• Class Number 2085
  • Term Code 3530
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
  • COURSE CONVENER
    • Prof Robert Mahony
  • LECTURER
    • Prof Robert Mahony
  • Class Dates
  • Class Start Date 17/02/2025
  • Class End Date 23/05/2025
  • Census Date 31/03/2025
  • Last Date to Enrol 24/02/2025
  • TUTOR
    • Arara Kar
    • Arlene Mendoza
    • Iman Hosseini
    • Jacinta Ryan
    • Mosaab Hamed
    • Rhys Kissell
SELT Survey Results

This course provides an introduction to systems engineering fundamentals, establishing a robust framework for designing complex engineered systems in response to customer needs and expectations. The emphasis of the course is on the core activities of systems engineering, which are requirements analysis; functional analysis and allocation; and design synthesis, test and evaluation. Together, these activities and concerns form what is called the systems engineering process, which provides a comprehensive, life-cycle balanced approach to the design of complex systems that satisfy customer expectations and public acceptability. The course covers lifecycle concerns such as reliability, maintainability and human factors.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Identify different types of systems through key behaviours and functionality.
  2. Identify and analyse the various phases in a system's life-cycle, and demonstrate an understanding of the importance of considering a system's life-cycle early in the design effort.
  3. Perform stakeholder identification and requirements analysis.
  4. Identify, analyse, and objectively resolve design trade-offs for different types of requirements and constraints.
  5. Understand the key role of test and evaluation and distinguish different types of test and evaluation activities.
  6. Understand the importance of lifecycle non-functional requirements such as reliability, maintainability, human factor as well as systems engineering management in the design process.
  7. Apply systems engineering fundamentals to a real-world project as part of a design team.

Examination Material or equipment

There is no exam for this course.

Required Resources

Blanchard, Benjamin S; Fabrycky, Wolter J. Systems Engineering and Analysis: Pearson New International Edition. Pearson Education Limited. 2014.

INCOSE Systems Engineering Handbook

Staff Feedback

Students will be given feedback in the following forms in this course:

  • written comments
  • verbal comments
  • feedback to groups
  • individual feedback

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Other Information

Face-to-face activities

  1. Lectures, held once a week for two hours.
  2. Guest Lectures, held in some weeks in the second half of the two-hour lecture slot.
  3. Workshops, held once a week in large groups. Times and locations are as per wattle. Workshops are two hours long.


Use of Generative AI Tools

The use of Generative AI Tools (e.g., ChatGPT) is permitted for assessment in this course. AI generated material must be properly cited at the point it is included. The tool used and prompts used to generate the material, along with a description of how the tool contributed to the assignment, must be provided in appendices attached to assignment submitted. Guidelines regarding appropriate citation and use can be found on the ANU library website (https://libguides.anu.edu.au/generative-ai). Marks will reflect the contribution of the students rather than the contribution of the tools. Further guidance on appropriate use should be directed to the convenor for this course.

The use of Generative AI Tools is NOT permitted for in-class assessments (quizzes, exams and during presentations, or interviews).

Class Schedule

Week/Session Summary of Activities Assessment
1 Lecture: Systems, System Life Cycle and Systems EngineeringTutorial: Life-cycle engineering Quiz 1
2 Lecture: Requirements Tutorial: Customer needs/Standards Quiz 2A1 Assignment 1 released
3 Lecture: RequirementsTutorial: RequirementsGroup assignment initiation Quiz 3Group design project released
4 Lecture: No lecture - public holidayTutorial: Project review
5 Lecture: Conceptual DesignTutorial: Functional Analysis Quiz 4A1 Assignment 1 due (20%)A2 Assignment 2 released
6 Lecture: Conceptual DesignTutorial: Design Synthesis Quiz 5
7 Lecture: Preliminary DesignTutorial: Trade-off analysis Quiz 6A2 Assignment 2 due (20%)A3 Assignment 3 released
8 Lecture: No lecture - public holidayAll classes: Concept Design Stage Gate Presentation - Project review G1 Concept Design Stage Gate Presentations (5%)
9 Lecture: OptimisationTutorial: House of Quality Quiz 7
10 Lecture: Test and validationTutorial: System Optimisation Quiz 8
11 Lecture: Intellectual Property and EthicsTutorial: Drop-in sessions (times TBA) A3 Assignment 3 due (20%)
12 Lecture: No lecture Tutorial: Drop-in sessions (times TBA)
13 G2 Group design project report due (20%)

Tutorial Registration

Please self-allocate for your chosen two hour tutorial in MyTimetable.

