| Effective Term: | 2024/05 |
| Institute / School : | Institute of Innovation, Science & Sustainability |
| Unit Title: | Quantitative Techniques for Asset Management |
| Unit ID: | MREGC5005 |
| Credit Points: | 15.00 |
| Prerequisite(s): | Nil |
| Co-requisite(s): | Nil |
| Exclusion(s): | (MREGC5101) |
| ASCED: | 039999 |
| Other Change: | |
| Brief description of the Unit |
This unit covers quantitative techniques and tools applied to asset management and risk based asset management decisions. This unit includes core topics of engineering systems, system diagrams, quantitative risk analysis techniques and reliability analysis methods (system and reliability block diagrams and hazard rate analysis for systems and components and active, parallel / standby redundancy). It also covers reliability statistics (Weibull analysis, reliability growth analysis, repairable and non-repairable systems) and maintenance optimisation models (replacement, inspections, maintenance resources requirement). |
| Grade Scheme: | Graded (HD, D, C, P, MF, F, XF) |
| Work Experience Indicator: |
| No work experience |
| Placement Component: | |
| Supplementary Assessment:No |
| Supplementary assessment is not available to students who gain a fail in this Unit. |
| 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. | Interpret systems drawing, quantitative risk analysis, event trees and fault tree analysis. |
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| K2. | Detailed and critical explanations of reliability analysis methods including system diagram, reliability block diagram, hazard rates at system & component level, MooN system, active, parallel and stand-by redundancy. |
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| K3. | Provide comprehensive overviews of reliability related statistical processes. |
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| K4. | Classify and annotate maintenance decision models. |
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| Skills: |
| S1. | Analyse asset maintenance and asset performance data to conduct quantitative risk analyses. |
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| S2. | Develop models to analyse asset management options and recommend decisions based on maintenance optimisation techniques. |
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| Application of knowledge and skills: |
| A1. | Identify opportunities for improvement using reliability engineering techniques and analysing maintenance and asset performance data. |
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| A2. | Construct models and apply reliability engineering and statistical techniques to optimise maintenance decisions. |
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| Unit Content: |
This unit covers engineering systems, system diagrams, quantitative risk analysis techniques and reliability analysis methods (system and reliability block diagrams and hazard rate analysis for systems and components and active, parallel / standby redundancy).
Engineering Systems and Quantifiable Risk Analysis.
Reliability Analysis for components and systems.
Failure data and statistical analysis for reliability.
Maintenance Optimisation Models. |
| Graduate Attributes: |
| | Learning Outcomes Assessed | Assessment Tasks | Assessment Type | Weighting | | 1. | K1-K2-K3-K4-S1-S2-A1-A2 | Analysis and report of faults using failure data. | Analysis and report | 10% - 30% | | 2. | K1-K2-K3-S1-S2-A1-A2 | Analysis of failure data for life prediction and improve reliability. | Analysis and report | 20% - 40% | | 3. | K1-K2-K3-k4-S1-S2-A1-A2 | Examination or online test | Examination or online test | 60% - 40% |
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