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Unit outline_

MECH9660: Manufacturing Engineering

Semester 1, 2020 [Normal day] - Camperdown/Darlington, Sydney

The unit aims to teach the fundamentals of manufacturing processes and systems in mechanical, mechatronic and biomedical engineering, including traditional and advanced manufacturing technologies. This unit aims to develop the following attributes: to understand the fundamental principles of manufacturing technologies for the above mentioned engineering areas; to gain the ability to select existing manufacturing processes and systems for direct engineering applications; to develop ability to create innovative new manufacturing technologies for advanced industrial applications; to develop ability to invent new manufacturing systems. At the end of this unit students will have a good understanding of the following: merits and advantages of individual manufacturing processes and systems; principles of developing new technologies; comprehensive applications and strategic selection of manufacturing processes and systems. Course content will include: CAD / CAM: An introduction into the use of CAD and manual CNC coding as separate tools combined with an introduction into the kinematics and structural requirements in the construction of a CNC machine. Rapid Engineering: An introduction into the most current Rapid Engineering methods currently in use. Manufacturing Processes: Common processes and their science (machining, casting, powder metallurgy, metal working, welding) and their relative merits and limitations.

Unit details and rules

Academic unit Aerospace, Mechanical and Mechatronic
Credit points 6
Prerequisites
? 
MECH9400
Corequisites
? 
None
Prohibitions
? 
MECH8660
Assumed knowledge
? 

None

Available to study abroad and exchange students

No

Teaching staff

Coordinator Paul Briozzo, paul.briozzo@sydney.edu.au
Lecturer(s) Karina Taylor, karina.taylor@sydney.edu.au
Type Description Weight Due Length
Assignment group assignment Rapid Engineering Laboratory Group Report
Group Report
5% Multiple weeks n/a
Outcomes assessed: LO1 LO2 LO4 LO5 LO6
Assignment group assignment Robot Assembly Laboratory Video
Video Submission
5% Multiple weeks No longer than 90 seconds
Outcomes assessed: LO1 LO2
Assignment Assignment 0 - CNC Code Development
CNC Code Development
10% Week 05
Due date: 27 Mar 2020 at 23:00
n/a
Outcomes assessed: LO7
Assignment group assignment Assignment 1 - Kinematics of CNC Machines and Automation
Report and LabView File Submission
20% Week 07
Due date: 09 Apr 2020 at 23:00
n/a
Outcomes assessed: LO2 LO7 LO6 LO5 LO4 LO3
Small test Quiz 1 - CNC Machining and Automation
Quiz 1 assess content delivered in Weeks 1 to 6
20% Week 07
Due date: 06 Apr 2020 at 11:00
50 Minutes
Outcomes assessed: LO2 LO7 LO6 LO5 LO4 LO3
Assignment group assignment Assignment 2 - Manufacturing Processes and Automation
Report and LabView File Submission
20% Week 13
Due date: 29 May 2020 at 23:00
n/a
Outcomes assessed: LO2 LO6 LO5 LO4 LO3
Small test Quiz 2 - Manufacturing Processes and Automation
Quiz 2 assess content delivered in Weeks 7 to 12
20% Week 13
Due date: 26 May 2020 at 11:00
50 Minutes
Outcomes assessed: LO2 LO6 LO5 LO4 LO3
group assignment = group assignment ?

Assessment summary

  • Assignment 0: Focuses on writing CNC code for a simple machine element. 
  • Assignment 1: This has two parts and requires the basic design of a 3D printer and automation system using LabView. 
  • Assignment 2: This has two parts and requires that students either compare manufacturing processes in the design of a component and automation system using LabView.
  • Rapid engineering laboratory group report: A group report focusing on the rapid engineering laboratory and individual research must be submitted no later than two weeks of attending the rapid engineering laboratory.
  • Robotic assembly laboratory video: A group video focusing on the robotic pick and place assembly laboratory must be submitted via the CANVAS ARC video submission system.

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.

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 1. Introduction to Unit of Study and CNC Machining; 2. Manufacturing Automation - Introduction to Automation and Testing Lecture and tutorial (4 hr) LO2 LO7
Week 02 1. CNC Machining; 2. Manufacturing Automation - Data Acquisition and LabVIEW Lecture and tutorial (4 hr) LO2 LO7
Week 03 1. Cutting Forces plus Jigs and Fixtures; 2. Manufacturing Automation - Analogue Sampling and LabVIEW Lecture and tutorial (4 hr) LO2 LO3 LO4 LO6 LO7
Week 04 1. CNC Machining - Structure and Kinematics; 2. Manufacturing Automation - Data processing with LabVIEW Lecture and tutorial (4 hr) LO2 LO3 LO4 LO6 LO7
Week 05 1. CNC Machining - Review Lecture; 2. Manufacturing Automation - Software Development - Design Patterns Lecture and tutorial (4 hr) LO2 LO3 LO4 LO6
Week 06 1. Manufacturing Processes - Casting; 2. Manufacturing Automation - Review Lecture Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 07 1. Quiz 1; 2. Manufacturing Automation - Automated Inspection Systems Lecture and tutorial (4 hr) LO2 LO3 LO4 LO5 LO6 LO7
Week 08 1. Manufacturing Processes - Shrink Fits; 2. Manufacturing Automation - Finding Measurements in VBAI Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 09 1. Manufacturing Processes - Welding; 2. Manufacturing Automation - Measurements and OCR in VBAI Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 10 1. Manufacturing Processes - Metal Forming Thin; 2. Manufacturing Automation - VBAI Tools and Vision in LabVIEW Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 11 1. Manufacturing Processes - Forging; 2. Manufacturing Automation - Introduction to Motion Control Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 12 1. Manufacturing Processes - Powder Metallurgy; 2. Manufacturing Automation - Review Lecture Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 13 1. Manufacturing Processes - Review Lecture; 2. Quiz 2 Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 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.

Required readings

All readings for this unit can be accessed through the Library eReserve, available on Canvas.

  • Paul Briozzo, MECH3660 8660 9660 Manufacturing Engineering.

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. Contribute to effective team processes
  • LO2. Understand the fundamental principles of manufacturing technologies for mechanical and mechatronic engineering
  • LO3. Discuss the major problems in the current manufacturing practice and provide suggestions to overcome or improve them
  • LO4. Determine functional requirements of a product in terms of application and suitability
  • LO5. Discuss the merits and disadvantages of an individual manufacturing method
  • LO6. Determine the basic manufacturing considerations necessary to realise the function, including the selection of materials and the manufacturing method, taking into account the strength and reliability
  • LO7. Display familiarity in the use of CNC machining in manufacturing

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.

Content related to Manufacturing Processes and Automation have been expanded in 2020.

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.