STRP-ASMPR v.2 Asset Management and Productivity Stream
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.
The Asset Management and Productivity (AMP) Stream offers students the opportunity to develop the skills necessary to meet the 21st Century business challenges in asset management and maintenance. The emergence of “big data” means that a huge amount of information is available to managers about the condition and performance of a company’s assets. This allows managers to drive asset productivity through enhanced maintenance planning, for example, but requires seamless integration of computer programming, statistics and business processes.
Major/Minor/Stream Organisation
Major/Stream Learning Outcomes
A graduate of this course can:
1. use research to apply an understanding of the theoretical background basis of data analytics and to allow the data processing of unstructured data, including all aspects of cluster analysis to produce a qualified interpretation of the data
2. analyse an unstructured data set or problem in a logical, rational and critical way; identify alternative methods of solving the issue and select the optimum solution that provides the best outcomes for both industry and the community
3. obtain, evaluate and apply relevant processing algorithms to unstructured data from a range of sources to solve or predict an operational problem prior to or during an occurrence
4. communicate effectively with a wide range of people from different discipline areas, professional positions and countries; communicate data analysis findings in a variety of ways via written, verbal or electronic communications
5. evaluate and utilise appropriate technology for the implementation of data analysis and prediction developments and the continual operational improvement of data generating systems throughout their lifecycle
6. appreciate the need for, and develop, a lifelong learning skills strategy in relation to enhanced personal and company performance
7. recognise the global nature of the predictive analytics industry and apply global standard practices and skills for acceptable prediction outcomes regardless of discipline or geographical location
8. practise appropriate industry data collection methodologies; work and apply discipline knowledge within the given social or industrial framework; with consideration of and respect for cultural diversity, indigenous perspectives and individual human rights
9. apply lessons learnt in a professional manner in all areas of prediction design, demonstrating leadership and ethical behaviour at all times
Duration and Availability
This Stream is one year full-time or equivalent part-time study.
| Course Structure | Hrs/Wk | Credit | |||
|---|---|---|---|---|---|
| Year 2 Semester 1 | |||||
| MGMT6049 | v.1 | Strategic Operations Management | 3.0 | 25.0 | |
| MGMT6035 | v.1 | Strategic Project Management | 3.0 | 25.0 | |
| OR | |||||
| PRRE5008 | v.1 | Systems Control and Remote Operations | 2.0 | 25.0 | |
| MGMT6019 | v.1 | Supply Chain Planning and Design | 3.0 | 25.0 | |
| COMM5000 | v.2 | Risk Assessment and Strategies | 3.0 | 25.0 | |
| 100.0 | |||||
| Year 2 Semester 2 | |||||
| COMM5001 | v.2 | Asset Management and Maintenance | 3.0 | 25.0 | |
| COMM5002 | v.2 | Asset Management and Productivity Research Project | 15.0 | 50.0 | |
| SELECT OPTIONAL UNITS TO THE TOTAL VALUE OF: | 25.0 | ||||
| 100.0 | |||||
| Optional Units to Select from in Year 2 Semester 2 | Hrs/Wk | Credit | |||
| LAWS5001 | v.1 | Legal Framework for Managers | 3.0 | 25.0 | |
| MGMT5015 | v.1 | Leadership in a Dynamic Global Environment | 3.0 | 25.0 | |
| MGMT5024 | v.1 | Organisational Change and Development | 4.0 | 25.0 | |
| MGMT6036 | v.1 | Fundamentals of Leadership | 3.0 | 25.0 | |
| MGMT6039 | v.1 | Human Resource Strategies | 3.0 | 25.0 | |
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