MJRP-IENGM v.1 Industrial Engineering Major (MSc Science)
Major/Stream Overview
This major/stream is part of a larger course. Information is specific to the major/stream, please refer to the course for more information.
This major provides tools for the quantitative evaluation of alternative policies, plans and decisions. Nationally, demand for graduates comes from government departments (agriculture, Forest Products Commission, treasury, transport and infrastructure, minerals and energy, and health), government agencies (CSIRO, DSTO) and industries such as mining and petroleum, banking, communications, defence, transport and logistics and manufacturing.
Major/Minor/Stream Organisation
Major/Stream Learning Outcomes
A graduate of this course can:
1. the skills necessary to pursue research into developing models and techniques for difficult industry problems for whichavailable methods are either not applicable or else are computationally intractable
2. a clear and concise understanding of the principles and techniques that can be applied to modelling and optimising a range of industrial systems
3. a suite of optimisation tools that can be applied to generate a range of accurate and robust outputs that assist management in developing effective strategic, tactical and operational plans
4. communicate effectively in language appropriate to the discipline of Industrial Modelling & Optimisation in both the oral and written word through the production of a large and detailed project report
5. an appreciation of the contribution that modelling and optimisation technology can provide to improve the quality, efficiency and productivity of industry; use established and emerging technologies and applies them appropriately within the field of Industrial Modelling and Optimisation
6. demonstrate an ability to be self-motivated and self-directed lifelong learners, keeping up to date with recent developments in the discipline
7. understand and appreciate the global nature and impact of industrial modelling and optimisation and the international standards of practice that are relevant to their profession
8. appreciate the importance of cultural diversity and individual human rights and how these impact on their profession; work both as an independent professional and within teams, either as a leader or a collaborator, using effective problem solving and decision making skills in an ethical manner
9. experience in a significant industry focussed R&D project
Course Organisation Note
This major is prescriptive and electives are not available. It is expected that students enrolling in this major will not need to undertake preparatory units.
| Course Structure | Hrs/Wk | Credit | |||
|---|---|---|---|---|---|
| Year 1 Semester 1 | |||||
| NPSC5000 | v.1 | Science Masters Research Methodologies | 3.0 | 25.0 | |
| STAT5008 | v.1 | Mathematical Statistics | 4.0 | 25.0 | |
| OR | |||||
| MATH5006 | v.1 | Numerical Methods | 3.0 | 25.0 | |
| INDE5000 | v.1 | Supply Chain Modelling and Optimisation | 4.0 | 25.0 | |
| SELECT ELECTIVE UNITS TO THE TOTAL VALUE OF: | 25.0 | ||||
| 100.0 | |||||
| Year 1 Semester 2 | |||||
| MATH5004 | v.1 | Advanced Numerical Analysis | 3.0 | 25.0 | |
| OR | |||||
| MATH5005 | v.1 | Applied Mathematics Topics | 4.0 | 25.0 | |
| SELECT OPTIONAL UNITS TO THE TOTAL VALUE OF: | 75.0 | ||||
| 100.0 | |||||
| Year 2 Semester 1 | |||||
| INDE6001 | v.1 | Industrial Modelling and Optimisation | 4.0 | 25.0 | |
| INDE6002 | v.1 | Network Optimisation for Transport and Logistics | 4.0 | 25.0 | |
| MATH6004 | v.1 | Industrial Engineering Masters Project | 8.0 | 50.0 | |
| 100.0 | |||||
| Year 2 Semester 2 | |||||
| INDE6000 | v.1 | Production Planning and Management | 4.0 | 25.0 | |
| INDE6003 | v.1 | Logistics and Supply Chain Optimisation | 4.0 | 25.0 | |
| MATH6001 | v.1 | Mathematics Masters Project 3 | 8.0 | 50.0 | |
| 100.0 | |||||
| Optional Units to Select from in Year 1 Semester 2 | Hrs/Wk | Credit | |||
| MATH2011 | v.1 | Operations Research | 4.0 | 25.0 | |
| STAT5006 | v.1 | Statistical Data Analysis 1 | 3.0 | 12.5 | |
| STAT5001 | v.1 | Statistical Probability | 3.0 | 12.5 | |
| MATH4002 | v.1 | Advanced Topics in Optimisation | 3.0 | 25.0 | |
| ISAD5000 | v.1 | Advanced Optimisation Techniques | 4.0 | 25.0 | |
| MATH2000 | v.1 | Network Optimisation | 4.0 | 25.0 | |
| INDE2001 | v.1 | Logistics Modelling and Optimisation | 4.0 | 25.0 | |
| INDE3002 | v.1 | Dynamic and Stochastic Modelling and Optimisation | 4.0 | 25.0 | |
* Students may only take 100 credits of undergrduate units. CRL for undergraduate units will not be permitted.
Handbook
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