Advanced Aerospace Engineering Management

Learning Outcomes

Subject Specific Practical Skills

Having successfully completed this module you will be able to:

• Manage uncertainty within a project management context [M9, M15]
• Model, manage and optimise for the reliability/uncertainty of an engineering system [M7, M14]

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

• Explain the working principles behind the methods covered throughout the module and appreciate their strengths and limitations [M2,M3]
• Interpret the results of a model predicting reliability or uncertainty [M9]

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

• The importance of risk and security within engineering [M9, M10, M15]
• The role of inclusivity and diversity within engineering [M5, M8, M11]
• Ethical practice within engineering [M5, M8]

Statistical Fundamentals for Management

• Probability theory, rules & notation, sequence trees, Bayes’ Theorem
• Single & multi-variate PDFs and CDFs
• Statistical model fitting, method of moments, least squares & maximum likelihood estimation (censored & uncensored)
• Monte Carlo & Quasi-Monte Carlo analysis

Systems Reliability Modelling

• Series, parallel, m-out-of-n systems, m-out-of-n consecutive and balanced systems
• Reliability block diagram analysis
• Block diagram decomposition
• Active & inactive redundancy
• Multistate models
• Optimal component assignment
• Determining component importance
• Fault tree analysis
• Competing risk models
• Load sharing systems
• Optimal maintenance scheduling

Management of Uncertainty, Risk & Security

• Business continuity planning
• Project risk modelling & management
• Supply chain uncertainty and management
• Task scheduling & resource planning
• Designing for reliability (inc. FMEA)
• Designing in the presence of uncertainty / robust design
• Robust regularisation, aggregation & randomised techniques for robust design
• Taguchi methods
• Cyber security
• Intellectual property management & export control
• Concurrent & collaborative design processes

Engineering Ethics & Inclusivity

• Ethical practice including, accuracy & rigour, honesty & integrity, responsible leadership and respect for life, law and the public good
• Case studies in engineering ethics
• Diversity & inclusion
• Design for inclusivity

Teaching and learning methods

The module features a series of lectures covering the above syllabus in addition to tutorials covering worked examples, real world case studies and guest lectures. Background reading, pre-recorded material and self-study complement the face-to-face elements of the module.

Assessment strategy

(Summative) Assessment Method:

• Coursework 20%
• Examination 80%

(Referral) Assessment Method:

• Examination 100%

External Repeat Assessment Method:

• Examination 100%

Summative

This is how we’ll formally assess what you have learned in this module.

Repeat Information

Repeat type: Internal & External