Assessment Summary

Assessment task Value Learning Outcomes
Assignments 60 % 1,2,3,4,5
Quizes 15 % 1,2,3,5
Group project and presentation 25 % 6,7,8

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

ANU has educational policies, procedures and guidelines , which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Integrity Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Participation

Tutorial attendance will be required to complete the quizzes.

Examination(s)

There is no exam for this course.

Assessment Task 1

Value: 60 %
Learning Outcomes: 1,2,3,4,5

Assignments

Three assignments worth 20% each. Students will work individually on the assignments.

Please see Wattle for more details.

Assessment Task 2

Value: 15 %
Learning Outcomes: 1,2,3,5

Quizes

Weekly multiple choice quizzes completed during tutorials. Best six of eight quizzes will count each worth 2.5% (total 15%). No extensions will be given on quizzes.

Please see Wattle for more details.

Assessment Task 3

Value: 25 %
Learning Outcomes: 6,7,8

Group project and presentation

Students will complete a group project with a report (worth 20%) and a presentation (worth 5%).

Please see Wattle for more details.


Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.


The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.


The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.

 

The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Hardcopy Submission

No hardcopy submissions will be accepted in this course.

Late Submission

All assessment items are to be submitted online through turnitin/wattle. Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date.

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material. Any use of artificial intelligence must be properly referenced. Failure to properly cite use of Generative AI will be considered a breach of academic integrity.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

  • ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
  • ANU Accessibility for students with a disability or ongoing or chronic illness
  • ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
  • ANU Academic Skills supports you make your own decisions about how you learn and manage your workload.
  • ANU Counselling promotes, supports and enhances mental health and wellbeing within the University student community.
  • ANUSA supports and represents all ANU students
Prof Robert Mahony
u4033888@anu.edu.au

Research Interests


Robot vision, cameras, mobile robots, Lie groups, closed loop systems, Lyapunov methods, asymptotic stability, autonomous aerial vehicles, distance measurement, filtering theory, learning (artificial intelligence), motion estimation, nonlinear control systems, pose estimation, position control, and image analysis including reconstruction, resolution, segmentation, sensors, colour analysis, and representation.

Prof Robert Mahony

Monday 09:00 11:00
Prof Robert Mahony
robert.mahony@anu.edu.au

Research Interests


Prof Robert Mahony

Monday 09:00 11:00
Arara Kar
arara.kar@anu.edu.au

Research Interests


Robot vision, cameras, mobile robots, Lie groups, closed loop systems, Lyapunov methods, asymptotic stability, autonomous aerial vehicles, distance measurement, filtering theory, learning (artificial intelligence), motion estimation, nonlinear control systems, pose estimation, position control, and image analysis including reconstruction, resolution, segmentation, sensors, colour analysis, and representation.

Arara Kar

Sunday
Arlene Mendoza
Arlene.Mendoza@anu.edu.au

Research Interests


Arlene Mendoza

Sunday 18:00
Iman Hosseini
Iman.Hosseini@anu.edu.au

Research Interests


Robot vision, cameras, mobile robots, Lie groups, closed loop systems, Lyapunov methods, asymptotic stability, autonomous aerial vehicles, distance measurement, filtering theory, learning (artificial intelligence), motion estimation, nonlinear control systems, pose estimation, position control, and image analysis including reconstruction, resolution, segmentation, sensors, colour analysis, and representation.

Iman Hosseini

Sunday 16:00
Jacinta Ryan
jacinta.ryan@anu.edu.au

Research Interests


Robot vision, cameras, mobile robots, Lie groups, closed loop systems, Lyapunov methods, asymptotic stability, autonomous aerial vehicles, distance measurement, filtering theory, learning (artificial intelligence), motion estimation, nonlinear control systems, pose estimation, position control, and image analysis including reconstruction, resolution, segmentation, sensors, colour analysis, and representation.

Jacinta Ryan

Sunday
Mosaab Hamed
mosaab.hamed@anu.edu.au

Research Interests


Robot vision, cameras, mobile robots, Lie groups, closed loop systems, Lyapunov methods, asymptotic stability, autonomous aerial vehicles, distance measurement, filtering theory, learning (artificial intelligence), motion estimation, nonlinear control systems, pose estimation, position control, and image analysis including reconstruction, resolution, segmentation, sensors, colour analysis, and representation.

Mosaab Hamed

Sunday
Rhys Kissell
rhys.kissell@anu.edu.au

Research Interests


Robot vision, cameras, mobile robots, Lie groups, closed loop systems, Lyapunov methods, asymptotic stability, autonomous aerial vehicles, distance measurement, filtering theory, learning (artificial intelligence), motion estimation, nonlinear control systems, pose estimation, position control, and image analysis including reconstruction, resolution, segmentation, sensors, colour analysis, and representation.

Rhys Kissell

Sunday

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