Registry

Module Specifications

Current Academic Year 2012 - 2013
Please note that this information is subject to change.

Module Title	Manufacturing Systems Simulation
Module Code	MM584
School	School of Mechanical and Manufacturing Engineering
Online Module Resources
Module Co-ordinator	Semester 1: John Geraghty Semester 2: John Geraghty Autumn: John Geraghty
Module Teacher	John Geraghty
NFQ level	8	Credit Rating	7.5
Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

Description

The purpose of this module is to introduce the fundamentals of the field of engineering and scientific practice of Discrete Event Simulation. In this module students will develop knowledge and skills in developing and analysing simulation models with particular emphasis on manufacturing systems problems. Students will participate in the following learning activities: they will attend weekly lectures and laboratory, participate in assignments and present for end of semester examinationThis module can be delivered to distance learning students but may require the students to complete alternative assignments as software is not available off-campus

Learning Outcomes

1. Develop conceptual, paper based, models of manufacturing systems problems as a prior step to developing a discrete event simulation model
2. Develop a discrete event simulation model.
3. Distinguish between the concepts of model verification, validation and credibility and make recommendations on how to best accomplish each of these in a manufacturing environment
4. Assess the goodness of fit of a theoretical probability distribution to a dataset of observations
5. Analyse the outputs of discrete event simulation models to determine appropriate simulation model run lenghts, identify the warm-up period, and determine the appropriate number of runs required to achieve a desired level of confidence in the estimate of a performance measure
6. Identify and implement an appropriate variance reduction technique when designing simulation experiments
7. Analyse the output of simulation models to compare the results of two or more alternative system configurations and/or operating policies

Workload	Full-time hours per semester
*Type*	*Hours*	*Description*
Lecture	24	No Description
Lab	24	No Description
Assignment	24	Lab assignments due one week after lab (weeks 1 to 6 only)
Assignment	48	Development of a DES
Examination	38	Exam preparation and exam time
Independent learning time	29.5	preparation for lectures and labs etc, library research and reading
Total Workload: 187.5

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Types of simulation.
discrete, continuous, combined..

Stochastic simulation..
Discrete simulation.

entities, activities, events, queues, sets, states..
Overview of simulation software..

Simulation Input Data Analysis.
goodness of fit tests.

Simulation Output Analysis.
Determining the appropriate number of runs, run lenght and Warm-up period.

Variance Reduction Techniques.
the method of Common Random Numbers and the Antithetic Variates VRT.

Comparing Alternative Scenarios.
Comparing the output data from simulation models in order to determine the best alternative.

Assessment Breakdown
Continuous Assessment	50%	Examination Weight	50%

Course Work Breakdown
Type	Description	% of total	Assessment Date
Assignment	Lab assessment - due one week after lab (first 6 labs only)	30%	Week 1
Assignment	Individual Assignment - Develop a DES	20%	Week 12

Reassessment Requirement
Resit arrangements are explained by the following categories; 1 = A resit is available for all components of the module 2 = No resit is available for 100% continuous assessment module 3 = No resit is available for the continuous assessment component
This module is category 1

Indicative Reading List