Course overview
- Study period
- Semester 2, 2024 (22/07/2024 - 18/11/2024)
- Study level
- Postgraduate Coursework
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Mech & Mine Engineering School
Students will learn how to design experiments to explore the entire parameter space for an engineering problem; they will learn how to test hypotheses to a desired degree of confidence; they will learn how to process data from engineering sensors and how to analyse such data using advanced multivariate statistics.
Our understanding of science is driven by experimental measurements and observations, and so too is our application of the scientific principles so derived to deliver useful and reliable engineering outcomes. Historically, much experimentation and research has occurred in a somewhat random manner and many discoveries have been quite fortuitously picked up by alert observers who were able to correlate certain occurrences with specific causational circumstances. However, a poorly planned and executed experimental campaign is of little or no value, and may even set back the cause of science, and its counterpart engineering application, by providing misleading or faulty information. The primary cause of this is the fundamental complexity of physical processes, which are in general controlled and influenced by a multitude of interacting parameters, all of which may not be known. Experiments which don’t take this into account are inherently faulty. A multi-parametric investigation is required to fully and accurately characterise any physical system. However, comprehensive investigations of coupled multiple parametric variations quickly become impractical, and a scientific approach is needed in order to plan an achievable testing sequence which can reliably quantify a system or process over the required envelope of conditions. Likewise, in order to use the results of experimental measurements, an understanding of the circumstances under which they were made and the errors associated with every single measurement is required.
In many situations, the physical processes involved are well understood and can be accurately modelled numerically; however, the execution of computer simulations may be very expensive and time consuming, and the design process must be well planned in order to iterate to a valid engineering solution in the most efficient way. In these cases, it is important to plan campaigns of numerical analysis in the context and understanding of the significance of the various groups of parametric variables, and the likely interactions between relative parametric groupings.ﾠ
This has led to a professional discipline known as the design of experiments, or ‘experimental design’, which establishes procedures for the generation and subsequent use of experimental data. Experimental design concerns the effect of some process or intervention on a physical situation which is of interest to the experimenter. Design of experiments is a discipline that has very broad application across all the natural and social sciences. For example, in a manufacturing process there are many factors that could affect the quality of a product, and in fluid flow many interacting parameters influence the forces on immersed objects. Experiment design can help identify the most important factors and use them to control the quality of a product (if possible) and to understand and model the system. Design of experiments can also be applied to numerical investigations in order to increase the efficiency of the simulation sequence. Design of experiment methods usingﾠstatistics can be applied in any engineering discipline.
This course introduces the elements of experiment design and its application to practical engineering problems. The focus is on the application of design of experiment techniques or methods in practical engineering projects, and the basics of statistical analysis are discussed. The basic concepts of control factors, noise factors, array design, and ANOVA analysis will be introduced. The key concepts as well as the standard design of experiment methods will be applied in experimental group projects performed by the students.
ﾠ
Course requirements
Assumed background
Students are assumed to have had acquired the skills and knowledge of a graduate engineer. In particular, this course requires a good understanding of the basic concepts of statistics, for example Gaussian distribution, standard deviation, etc. It is recommended that students refresh their basic knowledge in statistics before they take the course.
Incompatible
You can't enrol in this course if you've already completed the following:
ENGG7601
Course contact
Course staff
Lecturer
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
The main aim of this course is for students to develop the ability to apply design of experiment methods in their research and engineering projects, and also to give students experience in applying Design of Experiments (DoE)ﾠconcepts to real engineering problems.
It will also give them the skills to evaluate archival experimental data from other researchers for use in their own application, with appropriate consideration and analysis of the applicability of the data in that situation and with statistical evaluation of the appropriate error bars.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Understand the fundamental concepts and methods in design of experiments.
LO2.
Apply the techniques to design an experiment and collect and analyse data using the experiment design methods
LO3.
Conduct an uncertainty analysis of the parameters in experiments
LO4.
