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Unit outline_

DECO1008: 3D Modelling and Fabrication

Semester 2, 2020 [Normal day] - Camperdown/Darlington, Sydney

This unit teaches students an understanding of the basic concepts of modelling and prototyping 3D artefacts. Students will develop skills in creating and using 3D models for real-world and virtual environments. The unit further introduces students to rapid prototyping fabrication techniques, such as 3D printing and laser cutting with the aim to understand how to prepare a digital representation of artefacts (such as digital products or packaging) for physical fabrication. Students will learn how physical artefacts are represented in 3D digital models by modelling various 3D geometric entities, and how to create photorealistic representations that accurately and efficiently describe intent, structure, and geometric and surface variations of 3D models. Key concepts covered in this unit include: boundary representations, solid and parametric modelling, texture mapping, light sources, camera locations and projections.

Unit details and rules

Academic unit Design Lab
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Rohann Dorabjee, rohann.dorabjee@sydney.edu.au
Lecturer(s) Rohann Dorabjee, rohann.dorabjee@sydney.edu.au
Type Description Weight Due Length
Small test In-tutorial tasks
Tutorial exercise
20% Multiple weeks 8 hours
Outcomes assessed: LO1 LO2
Assignment Design concept sketches
Design
15% Week 04
Due date: 15 Sep 2020 at 23:59
6 A4 pages
Outcomes assessed: LO3 LO4 LO5
Assignment 3D model: fabricated and digital
Design
40% Week 09
Due date: 27 Oct 2020 at 23:59
300 Word Journal, 3D Model, A4 Poster
Outcomes assessed: LO1 LO2 LO5
Assignment Design visualisation
Design
25% Week 12
Due date: 20 Nov 2020 at 23:59
A1 poster, 50 words
Outcomes assessed: LO1 LO3 LO4

Assessment summary

  • In-tutorial tasks: For four weeks of the unit, there will be an in-tutorial task that will be marked on a 5-point scale.
  • Design concept sketches: Students will prepare a document describing and visualising their design concept for a smart autonomous device.
  • 3D model: fabricated and digital: Students will submit a 3D model that they have designed; both as a Blender scene file and as a digitally fabricated object. This object should demonstrate the student’s knowledge of appropriate strategies for modelling and digital fabrication.
  • Design visualisation: Students will prepare an A1 poster that communicates their design’s purpose and function. The poster should incorporate at least 1 photo-realistic rendering of their device, that demonstrates an understanding of lighting, camera positions, textures, materials, and other aspects of the rendering process.

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

Work of outstanding quality, demonstrating mastery of the learning outcomes assessed. The work shows significant innovation, experimentation, critical analysis, synthesis, insight, creativity, and/or exceptional skill.

Distinction

75 - 84

Work of excellent quality, demonstrating a sound grasp of the learning outcomes assessed. The work shows innovation, experimentation, critical analysis, synthesis, insight, creativity, and/or superior skill.

Credit

65 - 74

Work of good quality, demonstrating more than satisfactory achievement of the learning outcomes assessed, or work of excellent quality for a majority of the learning outcomes assessed.

Pass

50 - 64

Work demonstrating satisfactory achievement of the learning outcomes assessed.

Fail

0 - 49

Work that does not demonstrate satisfactory achievement of one or more of the learning outcomes assessed.

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 Introduction to 3D form. - History of 3D design tools and the influence of 3D modelling on design - Introduction to Assessments Lecture (1 hr)  
Understanding 3D form Tutorial (2 hr)  
Week 02 Digital 3D Modelling - Geometric theory of shapes - Principles of 3D representations - Visual relativity & computer graphics - The Blender environment Lecture (1 hr)  
Introduction to Blender Tutorial (2 hr)  
Week 03 Complex geometry in 3D space. - Boolean based objects - Geometric topology in relation to purpose and objective Lecture (1 hr)  
Basic 3D operations Tutorial (2 hr)  
Week 04 Digital Prototyping - DMaF Online Lecture (1 hr)  
DMaF Online Induction. - Workshop: on final pointers for Assignment 2 - Feedback session. Tutorial (2 hr)  
Week 05 Digital fabrication 1 Lecture (1 hr)  
Complex 3D operations part 1 Tutorial (2 hr)  
Week 06 Digital fabrication 2 Lecture (1 hr)  
Complex 3D operations Part 2 Tutorial (2 hr)  
Week 07 3D animation, rigging, and skinning properties Lecture (1 hr)  
Complex 3D operations part 3 Tutorial (2 hr)  
Week 08 Advanced product experiences Lecture (1 hr)  
Assessment Workshop. - Working towards completing Assignment 3 - Feedback session Tutorial (2 hr)  
Week 09 Rendering techniques Lecture (1 hr)  
Basic rendering techniques Tutorial (2 hr)  
Week 10 Rendering engines Lecture (1 hr)  
Advanced rendering techniques Tutorial (2 hr)  
Week 11 Visualisation techniques Lecture (1 hr)  
Post-production techniques: part 1 Tutorial (2 hr)  
Week 12 Fundamentals of VR environments Lecture (1 hr)  
Post-production techniques: part 2 - Post-production techniques. - Documentation preparation for final submission. Tutorial (2 hr)  

Attendance and class requirements

Please refer to the Resolutions of the University School: http://sydney.edu.au/handbooks/architecture/rules/faculty_resolutions.shtml

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. demonstrate effective strategies for 3D modelling and fabrication of objects
  • LO2. apply 3D modelling and fabrication techniques to achieve a creative outcome
  • LO3. assess the aesthetic qualities of tangible devices and apply to a new design
  • LO4. compose and render images for presentational impact and visual accuracy
  • LO5. understand and communicate design decisions and the technical constraints of 3D modelling technologies.

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.

This unit has changed in delivery due to the Pandemic. We also have made some changes to the weekly subject content as a result of the feedback received. The assessment brief has also been developed further for clarity.

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.