Course overview
- Study period
- Semester 2, 2025 (21/07/2025 - 15/11/2025)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Mech & Mine Engineering School
Development of a pre-feasibility study for a metalliferous or coal mining project. Activities include assessment of reserves, method selection, layout and optimisation of surface and underground operations, geotechnical design, ventilation design, project risk assessment, mine scheduling, equipment selection, cost estimation, economics / finance, and sustainability. Mine design and optimisation software packages are used.
This course employs a project-based learning approach. It aims to bring together the full range of disciplines offered in Mining Engineering for use on a real mining project. Students will use several mine design and optimisation packages in order to complete the project, which will give students an industrial based experience about these commonly used software packages in the mining industry.
Students will be given some occasional lectures on specific topics related to the project as a refresher.
Since the course will be completed as a group project, students will need to organise among themselves how to share the workload and decide who is responsible for which component of the project within their group. Although there is no expectation that every student will be heavily involved in all aspects, students will need to provide each other with a thorough debriefing so that each of them know the key details of what the other has completed.
Course requirements
Assumed background
Students should have sufficient knowledge to apply the principles of resource geology, resource estimation, mine planning and design, surface and underground mining methods, minerals economics, ventilation design, geotechnical engineering, equipment selection and financial modelling.
Recommended prerequisites
We recommend completing the following courses before enrolling in this one:
[MINE3122 or MINE4126] and [MINE3123 or MINE4127]
Course contact
Course staff
Lecturer
Casual academic
Mr Oskar Clare
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
The aim of this course is to provide students with the principles of mine feasibility studies for a metalliferous deposit and develop their skills for optimal mine design, mine scheduling and preparation of a pre-feasibility report. The project should be undertaken in the spirit of a pre-feasibility study; that is, to determine its technical and then economical viability using engineering design principles and project evaluation methodologies.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Analyse and interpret data for the design of a mine.
LO2.
Design and optimise a mine utilising geometrical, geotechnical and economical design parameters.
LO3.
Select a mining method most appropriate for a deposit, develop production plans and perform equipment selection and apply geomechanics and ventilation considerations.
LO4.
Estimate the social, economical and environmental impact of the selected mining method and the project.
LO5.
Develop a mine schedule for maximising the project Net Present Value and perform economic evaluations for a mining operation.
LO6.
Enhance collaborative competencies and master advanced oral and written communication techniques to effectively contribute to team-based projects.
LO7.
Apply mine design and optimisation software packages.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Presentation |
Progress Presentation/Interview 1
|
10% |
22/08/2025 8:00 am |
| Presentation |
Progress Presentation/Interview 2
|
15% |
19/09/2025 8:00 am |
| Presentation |
Final Presentation
|
25% |
24/10/2025 8:00 am |
| Paper/ Report/ Annotation |
Final Hard Rock Mine Design Report
|
50% |
31/10/2025 1:00 pm |
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
Progress Presentation/Interview 1
- Hurdle
- Team or group-based
- Mode
- Oral
- Category
- Presentation
- Weight
- 10%
- Due date
22/08/2025 8:00 am
- Other conditions
- Peer assessed, Peer assessment factor.
- Learning outcomes
- L01, L02, L03, L04, L06, L07
Task description
More information will be provided during the applied class.
Please refer to Blackboard for detailed marking criteria.
If, for whatever reason, you find that your group is not functioning effectively, please contact your Course Coordinator for support.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Hurdle requirements
Students must obtain at least 40% or higher on the combined presentation/interview marks after the peer review marks are applied in order to achieve a passing grade.Submission guidelines
No submission is required.
Deferral or extension
You may be able to apply for an extension.
Discretionary extensions are not available for this task.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
Students who are unable to attend the presentation/interview at the scheduled date and time should apply for an extension, with evidence that supports this. As this is a timed-assessment, Student Access Plans (SAPs) are not suitable supporting documentation.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
Presentation/interviews are scheduled and time limited.
Progress Presentation/Interview 2
- Hurdle
- Team or group-based
- Mode
- Oral
- Category
- Presentation
- Weight
- 15%
- Due date
19/09/2025 8:00 am
- Other conditions
- Peer assessed, Peer assessment factor.
- Learning outcomes
- L01, L03, L04, L05, L06, L07
Task description
More information will be provided during lectures.
Please refer to Blackboard for detailed marking criteria.
If, for whatever reason, you find that your group is not functioning effectively, please contact your Course Coordinator for support.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Hurdle requirements
Students must obtain at least 40% or higher on the combined presentation/interview marks after the peer review marks are applied in order to achieve a passing grade.Submission guidelines
No submission is required.