Gain more experience in working within a group to complete a project
LO5.
Report findings from a DoE investigation and make appropriate recommendations
LO6.
Apply techniques from a range of engineering subjects to solve a design task
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Practical/ Demonstration |
Laboratory Experiments
|
P/F |
At scheduled practical sessions. |
| Tutorial/ Problem Set | Assignment - Dimensional analysis and scaling | 10% |
8/08/2024 4:00 pm |
| Project |
Major Experimental Project
|
50% |
Design of test model (10%) 29/08/2024 4:00 pm PAF 1 6/09/2024 5:00 pm Experimental Plan (10%) 19/09/2024 4:00 pm Experiment Final Report (30%) 22/10/2024 4:00 pm PAF 2 25/10/2024 5:00 pm |
| Examination |
Final Exam
|
40% |
End of Semester Exam Period 2/11/2024 - 16/11/2024 |
A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.
Assessment details
Laboratory Experiments
- Team or group-based
- In-person
- Mode
- Activity/ Performance
- Category
- Practical/ Demonstration
- Weight
- P/F
- Due date
At scheduled practical sessions.
- Learning outcomes
- L01, L02, L03, L04
Task description
A series of three experiments are to be completed in Weeks 4, 7 and 10. Details will be released via Blackboard. This activity is not directly assessed; however, attendance is compulsory. Students must arrive within 10 minutes of the session commencement to be marked as attending. Closed footwear is a requirement of the laboratory sessions.
All experiments are to be performed in groups of three to four, using the same groups for all of the experientially based assessment items. Students will enroll on Blackboard for the group of their choice, within their scheduled practical sessions. The group enrolment details will be made available prior to the first experimental session. Please let the Course Coordinator know ASAP if you need to change groups as this is only possible early in the semester.
The first experimental session involves familiarisation with the apparatus and calibration of the test section. The second session involves a simple experiment where students are given the opportunity to apply their developing skills in design of experiments to the scenario. The final session involves the testing of student-designed apparatus that will be reported on at the end of semester in the experiment final report.
Submission guidelines
Deferral or extension
You cannot defer or apply for an extension for this assessment.
Practicals are 4 hours in length and only suitable for small groups. As such, there is limited opportunity for a student to be able to attend another. Students who are unable to attend the practical for an acceptable reason as described on https://my.uq.edu.au/information-and-services/manage-my-program/exams-and-assessment/applying-assessment-extension?p=1#1, should apply for an extension via my.UQ for alternative arrangements. Students who do not attend the practicals without an approved reason will have a grade cap of 5 applied.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
Students must arrive within 10 minutes of the session commencement to be marked as attending. Students who arrive late owing to circumstances beyond their control should attend as soon as it is practical, alert their group members, and contact the Course Coodinator at the conclusion of the session with an explanation.
Assignment - Dimensional analysis and scaling
- Mode
- Written
- Category
- Tutorial/ Problem Set
- Weight
- 10%
- Due date
8/08/2024 4:00 pm
- Learning outcomes
- L01, L06
Task description
This assignment tests the understanding of lecture material presented on the analysis of physical phenomena based on the fundamental dimensions of the controlling parameters, and on the scaling of the known performance of specific situations to conditions where different scales apply. This may refer to a direct scaling of physical size (such as perhaps a small prototype model air plain), velocities, temperatures, material properties or other parameters. The task sheet will be available for download from the course Blackboard site. Students will work individually to complete the tasks.
