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Unit outline_

AMME5902: Computer Aided Manufacturing

Semester 2, 2020 [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 oral 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
? 
None
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Paul Briozzo, paul.briozzo@sydney.edu.au
Lecturer(s) Paul Briozzo, paul.briozzo@sydney.edu.au
Type Description Weight Due Length
Assignment Assignment 1 - CNC code generation
CNC Code Submission
15% Week 05
Due date: 25 Sep 2020 at 23:00
8 Hours
Outcomes assessed: LO1 LO2 LO3 LO4
Assignment Virtual CNC Mill Laboratory
Online version of the CNC Mill Laboratory
5% Week 06
Due date: 02 Oct 2020 at 23:00
2 Hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5
Assignment Assignment 2 - Fixture Design / Forces
Fixture Design / Forces
15% Week 08
Due date: 30 Oct 2020 at 23:00
8 Hours
Outcomes assessed: LO1 LO4 LO5
Assignment group assignment Virtual Rapid Engineering Laboratory
Virtual Rapid Engineering Laboratory
5% Week 09
Due date: 30 Oct 2020 at 23:00
2 hours
Outcomes assessed: LO4 LO5 LO9
Assignment Assignment 3 - Kinematics of Rapid Engineering
Kinematics of Rapid Engineering
15% Week 10
Due date: 06 Nov 2020 at 23:00
8 Hours
Outcomes assessed: LO4 LO5 LO9 LO13
Assignment group assignment Virtual Robot Assembly Laboratory
Virtual Robot Assembly Laboratory
5% Week 12
Due date: 20 Nov 2020 at 23:00
2 hours
Outcomes assessed: LO5 LO11
Assignment group assignment Presentation
5 to 6-minute video on Project topic in prerecorded MP4 format
10% Week 13
Due date: 20 Nov 2020 at 23:00
4 hours
Outcomes assessed: LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO10 LO11 LO12
Assignment group assignment Manufacturing Report
Final Report
30% Week 13
Due date: 20 Nov 2020 at 23:00
20 hours
Outcomes assessed: LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO10 LO11 LO12
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 calcululations.

Presentation: Group Presentation. A 5 to 6 minutes pre-recorded video (in .mp4 format) focusing on the major Project.

Manufacturing Report: Final Report. A report which includes many themes covered in the Unit of Study and is focused on the discussion of manufacturing one major assembly of components.

Virtual CNC Mill Laboratory: An online version of the CNC Mill Demonstration Laboratory that enables students to interact with CNC maching scenarios.

Virtual Rapid Engineering Laboratory: A report submission that enables students to undertake a Rapid Engineering task using the available Ultimaker software. 

Virtual Robot Assembly Laboratory: A report submission that enables students to undertake a Robot Assembly task using the available CoppeliaSim software.

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
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 Lecture (2 hr) LO1 LO2
CNC machining and CIMCO Lecture (2 hr) LO1 LO2 LO3
Week 04 CNC machining and CIMCO Tutorial (2 hr) LO1 LO2 LO3
3D Printing, Machining fixtures, jigs and forces Lecture (2 hr) LO4 LO9
Week 05 3D Printing, Machining fixtures, jigs and forces Tutorial (2 hr) LO4 LO9
Construction and kinematics of CNC machines Lecture (2 hr) LO5
Week 06 Construction and kinematics of CNC machines Tutorial (2 hr) LO5
3D scanning Lecture (2 hr) LO8
Week 07 Tutorial Assistance Tutorial (2 hr) LO2 LO3 LO4 LO5
CAMWorks 2.5 and 3 axis machining Lecture (2 hr) LO10
Week 08 CAMWorks 2.5 and 3 axis machining Tutorial (2 hr) LO10
Robot arm programming Lecture (2 hr) LO11
Week 09 Robot arm programming Tutorial (2 hr) LO11
Week 10 CAMWorks post processors Lecture (2 hr) LO10 LO12
Week 11 CAMWorks post processors Tutorial (2 hr) LO10 LO12
Process engineering Lecture (2 hr) LO13
Week 12 Process engineering Tutorial (2 hr) LO13
Super Tutorial Lecture (2 hr) LO6 LO7

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 method such as CNC machining.
  • LO2. write Computer Numerical Control (CNC) codes and apply them to manufacture a component using a CNC machine.
  • LO3. use a CNC machining simulator for development and checking of CNC codes.
  • LO4. gain skills in selecting and designing jigs and fixtures to be used in the manufacture of a component.
  • LO5. 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.
  • LO6. gain skills in manufacturing management and systems such as; product planning, manufacturing sequence, time and cost and express the outcomes in a comprehensive report.
  • LO7. gain teamwork and project management skills and be able to apply then in the context of an engineering project.
  • LO8. understand the nomenclature, standards, and the selection process for the different commercially available 3D scanning systems with consideration for their relative merits.
  • LO9. understand the nomenclature and selection process for different commercially available 3D printing systems with consideration for their relative merits and the .stl file format.
  • LO10. use SolidWorks combined with CAMWorks to be introduced to multi-axis machining components that have complex non-orthogonal geometry.
  • LO11. gain skills in the use of offline Robot Programming software packages such as the Robot Tool Box for MATLAB and CoppeliSim.
  • LO12. gain skills in the development and compiling of Post Processors for use within machining packages such as CAMWorks.
  • LO13. 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 revised to accomodate more individual learning assesments to provide students with a better learning pathway during COVID-19 restrictions.

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.