Introductory description

Simulation of Operations

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

1. Fundamental theory of discrete-event simulation.
2. Setting objectives for the simulation (formal planning, shop loading, optimisation).
3. Data collection and verification; data collection from existing plant operations;
4. Methods of estimating in the common case of incomplete data; synthetic data for a new simulation.
5. Choice of the system for simulation; criteria: technological aspects, simulation objectives.
6. Types of simulation software and their best areas of application.
7. Planning and executing a simulation; programming and cross-checking validity of the model; model running; sensitivity analysis; output format.

Learning outcomes

By the end of the module, students should be able to:

• Demonstrate an advanced ability to present the results of a simulation study in written form, and make evidence-based recommendations based on this.(M3,M4,M17)
• Analyse experimental results using appropriate structured and statistical methods to critically evaluate engineering proposals. (M1,M2,M3,M6)
• Demonstrate in depth knowledge and skills to allow a new or existing facility and its operation to be simulated using discrete event simulation.(M5,M6)
• Demonstrate an in-depth understanding of DES theory and make suitable simplifications of a problem to suit DES technologies.(M4)
• Make appropriate modelling simplifications (choice of variable, level of detail, degree of abstraction)(M2,M13)
• Design and execute an appropriate set of experiments using a simulation model.(M2,M3,M13)

Indicative reading list

Simulation Modeling & Analysis, Law A., McGraw-Hill. 5th edition 2014
Computer Simulation in Management Science, Pidd M., Wiley. 5th edition, 2004.
Simulation: The practice of model development and use. Robinson S., Palgrave Macmillan. 2nd edition 2014.

View reading list on Talis Aspire

Subject specific skills

Ability to conceive, make and realise a component, product, system or process
Ability to be pragmatic, taking a systematic approach and the logical and practical steps necessary for, often complex, concepts to become reality
Including these specific skills:
Ability to conceive, make and realise a simulation model using commercial software
Ability to design and conduct valid experiments within a time constraint
Ability to make pragmatic choices to develop useful models by oneself within a time constraint
Ability to consider the risks associated with building models with limited data

Transferable skills

Numeracy: apply mathematical and computational methods to communicate parameters, model and optimize solutions
Apply problem solving skills, information retrieval, and the effective use of general IT facilities
Communicate with technical and non-technical audiences and work with others
Plan self-learning and improve performance, as the foundation for lifelong learning/CPD
Exercise initiative and personal responsibility, including time management.
Overcome difficulties by employing skills, knowledge and understanding in a flexible manner

Including these specific transferable skills:
Computer literacy at an advanced level, including some programming skills
Experience in developing computer-based skills from within own resources by self-paced learning.
Managing time in an uncertain data environment
Presenting technical work to non-technical clients