Submission guidelines
Submit via TurnItIn on Blackboard
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
Feedback is provided to students following 14 calendar days.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Major Experimental Project
- Team or group-based
- Mode
- Written
- Category
- Project
- Weight
- 50%
- Due date
Design of test model (10%) 29/08/2024 4:00 pm
PAF 1 6/09/2024 5:00 pm
Experimental Plan (10%) 19/09/2024 4:00 pm
Experiment Final Report (30%) 22/10/2024 4:00 pm
PAF 2 25/10/2024 5:00 pm
- Learning outcomes
- L01, L02, L03, L04, L05, L06
Task description
This is a group project, prepared by groups of three to four students per group. You should stay in the same laboratory group throughout semester, unless groups become unviable due to withdrawals or non-functional group dynamics. Please inform the Course Coordinator if such a situation appears to be developing. Conflicts within a group are nearly always resolved satisfactorily between group members without intervention from the academic staff, but do not hesitate to contact the Course Coordinator if incipient problems are not resolved in good time.
Design of Test Model
In the Experiment Test Model, students will prepare a design for a test model to be fabricated and used in experiments completed in the third laboratory session. This third laboratory session is held in Week 10. The test models must be designed and sent for fabrication prior to the testing session. Due to workshop fabrication constraints, the test model designs must be submitted to the workshop by the end of Week 6. Detailed instructions will be supplied on Blackboard.
Experimental Plan
The Experimental Plan submission will involve the development of an experimental plan and appropriate risk assessments for the testing to be completed in the third laboratory session. Detailed instructions will be supplied on Blackboard.
Experiment Final Report
This report contains the results and analysis of your final experimental testing campaign. It should include the logical reasoning by which the testing matrix was developed, identification of the governing non-dimensional parameters involved, and an analysis of the final results with reference to the parameters identified. A full error analysis should be contained of the uncertainty in the raw data collected, and in the compounded errors in the computed parameters. Couplings and trends of the output data should be identified, and where possible empirical correlations should be developed to quantify the outputs in a non-dimensional form with generic applicability that future workers in the field can use, without repeating another experimental program. Full details will be supplied on Blackboard.
Peer assessment of team member contributions (PAF)
Two peer assessments will be performed in Week 7 and 13. The results from the peer assessments will be used to scale all team marks, which account for 50% of the course.
Peer assessment scores can decrease your individual score. No increase in score is possible. The purpose of the peer assessment is not to artificially elevate your personal score above the collective team. Peer assessment factors will be capped at 1.0 of the total team mark. There is no lower bound on the PAF (students that do not contribute to the team exercises can receive a zero).
The two peer assessment factors will be averaged unless there is an overwhelmingly compelling reason not to do so (at the discretion of the Course Coordinator). The first peer assessment will open in Week 6 and must be completed by Week 7. The second peer assessment will open in Week 12 and must be completed by Week 13.
Submission guidelines
Submit the reports via TurnItIn on Blackboard.
Buddycheck will be used for PAF evaluations.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
Extensions to the Design of Test Model are limited to 3 days due to workshop fabrication time restrictions. This is owing to the time taken for the teaching team to convert the files suitable to fabrication.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Final Exam
- Hurdle
- Identity Verified
- Mode
- Written
- Category
- Examination
- Weight
- 40%
- Due date
End of Semester Exam Period
2/11/2024 - 16/11/2024
- Learning outcomes
- L01, L02, L03
Task description
Your understanding of the course concepts will be tested by an end of semester examination. This exam will be open book.
Questions will be set which require comprehension of and ability to use the course material, demonstrated by the solving of engineering problems with clearly defined conditions. All material used during the examination must be in hard copy only. Any UQ approved calculator may be used, but personal computers may not.
