QLTY09031 2013 System Simulation Modelling and Analysis

General Details

Full Title
System Simulation Modelling and Analysis
Transcript Title
System Simulation Modelling
Code
QLTY09031
Attendance
N/A %
Subject Area
QLTY - Quality
Department
MENG - Mech. and Electronic Eng.
Level
09 - NFQ Level 9
Credit
05 - 05 Credits
Duration
Semester
Fee
Start Term
2013 - Full Academic Year 2013-14
End Term
2019 - Full Academic Year 2019-20
Author(s)
JOHN DONOVAN
Programme Membership
SG_EPROJ_M09 201300 Master of Science in Project Management SG_SPROJ_O09 201700 Postgraduate Diploma in Science in Project Management
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

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.

Teaching and Learning Strategies

Real world examples, case studies and published peer reviewed papers will be utilised, where possible.

Module 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%

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.

Coursework & Assessment Breakdown

Coursework & Continuous Assessment
20 %
End of Semester / Year Formal Exam
80 %

Coursework Assessment

Title Type Form Percent Week Learning Outcomes Assessed
1 Project Design and analyse own simulation Continuous Assessment UNKNOWN 20 % Any 1,2,3,4,5,6,7,8,9
             
             

End of Semester / Year Assessment

Title Type Form Percent Week Learning Outcomes Assessed
1 Final Exam One written 2.5 hour paper and one 2.5 hour practical exam Final Exam UNKNOWN 80 % End of Term 1,2,3,4,5,6,7,8,9
             
             

Full Time Mode Workload


Type Location Description Hours Frequency Avg Workload
Lecture Not Specified Lecture 3 Weekly 3.00
Independent Learning UNKNOWN Independent Learning 4 Weekly 4.00
Total Full Time Average Weekly Learner Contact Time 3.00 Hours

Part Time Mode Workload


Type Location Description Hours Frequency Avg Workload
Lecture Distance Learning Suite Lecture 3 Weekly 3.00
Independent Learning UNKNOWN Independent Learning 4 Weekly 4.00
Total Part Time Average Weekly Learner Contact Time 3.00 Hours

Module Resources

Non ISBN Literary 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, 5th Edition

Prentice Hall

2010

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

Simulation Modelling & Analysis, 4th Edition

McGraw-Hill

2006

Ross, S.

Simulation, 5th Edition,

Academic Press

2012

Winston, W. & Albright, S.C.

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

South Western College Publishing

2008

Other Resources

None

Additional Information

None