| Effective Term: | 2026/05 |
| Institute / School : | Institute of Innovation, Science & Sustainability |
| Unit Title: | Smart Engineering Technologies |
| Unit ID: | ENGPG9407 |
| Credit Points: | 15.00 |
| Prerequisite(s): | Nil |
| Co-requisite(s): | Nil |
| Exclusion(s): | (ENGRG9401) |
| ASCED: | 030303 |
| Other Change: | |
| Brief description of the Unit |
The unit introduces key technologies essential for modern engineering practices. These include modern tunneling technologies, sensor technologies, industrial robots, data analytics, and artificial intelligence. The unit aims to prepare students to become the engineering and applied science professionals of tomorrow. |
| Grade Scheme: | Graded (HD, D, C, P, MF, F, XF) |
| Work Experience Indicator: |
| No work experience |
| Placement Component: | |
| Supplementary Assessment:Yes |
| Where supplementary assessment is available a student must have failed overall in the Unit but gained a final mark of 45 per cent or above, has completed all major assessment tasks (including all sub-components where a task has multiple parts) as specified in the Unit Description and is not eligible for any other form of supplementary assessment |
| Course Level: |
| Level of Unit in Course | AQF Level(s) of Course | | 5 | 6 | 7 | 8 | 9 | 10 | | Introductory | | | | |  | | | Intermediate | | | | | | | | Advanced | | | | | | |
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| Learning Outcomes: |
| Knowledge: |
| K1. | Explain shaft sinking and tunnelling by drilling and blasting method. |
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| K2. | Describe mechanised tunnelling method. |
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| K3. | Identify sensoring technologies for engineering application. |
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| K4. | Observe engineering applications of robots. |
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| K5. | Recognise engineering applications of data analytics. |
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| K6. | Review engineering applications of artificial intelligence. |
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| Skills: |
| S1. | Select appropriate tunnelling method for applications in mining and civil engineering. |
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| S2. | Analyse tunnelling projects and provide solutions to complex underground tunnelling problems. |
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| S3. | Investigate emerging technologies for engineering applications to improve performance, including, but not limited to, new tunnelling technologies, sensor technologies, industrial robots, data analytics and artificial intelligence. |
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| Application of knowledge and skills: |
| A1. | Evaluate, plan, and implement a tunnelling system for a project. |
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| A2. | Apply emerging technologies for engineering applications to improve performance, including, but not limited to, new tunnelling technologies, sensor technologies, industrial robots, data analytics and artificial intelligence. |
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| Unit Content: |
Topics may include:
1. Tunnelling by drilling and blasting.
2. Mechanised tunnelling.
3. Sensor technologies.
4. Industrial robots.
5. Data analytics.
6. Artificial intelligence. |
| Graduate Attributes: |
| | Learning Outcomes Assessed | Assessment Tasks | Assessment Type | Weighting | | 1. | K1, K2, S1, S2, S3, A1 | Numerical and conceptual tasks | assignments | 15-30% | | 2. | K3, K4, K5, K6, A2 | Up to three projects covering tunnelling technologies, sensor technologies, industrial robots, data analytics or artificial intelligence, or other emerging technologies specified by the unit coordinator. | reports | 70-85% |
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