Hurdle requirements
A minimum score of 40% in the Final Exam is required to receive a passing grade for the course.Exam details
| Planning time | 10 minutes |
|---|---|
| Duration | 120 minutes |
| Calculator options | (In person) Casio FX82 series or UQ approved , labelled calculator only |
| Open/closed book | Open Book examination |
| Materials | Any additional written or printed material is permitted; material may also be annotated. |
| Exam platform | Paper based |
| Invigilation | Invigilated in person |
Submission guidelines
Deferral or extension
You may be able to defer this exam.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Cut off Percent | Description |
|---|---|---|
| 1 (Low Fail) | 0.00 - 29.99 |
Absence of evidence of achievement of course learning outcomes. Course grade description: Overall grade. |
| 2 (Fail) | 30.00 - 44.99 |
Minimal evidence of achievement of course learning outcomes. Course grade description: Overall grade 30.00-44.99% |
| 3 (Marginal Fail) | 45.00 - 49.99 |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: Falls short of satisfying basic requirements for a Pass. Overall grade: 45.00-49.99% or less than 40% in the IVA requirement explained below. |
| 4 (Pass) | 50.00 - 64.99 |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: Satisfies all of the basic learning requirements for the course, such as knowledge of fundamental concepts and performance of basic skills; demonstrates sufficient quality of performance to be considered satisfactory or adequate or competent or capable in the course. Overall grade 50.00-64.99% and a minimum score of 40% in the IVA requirement explained below. |
| 5 (Credit) | 65.00 - 74.99 |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: Demonstrates ability to use and apply fundamental concepts and skills of the course, going beyond mere replication of content knowledge or skill to show understanding of key ideas, awareness of their relevance, some use of analytical skills, and some originality or insight. Overall grade 65.00-74.99% and a minimum score of 40% in the IVA requirement explained below. |
| 6 (Distinction) | 75.00 - 84.99 |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: Demonstrates awareness and understanding of deeper and subtler aspects of the course, such as ability to identify and debate critical issues or problems, ability to solve non-routine problems, ability to adapt and apply ideas to new situations, and ability to invent and evaluate new ideas. Overall grade 75.00-84.99% and a minimum score of 40% in the IVA requirement explained below and attended all practicals. |
| 7 (High Distinction) | 85.00 - 100.00 |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: Demonstrates imagination, originality or flair, based on proficiency in all the learning objectives for the course; work is interesting or surprising or exciting or challenging or erudite. Overall grade 85.00-100% and a minimum score of 40% in the IVA requirement explained below and attended all practicals. |
Additional course grading information
Students who do not attend the practicals without an approved reason will have a grade cap of 5 applied.
Grading Criteria
Specific grading criteria will be provided for each assessment item.
Identity verified assessment
Identity verified assessment (IVA) will be achieved by the studentﾠ obtaining ﾠat least 40% of the available marks ﾠin the final exam.ﾠ
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
A failure to reference AI use may constitute student misconduct under the Student Code of Conduct.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Find the required and recommended resources for this course on the UQ Library website.
Additional learning resources information
Suggested learning resources will be posted to the Blackboard site.
Students can access the required UQ Laboratory Induction information on Blackboard.
You are advised to check the Blackboard site for this course for announcements at least once per week and preferably more often.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Not scheduled |
Not Timetabled |
Background reading and research Independent Study (Independent Study): Students are expected to read the course notes prior to attending the lecture/discussion sessions, and are expected to do further independent reading on the principles covered in the course. Learning outcomes: L01 |
Multiple weeks From Week 1 To Week 13 |
Tutorial |
Tutorials Set questions are given on the lecture material. The tutorials are the primary times for discussing course work with the staff and getting feedback on submitted work. Learning outcomes: L01, L03 |
Lecture |
Lectures Lectures on design of experiments, dimensional analysis and scaling, uncertainty analysis, and statistics. Learning outcomes: L01, L06 |
|
Multiple weeks From Week 4 To Week 10 |
Practical |
Laboratory Student groups implement their experimental designs in the mechanical engineering laboratories. Student groups each attend three laboratory sessions on fan driven wind tunnels as rostered. The first session involves familiarisation with the apparatus and calibration of the test section. The second involves testing of the models and instrumentation prepared for the experiment, and the final session involves completion of the experimental test matrix prepared. Learning outcomes: L01, L02, L03, L04, L05 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.
You'll also need to be aware of the following policies and procedures while completing this course:
- Laboratory Occupational Health and Safety