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Unit outline_

AMME5902: Manufacturing of Micro- and Nanosystems

Semester 2, 2023 [Normal day] - Camperdown/Darlington, Sydney

The aim of this course is to enhance the student's manufacturing engineering skills in the CAD/CAM area. The course focuses on CNC milling as a manufacturing automation process applied to a project. The management, planning and marketing of a typical engineering project are also discussed. Through integrated project-based learning and hands-on-machine training, you will learn: How to successfully complete a CAD/CAM and CNC mill based project; Manufacturing management and system skills, such as product planning, manufacturing sequence, time and cost; The science in designing and selecting a manufacturing method; How to effectively present your ideas and outcomes using video and report based methods. It is expected that through your hard work in the semester, you will find: Enhanced learning by real-world problems; Improved comprehensive skill in manufacturing design.

Unit details and rules

Academic unit Aerospace, Mechanical and Mechatronic
Credit points 6
Prerequisites
? 
(MECH2400 or MECH9400) and (MECH3660 or MECH8660 or MECH9660)
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Niels Quack, niels.quack@sydney.edu.au
Demonstrator(s) Thai Nguyen, thai.nguyen@sydney.edu.au
Justin Wootton, justin.wootton@sydney.edu.au
Lecturer(s) Paul Briozzo, paul.briozzo@sydney.edu.au
Freddy Caro Diaz, freddy.carodiaz@sydney.edu.au
Type Description Weight Due Length
Assignment group assignment Systems Engineering Report
Systems Engineering Report
30% Please select a valid week from the list below
Due date: 03 Nov 2023 at 23:59

Closing date: 26 Nov 2023
Max 30 pages
Outcomes assessed: LO2 LO3 LO4 LO5 LO6 LO8 LO9 LO10
Assignment Assignment 1 - CNC code generation
CNC Code Submission
15% Week 05
Due date: 01 Sep 2023 at 23:59

Closing date: 22 Sep 2023
Max 5 pages
Outcomes assessed: LO1 LO2 LO3
Skills-based evaluation Lab 1 - CNC Mill Laboratory
CNC Mill Laboratory
5% Week 08
Due date: 22 Sep 2023 at 23:59

Closing date: 13 Oct 2023
Tour and 1.5 hour online Quiz
Outcomes assessed: LO7 LO4 LO3
Assignment Assignment 2 - Fixture Design / Forces
Fixture Design / Forces
15% Week 08
Due date: 22 Sep 2023 at 23:59

Closing date: 20 Oct 2023
Max 10 pages
Outcomes assessed: LO1 LO3 LO4
Skills-based evaluation Lab 2 - Rapid Engineering Laboratory
Rapid Engineering Laboratory
5% Week 11
Due date: 20 Oct 2023 at 23:59

Closing date: 10 Nov 2023
Max 10 pages
Outcomes assessed: LO3 LO2 LO1 LO4
Assignment Assignment 3 - Kinematics of Rapid Engineering
Kinematics of Rapid Engineering
15% Week 11
Due date: 20 Oct 2023 at 23:59

Closing date: 10 Nov 2023
Max 10 pages
Outcomes assessed: LO3 LO4 LO7 LO11
Skills-based evaluation Lab 3 - Robot Assembly Laboratory
Robot Assembly Laboratory
5% Week 12
Due date: 27 Oct 2023 at 23:59

Closing date: 17 Nov 2023
Max 10 pages
Outcomes assessed: LO4 LO9
Presentation group assignment System Engineering Presentation
Video on Systems Engineering Project in prerecorded MP4 format
10% Week 13
Due date: 03 Nov 2023 at 23:59

Closing date: 26 Nov 2023
5 to 6 minute video
Outcomes assessed: LO2 LO3 LO4 LO5 LO6 LO8 LO9 LO10
group assignment = group assignment ?

Assessment summary

Assignment 1: CNC code generation. CNC code to be submitted as a .nc file.

Assignment 2: Fixture Design / Forces. Fixture and force analysis assignment to be submitted as a report with calculations.

Assignment 3: Kinematics of Rapid Engineering. Kinematics of Rapid Engineering analysis assignemnt to be submitted as a report with calculations.

