The Higher Canadian Institute for Business
and Engineering Technology
Quality Assurance Unit
Course Specification
Course Name: Manufacturing & Services Systems Simulation
Course Code: IEN 442
I. Basic Course Information
Major or minor element of program Industrial Engineering
Department offering the course: Mechanical Engineering
Academic level: 3rd level
Semester in which course is offered : Spring
Course pre-requisite(s): Mathematics 3 (BAS 111)
Credit Hours: 3.0
Contact Hours Through:
Lecture
2.0
Tutorial*
2.0
Practical*
1.0
Total
5.0
Approval date of course specification: January 2015
II. Overall Aims of Course
Introduction to Modelling and Simulation concepts, inputs and related ideas, purposes
of simulation, advantages and disadvantages to Simulation, common mistakes in
simulation, building a simulation model, basic simulation methodology. Monte Carlo
Simulation Method: Introduction to Monte Carlo, steps of Monte Carlo Simulation,
Hit- Or - Miss Monte Carlo Method. Generation of Random Numbers: Definition of
random numbers, needs for random numbers, characteristics of a good random
numbers, sources of random numbers, random numbers generation methods.
Generating Random Variables: Introduction, inverse transformation method, sampling
from discrete probability distributions, sampling from continuous probability
distribution, acceptance – rejection method an empirical probability distribution.
Queuing Theory and Model Translation: Introduction, System specifications, sources
for input data, derivation of steady – state probabilities, model translation. Analyzing
Input Data and tests: Goodness of fit tests, randomness test, and nonparametric test
implementation. Verification: Introduction, divide – conquer approach, animation,
advancing the simulation clock event, writing to an output file. Verification:
Introduction, assumption, simplifications. Oversights, limitations, need for validation,
types of validation. Simulation Software: Introduction, Simulation Packages and
Simulation Software: Desirable Software features, general purpose simulation
packages, Arena Practice.
1
The Higher Canadian Institute for Business
and Engineering Technology
Quality Assurance Unit
Course Specification
III. Program ILOs covered by course
Program Intended Learning Outcomes (By Code)
Knowledge &
Intellectual Skills
Professional Skills
Understanding
K.14/K.20
I.1/I.2
General
Skills
P.2
G.f
IV. Intended Learning Outcomes of Course (ILOs)
a. Knowledge and Understanding
On completing the course, students should be able to:
k. 1 the constrains within Introduction to Modelling and Simulation concepts,
inputs and related ideas, purposes of simulation
k. 2 Practice building a simulation model, basic simulation methodology
appropriate to engineering industry
b. Intellectual/Cognitive Skills
On completing the course, students should be able to:
i.1 Select appropriate methods generating Random Variables: Introduction,
inverse transformation method, sampling from discrete probability
distributions
i.2 Select appropriate solution for sampling from continuous probability
distribution, acceptance – rejection method an empirical probability
distribution
c. Practical/Professional Skills
On completing the course, students should be able to:
p.1 The engineering knowledge and understanding of Queuing Theory and Model
Translation: Introduction, System specifications, sources for input data,
derivation of steady – state probabilities, model translation
d. General and Transferable Skills
On completing the course, students should be able to:
g.1 Effectively manage of the Modelling and Simulation concepts
V. Course Matrix Contents
Main Topics / Chapters
Duration
(Weeks)
Course ILOs Covered by Topic
(By ILO Code)
K&U
I.S.
P.S.
G.S.
- Introduction to Modelling
and Simulation concepts,
inputs and related ideas,
purposes of simulation
advantages and disadvantages
2to Simulation, common
1-
1
K.1
I.1
P.1
G.1
1
K.2
I.2
P.1
G.1
2
The Higher Canadian Institute for Business
and Engineering Technology
Quality Assurance Unit
Course Specification
3-
4-
5-
6-
7-
8-
9-
10-
11-
1213-
mistakes in simulation,
building a simulation model,
basic simulation methodology
Monte Carlo Simulation
Method: Introduction to
Monte Carlo, steps of Monte
Carlo Simulation, Hit- Or Miss Monte Carlo Method.
Generation of Random
Numbers: Definition of
random numbers, needs for
random numbers
characteristics of a good
random numbers, sources of
random numbers, random
numbers generation methods
Generating Random
Variables: Introduction,
inverse transformation
method, sampling from
discrete probability
distributions
sampling from continuous
probability distribution,
acceptance – rejection
method an empirical
probability distribution
Queuing Theory and Model
Translation: Introduction,
System specifications,
sources for input data,
derivation of steady – state
probabilities, model
translation
Analyzing Input Data and
tests: Goodness of fit tests,
randomness test, and
nonparametric test
implementation. Verification
divide – conquer approach,
animation, advancing the
simulation clock event,
writing to an output file
Verification: Introduction,
assumption, simplifications.