Deferral or extension
You may be able to apply for an extension.
Discretionary extensions are not available for this task.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
Students who are unable to attend the presentation/interview at the scheduled date and time should apply for an extension, with evidence that supports this. As this is a timed-assessment, Student Access Plans (SAPs) are not suitable supporting documentation.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
Presentation/interviews are scheduled and time limited.
Final Presentation
- Hurdle
- Team or group-based
- Mode
- Activity/ Performance
- Category
- Presentation
- Weight
- 25%
- Due date
24/10/2025 8:00 am
- Other conditions
- Peer assessed, Peer assessment factor.
- Learning outcomes
- L01, L02, L03, L04, L05, L06, L07
Task description
More information will be provided during lectures.
Please refer to Blackboard for detailed marking criteria.
If, for whatever reason, you find that your group is not functioning effectively, please contact your Course Coordinator for support.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Hurdle requirements
Students must obtain at least 40% or higher on the combined presentation/interview marks after the peer review marks are applied in order to achieve a passing grade.Submission guidelines
Deferral or extension
You may be able to apply for an extension.
Discretionary extensions are not available for this task.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
Students who are unable to attend the presentation at the scheduled date and time should apply for an extension, with evidence that supports this. As this is a timed-assessment, Student Access Plans (SAPs) are not suitable supporting documentation.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
Presentations are scheduled and time limited.
Final Hard Rock Mine Design Report
- Team or group-based
- Mode
- Written
- Category
- Paper/ Report/ Annotation
- Weight
- 50%
- Due date
31/10/2025 1:00 pm
- Other conditions
- Peer assessed, Peer assessment factor.
- Learning outcomes
- L01, L02, L03, L04, L05, L06, L07
Task description
More information will be provided during lectures.
Please refer to Blackboard for detailed marking criteria.
If, for whatever reason, you find that your group is not functioning effectively, please contact your Course Coordinator for support.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Submission guidelines
Submission is via Turn-it-in on the course Blackboard site. Email submission will not be accepted. ALWAYS keep a copy of your submitted assignment.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
Extensions impact on other students in the team.
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.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Cut off Percent | Description |
|---|---|---|
| 1 (Low Fail) | 0.00 - 19.99 |
Absence of evidence of achievement of course learning outcomes. Course grade description: The student made little to no attempt to demonstrate any relevant knowledge or understanding of the underlying concepts. |
| 2 (Fail) | 20.00 - 44.99 |
Minimal evidence of achievement of course learning outcomes. Course grade description: The student fails to demonstrate any relevant knowledge or understanding of the underlying concepts. Much of the information provided is inaccurate and irrelevant. The student has failed to contribute to the project team. |
| 3 (Marginal Fail) | 45.00 - 49.99 |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: Some knowledge of the course is evident, but the student only demonstrates a limited understanding of the underlying concepts and the information provided is largely inaccurate or irrelevant. |
| 4 (Pass) | 50.00 - 64.99 |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: The student demonstrates a sound knowledge of the relevant information and at least a partial understanding of the underlying concepts. Has some correct and some incorrect information. [50.00-64.99%] plus 40% or higher on the combined presentation/interview marks. |
| 5 (Credit) | 65.00 - 74.99 |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: The student demonstrates a sound knowledge of the relevant information and a sound understanding of the key concepts. There are only minor factual inaccuracies or invalid assumptions. [65.00-74.99%] plus 40% or higher on the combined presentation/interview marks. |
| 6 (Distinction) | 75.00 - 84.99 |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: Key concepts are understood. There are only very minor factual inaccuracies or invalid assumptions and no irrelevant information. [75.00-84.99%] plus 40% or higher on the combined presentation/interview marks. |
| 7 (High Distinction) | 85.00 - 100 |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: Key concepts are understood and can be used to generate possible solution for the real mining project. There is evidence of critical analysis and an ability to synthesize information from different aspects of the course. Outstanding achievement on the project reports and presentation. [85.00-100.00%] plus 40% or higher on the combined presentation/interview marks. |
Additional course grading information
Students must obtain at least 40% or higher on the combined presentation/interview marks after the peer review marks are applied in order to achieve a passing grade.
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
Peer Assessment:
Group performance is a key component of the assessment for this course. The sole measure of performance of teamwork is by peer review. Teams which are having problems with unproductive or non-cooperative members are encouraged to seek the intervention of the course coordinator as early as possible. Do not leave these problems to the last minute. The PEER REVIEW is required for all group assessments. An online tool will be used to collect Self and Peer Assessment data. This data will be used to provide feedback to, and receive feedback from, your group members regarding contributions to the project.
