of systems engineering, decision theory, optimisation for design, queueing theory, network design and advanced model-based systems engineering.

  • General Course Information
    Course Details
    Course Code ENG 7020
    Course Complex Systems Engineering PG
    Coordinating Unit Centre for STEM Education and Innovation
    Term Semester 2
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact Up to 4 hrs per week
    Available for Study Abroad and Exchange
    Prerequisites MECH ENG 7056
    Incompatible ENG 4020
    Course Staff

    Course Coordinator: Dr David Harvey

    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    On successful completion of this course students will be able to:
    1. Classify a system of interest and use this information to identify appropriate systems engineering approaches, processes, methods, tools, and techniques
    2. Tailor a system engineering approach to suit a system of interest
    3. Apply the systems engineering tools and analysis methods presented in the course to systems design problems
    4. Construct models of the system of interest that can support systems engineering design and analysis processes
    5. Demonstrate professional skills including effective team participation, oral communication, and written communication
    The above course learning outcomes are aligned with the Engineers Australia Stage 1 Competency Standard for the Professional Engineer. The course is designed to develop the following Elements of Competency: 1.5, 2.1, 2.2, 2.3, 2.4, 3.2, 3.3, 3.4, 3.6.
    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)

    Attribute 1: Deep discipline knowledge and intellectual breadth

    Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.


    Attribute 2: Creative and critical thinking, and problem solving

    Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.

    3 and 4

    Attribute 3: Teamwork and communication skills

    Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.

    3 and 5

    Attribute 4: Professionalism and leadership readiness

    Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.

    3 and 5

    Attribute 5: Intercultural and ethical competency

    Graduates are responsible and effective global citizens whose personal values and practices are consistent with their roles as responsible members of society.


    Attribute 6: Australian Aboriginal and Torres Strait Islander cultural competency

    Graduates have an understanding of, and respect for, Australian Aboriginal and Torres Strait Islander values, culture and knowledge.

    No specific outcomes

    Attribute 7: Digital capabilities

    Graduates are well prepared for living, learning and working in a digital society.

    1, 3 and 4

    Attribute 8: Self-awareness and emotional intelligence

    Graduates are self-aware and reflective; they are flexible and resilient and have the capacity to accept and give constructive feedback; they act with integrity and take responsibility for their actions.

    3 and 5
  • Learning & Teaching Activities
    Learning & Teaching Modes
    This course consists of a mixture of online video theory and practice focused content, active participation workshops, advanced modelling computer exercises and industry guest speakers.

    The course is structured around different types of assessments:
    • Engagement and active participation assessments for the video content and workshops
    • Structured computer exercises that guide students through advanced systems modelling
    • Individual written assessments and case studies to explore student understanding of content in more depth
    • A group systems design and modelling project, starting with an unstructured problem and working through to the high-level definition of a solution, using model supported design

    This is a hands-on, participation focused course and students will need to plan their schedule around attendance at the in-person or remote sessions depending on their circumstances.

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    It is expected that students spend:
    • Up to nine hours per week on lectures, online material and assignments over the course of the semester
    • Three hours per week attending the active workshops and computer exercise sessions
    Learning Activities Summary
    The course works to connect underpinning theory with methodology, processes and practices, while introducing advanced methods, tools and techniques. It covers the following topics:
    • Systems Engineering background
    • Introduction to Model Based Systems Engineering
    • Design Using Systems Thinking
    • Introduction to SysML
    • Generic Architectural Design Approach
    • Design Process and Representing the System of Interest
    • System Problem Definition
    • Requirements Engineering
    • Understanding System Behaviour
    • Representing System Behaviour
    • Synthesising Candidate Solutions
    • Representing Structure
    • Measurement
    • Representing Measures
    • Systems Engineering in Context
    • Systems Engineering Analysis
    • Analysis in SysML
    • Tailoring
    • The Future of Model Based Systems Engineering
    • Dealing with Complexity
    • The Future of Systems Engineering
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment Task Weighting (%) Individual/Group Due (week)* Learning Outcomes
    On-line quizzes associated with each lecture module 10 Individual Throughout the course 1, 2, 3
    Active learning assessments during workshops 10 Individual Throughout the course 1, 2, 3, 4, 5
    Computer exercises x 5 20 Individual Weeks 3-7 3, 4
    Case study written assessments x 2 20 Individual Week 4, Week 9 1, 2
    Group project design model 30 Group Week 12 3, 4
    Group project design report 10 Group Week 12 3, 4, 5
    Total 100%

    * The specific due date for each assessment task will be available on MyUni.

    This assessment breakdown is being registered as an exemption to the University's Assessment for Coursework Programs Policy. The exemption is related to the Procedures clause(s): 1. a. i
    Assessment Detail
    On-line quizzes associated with each lecture module (Weighting 10%): Quizzes to see what students understand from the video content released throughout the semester.
    Active learning assessments during workshops (Weighting 10%): Assessments measuring student engagement and participation in workshops throughout the semester.
    Computer exercises (Weighting 20%): Students will be guided through aspects of systems design modelling during computer exercise sessions, then will need to complete and submit a model fragment as evidence of their understanding of the content.
    Case study written assessments (Weighting 20%): Written assessments addressing short answer questions and case study exercises that explore aspects of the course content.
    Group project design model (Weighting 30%): Students will complete a group design project in the second half of semester. One output of this design work is a systems design model (in a SysML tool).
    Group project design report (Weighting 10%): Students will complete a group design project in the second half of semester. One output of this design work is a short document that explains the design process and guides the reviewer through the associated model.
    Work will be submitted mostly through MyUni through quiz and assignment submission options. Other work will be demonstrated through active participation within workshop sessions.
    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through Access Adelaide.

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

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