Learning outcome
1.1

1.1 Systematic, theory based understanding of the underpinning natural and physical sciences and the engineering fundamentals applicable to the technology domain.
1.2

1.2 Conceptual understanding of the, mathematics, numerical analysis, statistics, and computer and information sciences which underpin the technology domain.
1.3

1.3 In depth understanding of specialist bodies of knowledge within the technology domain.
1.4

1.4 Discernment of knowledge development within the technology domain.
1.5

1.5 Knowledge of contextual factors impacting the technology domain.
1.6

1.6 Understanding of the scope, principles, norms, accountabilities and bounds of contemporary engineering practice in the technology domain.
2.1

2.1 Application of established engineering methods to broadly defined problem solving within the technology domain.
2.2

2.2 Application of engineering techniques, tools and resources within the technology domain.
2.3

2.3 Application of systematic synthesis and design processes within the technology domain.
2.4

2.4 Application of systematic approaches to the conduct and management of projects within the technology domain.
3.1

3.1 Ethical conduct and professional accountability.
3.2

3.2 Effective oral and written communication in professional and lay domains.
3.3

3.3 Creative, innovative and pro-active demeanour.
3.4

3.4 Professional use and management of information.
3.5

3.5 Orderly management of self, and professional conduct.
3.6

3.6 Effective team membership and team leadership.
A1

<p>Identify opportunities for improvement using reliability engineering techniques and analysing maintenance and asset performance data.</p>
A2

<p>Construct models and apply reliability engineering and statistical techniques to optimise maintenance decisions.</p>
K1

<p>Interpret systems drawing, quantitative risk analysis, event trees and fault tree analysis.</p>
K2

<p>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.</p>
K3

<p>Provide comprehensive overviews of reliability related statistical processes.</p>
K4

<p>Classify and annotate maintenance decision models.</p>
S1

<p>Analyse asset maintenance and asset performance data to conduct quantitative risk analyses.</p>
S2

<p>Develop models to analyse asset management options and recommend decisions based on maintenance optimisation techniques.</p>