Based on a series of answers from each group member the Peer Assessment Tool automatically produces two weighting factors. The SPA or Self and Peer Assessment factor is a measure of how the group overall viewed the contribution of each member of the group. This factor will be used to adjust the group mark for the project into an individual mark.
Individual mark = Group mark x Individual’s SPA
For example; a student who receives an SPA factor of 0.9 for their project contributions, reflecting a lower than average team contribution as perceived by a combination of themselves and their peers, would receive an individual mark of 72% if their group project mark was 80%.
The second factor calculated is the SAPA factor. This is the ratio of a student’s own self assessment rating compared to the average rating of their contribution by their peers. It provides students with feedback about how the rest of the group perceives their contribution. For example, a SAPA factor greater than 1 means that a student has rated their own performance higher than they were rated by their peers. Conversely, a SAPA factor less than 1 means that a student has rated their own performance lower than they were rated by their peers.
Both factors for each student will be released to all group members.
The idea of using an online peer assessment tool is not only to make group work fairer and provide feedback on your performance but to encourage the development of your professional skills. These skills include giving and receiving both positive and negative feedback, conflict resolution, collaboration, the ability to assess both your work and the work of your peers and developing your professional judgement. If you successfully achieve these learning outcomes your group experience should be productive. Teams that contain students who do not adequately participate in group activities and/or develop their teamwork skills typically have friction between group members.
Objections:
The initially SPA and SAPA factors will be preliminary, and only become official after any protests are considered. Any students believing their peer assessments were unfair may lodge an objection. Any objection to yourself and peer assessment ratings must be made in writing to the lecturer in charge of the project. Each objection must be a maximum of 500 words (12 point Times New Roman font) clearly outlining why you believe your rating is unfair. Your protest will be discussed with the other members of your group. Objections must be lodged within 3 days from the date that the peer assessment results are released.
An objection usually indicates that at least one member of a group has not achieved the teamwork learning objectives. Marks are only awarded for successfully achieving learning outcomes. The lodgement of an objection will be considered as a request for reassessment of the entire group. Hence if a student lodges an objection the marks for the entire group will be reassessed and released after the objection has been considered. In considering any objection the log books and or meeting minutes for a group will be reviewed.
The course coordinator reserves the final say in application of the SPA factor.
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
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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 |
|---|---|---|
Week 1 (28 Jul - 03 Aug) |
Applied Class |
Course Introduction Introduction to the project. Introduction to general mine design and feasibilty studies. Learning outcomes: L01 |
Week 2 (04 Aug - 10 Aug) |
Applied Class |
Mine design software training Introduction to Mine Design software Learning outcomes: L01, L02 |
Week 3 (11 Aug - 17 Aug) |
Applied Class |
Pit Optimisation and Production Scheduling Block model validation/interrogation Learning outcomes: L01, L02 |
Week 4 (18 Aug - 24 Aug) |
Applied Class |
Progress Presentations/Interviews Progress Presentation/Interviews 1. All students need to present in a 10 + 5 mins presentation for each group. Learning outcomes: L01, L02, L03, L04, L06, L07 |
Week 5 (25 Aug - 31 Aug) |
Applied Class |
Reserve Calculation and Pit Design Learning outcomes: L01, L02, L03, L05 |
Week 6 (01 Sep - 07 Sep) |
Applied Class |
Underground design and Production Sch. Learning outcomes: L01, L02, L03, L05 |
Week 7 (08 Sep - 14 Sep) |
Applied Class |
Equipment Selection and Staffing Learning outcomes: L01, L04, L06 |
Week 8 (15 Sep - 21 Sep) |
Applied Class |
Progress Presentations/Interviews Progress Presentation/Interviews 2. All students need to present in a 10 + 5 mins presentation for each group. Learning outcomes: L01, L03, L04, L05, L06, L07 |
Week 9 (22 Sep - 28 Sep) |
Applied Class |
Ventilation, Geotech Analysis and Design Learning outcomes: L01, L02, L05 |
Week 10 (06 Oct - 12 Oct) |
Applied Class |
Social and Environmental Impact Learning outcomes: L01, L07 |
Week 11 (13 Oct - 19 Oct) |
Applied Class |
Economic Evaluation and Cost Estimation Learning outcomes: L01, L07 |
Week 12 (20 Oct - 26 Oct) |
Applied Class |
Final Presentations Final Presentations. All students need to present in a 10 + 5 mins presentation for each group. Learning outcomes: L01, L02, L03, L04, L05, L06, L07 |
Week 13 (27 Oct - 02 Nov) |
Applied Class |
Mine Closure and Rehabilitation Learning outcomes: L06 |
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 for Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.