Full Title System Simulation Modelling and Analysis

Short Title System Simulation Modelling

Code QLTY09031
Level 09
Credit 05

Author DONOVAN, JOHN
Department Mech. and Electronic Eng.

Subject Area Quality
Attendence N/A%
Fee

Description
Provides a comprehensive and practical treatment of all the important aspects of a simulation study, including modeling, simulation software, model verification and validation, input modeling, random number generators, generating random variates, statistical design and the analysis of a simulation study

Indicative Syllabus
Basic simulation modelling

Introduction to Simulation. When is simulation appropriate. When is simulation not appropriate. Advantage and disadvantages of simulation. Areas of application. Components of a system. Discrete event and continuous simulation.

Simulation Examples

Illustration of general area of application. For example, simulation of a queueing system.

Spreadsheet Modelling

Developing a spreadsheet model. Concepts. Use of Solver. Optimisation modelling. Sensitivity analysis. Simulation of an Inventory system. Lead-time simulation. Supply chain and outsourcing simulation. Warranty model simulation.

Simulation Principles

Dynamic and stochastic systems. Concepts in discrete event simulation. Developing a discrete event model.

Simulation Software

Comparison of simulation packages with programming languages. Classification of simulation software. Desirable software features. General-purpose simulation packages. Object oriented simulation. Trends in simulation software. Focus on SIMUL8 and @Risk (Excel add-on).

Statistical Models in Simulation

Review of basic probability and statistical distributions. Discrete distributions. Continuous distributions. Empirical distributions. Models for arrival processes e.g. Poisson process.

Queueing Models

Characteristics of queueing systems. Queueing notation. Little's formula. Long run measures of performance of queueing systems. Server utilisation. Spreadsheet queueing simulation models.

Random Number Generators

Properties. Generation of pseudo-random numbers. Techniques for Generating random numbers. Linear congruential method. Combined linear congruential generators. Tests for random number.

Generating Random Variates

General programming methods for generating random variates. Inverse transform technique. Convolution method. Acceptance-Rejection method.

Input Modelling

Developing a useful model of input data. Collecting data, Identifying a probability distribution, parameter estimation, Goodness of fit testing. Selecting input models without data.

Model Verification and Validation

Verification of simulation models. Calibration and validation of models. Face validity. Validation of model assumptions. Input-output validation.

Output Analysis

Examination of data generated by simulation. Stochastic nature of output data. Output analysis for a single model. Measures of performance and their estimation. Comparing alternative system configurations.

Learning Outcomes
On completion of this module the learner will/should be able to
  1. Describe the fundamentals of simulation and the techniques for developing simulation models.

  2. Use simulation as a decision support tool.

  3. Translate a business problem into a simulation model.

  4. Formulate an appropriate and correct discrete event simulation model of a system at an appropriate level of detail.

  5. Use an Excel spreadsheet with add-ins, e.g. @Risk, to build simulation models.

  6. Use SIMUL8 to model and solve a simulation problem.

  7. Identify the best probability distribution to describe the outcomes of a random variable.

  8. Generate random variates for discrete and continuous distributions.

  9. Analyse and interpret the results of a simulation model for making a business decision.


Assessment Strategies
Continuous Assessment

1. Project work - Design and analyse ones own Simulation 20%.

Final Examination

1. One written 2.5 hour paper 40%

2. One computer based 2.5 hour exam involving @Risk & Simul8 40%

Module Dependencies
Pre Requisite Modules
None
Co Requisite Modules
None
Incompatible Modules
None

Coursework Assessment Breakdown %
Course Work / Continuous Assessment 20 %
End of Semester / Year Formal Examination 80 %

Coursework Assessment Breakdown

Description Outcome Assessed % of Total Assessment Week
Project Design and analyse own simulation 1,2,3,4,5,6,7,8,9 20 Any


End Exam Assessment Breakdown

Description Outcome Assessed % of Total Assessment Week
Final Exam One written 2.5 hour paper and one 2.5 hour practical exam 1,2,3,4,5,6,7,8,9 80 End of Term


Distance Learning Mode Workload

Type Location Description Hours Frequency Avg Weekly Workload

Total Average Weekly Learner Workload 0.00 Hours

Part Time Mode Workload

Type Location Description Hours Frequency Avg Weekly Workload
Lecture Distance Learning Suite Lecture 3 Weekly 3.00
Independent Learning UNKNOWN Independent Learning 4 Weekly 4.00

Total Average Weekly Learner Workload 3.00 Hours

Full Time Mode Workload

Type Location Description Hours Frequency Avg Weekly Workload
Lecture Not Specified Lecture 3 Weekly 3.00
Independent Learning UNKNOWN Independent Learning 4 Weekly 4.00

Total Average Weekly Learner Workload 3.00 Hours

Online Learning Mode Workload

Type Location Description Hours Frequency Avg Weekly Workload

Total Average Weekly Learner Workload 0.00 Hours

Resources
Book Resources
Authors

Title

Publishers

Year

Robinson, S.,

Simulation - The Practice of Model Development and Use

John Wiley & Sons

2004

Banks, J., Carson, J.S., Nelson, B. & Nicol, D.

Discrete-Event System Simulation, 5 th Edition

Prentice Hall

2010

Law, A.M. & Kelton, W.D.

Simulation Modelling & Analysis, 4 th Edition

McGraw-Hill

2006

Ross, S.

Simulation, 5 th Edition,

Academic Press

2012

Winston, W. & Albright, S.C.

Practical Management Science: Spreadsheet Modeling and Applications, 3 rd Edition

South Western College Publishing

2008
Other Resources
None
Url Resources
Additional Info