Systems Engineering Presentation: A group presentation of 5 to 6 minutes in duration. The format required is in a pre-recorded video (.mp4 format) which focuses on the Systems Engineering task.

Systems Engineering Report: A final report which includes the many themes covered in the Unit of Study and is focused on the manufacturing of an assembly from a Systems Engineering approach.

CNC Mill Laboratory: CNC Mill Demonstration Laboratory that enables students to interact with CNC maching scenarios. Online Quiz Assessment.

Rapid Engineering Laboratory: A report submission that enables students to undertake a Rapid Engineering task using 3D Printers at the laboratories of the University. 

Robot Assembly Laboratory: A report submission that enables students to undertake a Robot Assembly task using the experimental robot setup at laboratories of the University.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

 

Distinction

75 - 84

 

Credit

65 - 74

 

Pass

50 - 64

 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Late penalties are in accordance with University Guidelines.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Ongoing Non-contact independent work doing research, homework, and working on assignments, group meetings, and prior readings across multiple weeks. Independent study (90 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Week 01 Introduction to unit of study and CAD Lecture (2 hr) LO1 LO2
Week 02 CAD SolidWorks refresher or CNC machining Tutorial (2 hr) LO1 LO2
Writing CNC machine code Lecture (2 hr) LO1 LO2
Week 03 Writing CNC machine code Tutorial (2 hr) LO1 LO2
CNC machining and CIMCO Lecture (2 hr) LO1 LO2
Week 04 CNC machining and CIMCO Tutorial (2 hr) LO1 LO2
3D Printing, machining fixtures, jigs and forces Lecture (2 hr) LO3 LO7
Week 05 3D Printing, machining fixtures, jigs and forces Tutorial (2 hr) LO3 LO7
Construction and kinematics of CNC machines Lecture (2 hr) LO4
Week 06 Construction and kinematics of CNC machines Tutorial (2 hr) LO4
CAMWorks 2.5 axis machining Lecture (2 hr) LO8
Week 07 CAMWorks 2.5 axis machining Tutorial (2 hr) LO8
3D Scanning Lecture (2 hr) LO6
Week 08 CAMWorks 3 axis machining Lecture (2 hr) LO2 LO4 LO8
Week 09 CAMWorks 3 axis machining Tutorial (2 hr) LO2 LO4 LO8
Robot arm programming Lecture (2 hr) LO9
Week 10 Robot arm programming Tutorial (2 hr) LO9
CAMWorks post processors Lecture (2 hr) LO8 LO10
Week 11 CAMWorks post processors Tutorial (2 hr) LO8 LO10
Process engineering Lecture (2 hr) LO11
Week 12 Process engineering Tutorial (2 hr) LO11
Manufacturing numerical models Lecture (2 hr) LO11
Week 13 Manufacturing numerical models Tutorial (2 hr) LO11
Systems Engineering Project Super Tutorial Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. Interpret a design within the context of how it will be manufactured using a subtractive manufacturing.
  • LO2. Write Computer Numerical Control (CNC) codes using a simulator and be able to apply them to manufacture a component using a CNC machine.
  • LO3. Gain skills in selecting and designing jigs and fixtures to be used in the manufacture of a component.
  • LO4. Understand the structure and kinematics of a CNC machine and be able to select an appropriate number of axes and motors for the machine's design.
  • LO5. Gain skills in Systems Engineering, product planning, manufacturing sequence, time, teamwork, project management, cost and express the outcomes in a comprehensive report.
  • LO6. Understand the nomenclature, standards, and the selection process for the different commercially available 3D scanning systems with consideration for their relative merits.
  • LO7. Understand the nomenclature and selection process for different commercially available 3D printing systems with consideration for their relative merits and the .stl file format.
  • LO8. Use SolidWorks combined with CAMWorks to be introduced to multi-axis machining components that have complex non-orthogonal geometry.
  • LO9. Gain skills in the use of offline Robot Programming software packages such as the Robot Tool Box for MATLAB and CoppeliSim.
  • LO10. Gain skills in the development and compiling of Post Processors for use within machining packages such as CAMWorks.
  • LO11. Gain skills in the development of numerical machining models in Process Engineering.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

The UOS has been updated to match S2 2023 calendar.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.