Oversights, limitations, need
for validation, types of
validation.
1
K.1
I.1
P.1
G.1
1
K.2
I.2
P.1
G.1
1
K.1
I.1
P.1
G.1
1
K.2
I.2
P.1
G.1
1
K.1
I.1
P.1
G.1
1
K.2
I.2
P.1
G.1
1
K.1
I.1
P.1
G.1
1
K.2
I.2
P.1
G.1
1
K.1
I.1
P.1
G.1
1
K.2
I.2
P.1
G.1
1
K.1
I.1
P.1
G.1
3
The Higher Canadian Institute for Business
and Engineering Technology
Quality Assurance Unit
Course Specification
Simulation Software:
Introduction, Simulation
Packages and Simulation
14- Software: Desirable Software
features, general purpose
simulation packages, Arena
Practice.
Net Teaching Weeks
1
K.2
I.2
P.1
G.1
14
VI. Course Weekly Detailed Topics / hours / ILOs
Week
No.
Sub-Topics
Total
Hours
Contact Hours
Theoretical
Practical
Hours
Hours*
- Introduction to Modelling and Simulation
1
2
3
4
5
6
7
8
9
10
11
2
concepts, inputs and related ideas, purposes
of simulation
advantages and disadvantages to
Simulation, common mistakes in
5
simulation,
building a simulation model, basic
5
simulation methodology
Monte Carlo Simulation Method:
Introduction to Monte Carlo, steps of Monte
5
Carlo Simulation, Hit- Or - Miss Monte
Carlo Method.
Generation of Random Numbers: Definition
of random numbers, needs for random
5
numbers
characteristics of a good random numbers,
sources of random numbers, random
5
numbers generation methods
Midterm Exam
Generating Random Variables:
Introduction, inverse transformation
5
method, sampling from discrete probability
distributions
sampling from continuous probability
distribution, acceptance – rejection method
5
an empirical probability distribution
Queuing Theory and Model Translation:
Introduction, System specifications, sources
5
for input data, derivation of steady – state
probabilities, model translation
Analyzing Input Data and tests: Goodness
of fit tests, randomness test, and
5
nonparametric test implementation.
Verification: Introduction
2
2
3
2
3
2
3
2
3
2
3
2
3
2
3
2
3
2
3
4
The Higher Canadian Institute for Business
and Engineering Technology
Quality Assurance Unit
Course Specification
12
13
14
15
divide – conquer approach, animation,
advancing the simulation clock event,
writing to an output file
Verification: Introduction, assumption,
simplifications.
Oversights, limitations, need for validation,
types of validation.
Final Exam
Total Teaching Hours
5
2
3
5
2
3
5
2
3
62
26
36
Teaching/Learning
Method
Lectures & Seminars
Tutorials
Computer lab Sessions
Practical lab Work
Reading Materials
Web-site Searches
Research & Reporting
Problem Solving /
Problem-based Learning
Projects
Independent Work
Group Work
Case Studies
Presentations
Simulation Analysis
Others (Specify):
Selected
Method
VII. Teaching and Learning Methods
Course ILOs Covered by Method (By ILO Code)
1
1
K.1/K.2
K.1/K.2
Intellectual
Skills
I.1/I.2
I.1/I.2
1
K.1
I.1
K&U
Professional
Skills
P.1
P.1
General
Skills
G.1
G.1
P.1
G.1
Assessment
Weight /
Percentage
Week
No.
Selected
Method
VIII. Assessment Methods, Schedule and Grade Distribution
Course ILOs Covered by Method
(By ILO Code)
Assessment
Method
K&U
I.S.
P.S.
G.S.
Midterm Exam
Final Exam
Quizzes
Course Work
Report Writing
Case Study
Analysis
Oral
Presentations
7
15
1
K.1
K.1/K.2
K.1/K.2
I.1
I.1/I.2
I.1/I.2
P.1
P.1
P.1
G.1
G.1
G.1
5
The Higher Canadian Institute for Business
and Engineering Technology
Quality Assurance Unit
Course Specification
Practical
Group Project
Individual
Project
Others (Specify):
IX. List of References
Essential Text Books

Course notes

Recommended books 
Periodicals, Web sites, 
etc …
Law, A. M. & Kelton, W. D., Simulation Modeling and Analysis,
McGraw Hill, 3 rd. Ed., 2000
Lectures
X. Facilities required for teaching and learning
 White Board
Course coordinator: Dr. Mervat Badr
Head of Department: Dr .Mahmoud Mohamed
Date: January 2015
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