simulation of engineering systems

8/9/2019 Simulation of Engineering Systems

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Simulation of Engineering

SystemsDr. Ashraf S. Youssef

Industrial Engineering Dept., Fayoum University

Lecture - 1

What is simulation?

What is being modeled?

Advanta es of simulation

Different kinds of simulation and Programming


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What is Simulation? Simulation is defined as a numerical

ec n que or con uc ng exper men s on a

digital computer.

Simulation is becoming more and moreaccepted tool for design of new facilities, for

investing the operational aspects of existing

p an s an or es ng con ro s ra eg es or automated factories.

Dr. Ashraf S. Youssef


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What is being modeled?DecisionVariables

simulation dealswith models of

systems.

SYSTEM

facility or process,

either actual or

planned.Outcomes



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System examples Manufacturing plant with M/Cs, People, transport

, , .

A bank or other personal service operations.

.

A computer network with servers, client, disk drivers,

rinters, and networkin ca abilities.

A supermarket with inventory control and customer

services.

A fast-food restaurant with workers of differenttypes.



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Advantages of simulation Allows us to study systems without disturbing

, ,

huge expenses.

,

problem refine designs without incurring

actual system.

design to parameter uncertainties.


.


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Advantages of simulation (cont.) Simulation can be used to study a proposed

somewhat sketchy.

,

to solve a problem.



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What is a model? A model is an abstraction of the system.

Model Types

Physical Model Textual Model Graphical ModelMathematical

Model

Simulation of a system is a computer-base model



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Different Kinds of simulations

. .

.

Deterministic Vs. Stochastic.



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Simulation Programming

Usin eneral ur ose lan ua es Fortran,

C++, Visual Basic,etc)

Using Simulation languages (GPSS,

SIMSCRIPT, SLAM, and SIMAN)

High-Level simulators (SIMFACTORY,



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Steps in a simulation study Formulate problem and plan the study.

Collect data and define a model. Valid.

ons ruc a compu er program an ver y.

Make pilot runs.

.

Design Experiments.

Make roduction runs.

Analyze output data.

Document and implement results.



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S stems

Lecture - 2 Manual Simulation


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Example For M/M/1 Queue process, MTBA=29, and

= , es ma e e o ow ng:

AWT

erver za on

Average Queue Length.



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Solution

= - * -

ST = -2*ln(1-R)

Generate Random No. and calculate TBA,

and ST for the first 16 arrivals.

USE MS Excel



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Homework 1 Use manual simulation to calculate the

, ,

20 arrivals, and AQL if you know that the TBA

Standard deviation = 5, Service time is a

=

and max value = 30.



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S stems

Lecture - 3 Goodness-of-Fit test

Chi-Square Test

Kolmo orov-Smirnov Test


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Chi-Square Test

It is suitable for discreet

an con nuous

distributions= 1

2i

=k iExpected

xpecteserve

Calculatedf

freedom is equal to k-1-p, where p is the number of

population parameters

22

1

0

:

:

CalculatedCritical

CalculatedCritical

H

H

=



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Kolmogorov-Smirnov Test

It is suitable for continuous distributions Onl

H : K-S From table >= K-S statistics

H1:K-S From table < K-S statistics

K-S statistics is equal the maximum difference

between the cumulative frequency and the

theoretical cumulative frequency. The degrees offreedom is equal to N



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Important Rule

-

large sample size; at least 100observations.

-

have small sample size.



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Example:

Use Chi-Square test and K-S test to evaluate

the following data at

= .05: 12.36, 14.15, 6.76, 14.46, 7.47, 5.71, 16.83, 5.17,

0.03, 19.65, 16.79, 19.33, 17.46, 15.45, 16.08,

18.01, 11.99, 10.72, 11.51, 11.99, 5.12, 20.18,

. , . , . , . , . , . , . , . ,

19.41, 6.31, 6.21, 9.83, 14.66, 8.58, 15.83, 12.52,

16.39, 6.57, 8.42, 12.87, 8.03, 9.6, 5.42, 15.56,

18.04, 8.97, 17.11, 7.79, 10, 12, 16, 18, 14, 18,17, 15, 19, 13


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