Learning Outcomes:

1. Relate the theory of decision analysis to decision making in engineering operations.
2. Demonstrate the application of quantitative tools and techniques to enable decision making in engineering operations environments.
3. Critique the results of decisions made with a view to improving engineering management decision making competency.
4. Apply both oral and written communication through continuous in-class discussions and written reports.
5. Assess published academic and practitioner research related to decision analysis to support in-class discussions and written reports.

Indicative Module Content:

Topics include:-
Introduction to quantitative decision making, modelling, simulation, underlying theory and concepts.

Problem identification, solution formulation, verification and validation.

Decision analysis, decision making with probabilities, decision trees. Spreadsheet computational tools, Linear and Non Linear Programming, Solver, Software packages for simulation.

Development of discrete event simulation models using manual techniques, Excel spreadsheets, Excel Monte Carlo methods and also the Extend simulation software package.

Use of probability distributions including empirical, normal, exponential, beta, triangular, etc.. Analysis of expected values and model outcomes. Queuing Theory, Reliability Theory.

Applications from sectors including service, industrial, manufacturing and financial.

Student Effort Type	Hours
Specified Learning Activities	24
Autonomous Student Learning	72
Lectures	24
Total	120

Learning Recommendations:

This is a core module on the Master of Engineering Management and the Professional Diploma in Operations Excellence programmes. It is designed for postgraduate students based in industry and who have at least two to five years professional engineering work experience.

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Additional Information:
This module is designed for postgraduate students based in industry and who have at least two to five years professional engineering experience.

Equivalents:
Decision Analysis (EEME40170)


 

Assessment Strategy  

Description	Timing		Component Scale		% of Final Grade
Project: Industry Based Decision Analysis Application	Week 10	n/a	Graded	No	25
Journal: Group Simulation Journal	Coursework (End of Trimester)	n/a	Graded	No	50
Presentation: Industry Based Application	Week 10	n/a	Graded	No	25

 

Resit In	Terminal Exam
Spring	No

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

Not yet recorded.

The module will use the following two texts:
"Decision Analysis for Management Judgment”, Paul Goodwin and George Wright, 5th Edition, publisher Wiley.
"Practical Management Science", Wayne Winston & S. Christian Albright, 6th edition, publisher Cengage Learning.

As an alternative to the "Practical Management Science" text , students are referred to the following 3 texts:
“Business Analytics – Data Analysis and Decision Making”, S. Christian Albright & Wayne Winston, 6th edition, publisher Cengage Learning.
“Management Science – The Art of Modeling with Spreadsheets”, Stephen Powell & Kenneth Baker, 1st – 4th editions, publisher Wiley.
“Analytics for Managers with Excel”, Peter C. Bell & Gregory S. Zaric, publisher Routledge (Taylor & Francis).

Other Decision Analysis reference texts are:
“Decision Making Under Uncertainty with RISKOptimizer – A Step by Step Guide Using Palisade’s RISKOptimizer for Excel”, by Wayne Winston, 2nd edition, publisher Palisade Corporation.
"Introduction to Management Science – A Modeling and Case Studies Approach with Spreadsheets", Frederick Hillier & Mark Hillier, 5th edition, publisher McGraw Hill International.
“Making Hard Decisions”, Robert Clemen & Terence Reilly, 1st/2nd/3rd editions, publisher Cengage Learning.
“Decision Making Under Uncertainty”, David E Bell & Arthur Schleifer, publisher Cengage Learning
“Handbook of Decision Analysis”, Gregory Parnell, Terry Bresnick, Steven Tani, Eric Johnson, publisher Wiley.

Name	Role
Dr Pezhman Ghadimi	Lecturer / Co-Lecturer

Autumn
Lecture	Offering 1	Week(s) - 1, 4, 8, 12	Fri 12:00 - 13:50
Lecture	Offering 1	Week(s) - 2, 3, 5, 6, 9, 10, 11	Fri 15:00 - 16:50
Autumn