Modelling & Simulation (ME0316) : Dr. Santhosh Kumar Gugulothu Assistant Professor Mechanical Engineering Department

Modelling & Simulation
(ME0316)
Dr. Santhosh Kumar Gugulothu

Assistant Professor
Mechanical Engineering Department
Topics to be Covered:
 Definition of Modeling & Simulation
 Simulation Advantages & Disadvantages
 Applications of Simulation
 System ( Discrete & Continuous systems)
 Developing Simulation model
 Why Simulation is required?
 Steps in simulation study.
 Simulation in Static System
 Classification:
a) Monte Carlo simulation method
b) Numerical
c) Estimate the value of PI
d) Calculate the area of Irregular shape
 Simulation in Dynamic System
a) Queuing System (Single Server & Multiple Server)
b) Components of Queuing System

Evaluation:

Components Date Weightage Duration
1. Mid Semester As assigned in the 20 (20%) 1.5 Hours
Theory Examination Schedule
Examinations
2. Assignments, As assigned in the class 10 (10%) Depending

Class work & from time to time upon the work
Tutorial
3. Class Test As assigned in the class 10 (10%) 50 min

from time to time
Fundamentals:
Modelling:
 Modeling is the process of representing a model which

includes its construction and working.
This model is similar to a real system, which helps the

analyst predict the effect of changes to the system.
 It is also an act of building a model.

Fundamentals:
Simulation:
 It is the process of using a model to study the

performance of a system.
 Simulation of a system is the operation of a model in

terms of time or space, which helps in analyzing the
performance of an existing or a proposed system.
 It is an act of using a model for simulation.

Fundamentals:
System:
 An object which has some action to perform and is dependent
on number of objects called entities, is considered to be a
system.
Ex: A classroom, college or University is a system
 University consists of number of colleges and college has class
rooms, students, labs and lot many other objects as entities.
Each entity has its own attributes or properties.
 For example attribute of a students is to study and work hard.
 If we combine few of these objects, joined in some regular
interactions or inter-dependence then this becomes a larger
system (Ex: University)
 System broadly can be classified into two types:
a) Static System: System doesn’t change with time.
b) Dynamic System: System changes with time.
 Components of a System:
Entity: An entity is an object of interest in a system.
Attributes: An attribute denotes the properties of an
entity.
Ex: Quantities of each order, type of part or no. of
machines in a department.
Activity: Any process causing changes in a system is
called an activity.
Ex: Manufacturing Process of the department.
 State of the system: This means a description of all the
entities, attributes and activities as they exist at one
point in time.
 Event: It defines an instantaneous occurrence that may

change the state of the system.
Bank System
Checking the Deposit money into

Customer in a account balance of the checked account
Bank(Entity) the at the specified date
customer(Attribute) & time (Activity)
No. of busy tellers, Customer, arrival,

No. of customers addition of new
waiting in a line teller & customer
(System State) departure. (Event)
System Environment:
 The external components which interact with the system and produce
necessary changes are said to constitute the system environment.
 System environment is classified into:
a) Endogenous system: If the system is not affected by the environment then it

is known as the endogenous system. It is used to describe activities and events
occurring within a system.
Ex: Drawing cash in a bank.
b) Exogenous system: If the system is affected by the environment. It is used to

describe activities and events in the environment that effect the system.
Ex: Arrival of customers

Closed System: A system for which there is no exogenous
activity and event is said to be a closed system.
Ex: Water in insulated flask
Open System: A system for which there is exogenous
activity and event is said to be an open system.
Ex: Bank system
Discrete System: In this system the state variables
change only at a discrete set of points in a particular time.
Ex: No. of students in a class room
Continuous System: In which the state variable changes
continuously over a time.
Ex: The amount of water flow over a dam.
Model of a System:
A model is defined as a representative of a system for the purpose
of studying the system.
It is necessary to consider only those aspects of the system that
affect the problem under investigation. These aspects are
represented in a model.
Types of Model:
a) Mathematical or Physical Model: Use symbolic notation and the
mathematical equations to represent a system.
b) Static Model: Represents a system at a particular point of time
c) Dynamic Model: Represents a system as they change over time.
d) Deterministic Model: Contains no random variables. They have a
unique set of inputs which will result in a unique set of outputs.
e) Stochastic Model: Has one or more random variables as inputs.
Random inputs leads to random outputs.
Simulation is a numerical technique for conducting experiments on a
digital computer, which involves certain types of mathematical and
logical models over extended period of real time.
Why Simulation is required?
 We can study the effect of certain informational, organizational and

environmental change on the operation of a system by making
alterations in the model of the system.
Detailed observation of the system being simulated may lead to better

understanding of the system and to suggestion for improving it.
Advantages:
Easy to understand
Easy to test
Easy to upgrade
Easy to identify constraints
Easy to diagnose problems
Disadvantages:
Simulation process is expensive
It requires experts to understand
Operations are performed on the system using random number. Hence it is difficult
to predict results.
Developing Simulation Model:
Problem:
Simulation model consist of the following components, i.e., system
entities, input variables, Performance measures and functional
relationships.
Steps:
 Identify the problem with an existing system or set requirements of
a proposed system.
Design the problem with taking care of the existing system factors
and limitations
Collect and start processing the system data, observing its
performance and result.
 Develop the model using network diagrams and verifying using
various verification technique.
Validate the model by comparing its performance under various
conditions with the real system.
Create a document of the model for future use which
includes objectives, assumptions, input variables and
performance in detail.
Select an appropriate experimental design as per

requirement.
 Induce the experimental conditions on the model and

observe the result.
Deterministic Model: Types of Demand(Inventory)
Inventory: A stock or store of goods.
Independent Demand: Finished & ready to be sold goods. (Ex:
Computer) (Uncertain)
Dependant Demand: Components of finished Product.
(Certain)
Types of Inventories:
a) Raw materials and purchased parts
b) Partially completed goods called “work in progress”.
c) Finished good inventories.
d) Replacement parts, tools and suppliers
e) Goods in transit to ware houses or customers.
Stochastic Modeling:
It is a form of financial modeling that includes one or more random variables.
The purpose of such modeling is to estimate how probable outcomes are within a forecast to
predict conditions for different situations.
 The Monte Carlo simulation is one example of stochastic model.
 This is a powerful forecasting model that can be used to great effect for investing and
implementing trade strategies.
Stochastic variables or Random variables:
 A random variable is a set of possible values from a random experiment.
Ex: Tossing a coin
Random Variable (X) = Possible values (0 & 1), Random events (Head & Tail)
X = {0,1}

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Modelling & Simulation

Dr. Santhosh Kumar Gugulothu

c) Estimate the value of PI

d) Calculate the area of Irregular shape

 Simulation in Dynamic System

a) Queuing System (Single Server & Multiple Server)

b) Components of Queuing System

2. Assignments, As assigned in the class 10 (10%) Depending

3. Class Test As assigned in the class 10 (10%) 50 min

 Modeling is the process of representing a model which

This model is similar to a real system, which helps the

 It is also an act of building a model.

 It is the process of using a model to study the

 Simulation of a system is the operation of a model in

 It is an act of using a model for simulation.

 Event: It defines an instantaneous occurrence that may

Checking the Deposit money into

No. of busy tellers, Customer, arrival,

 System environment is classified into:

a) Endogenous system: If the system is not affected by the environment then it

Ex: Drawing cash in a bank.

b) Exogenous system: If the system is affected by the environment. It is used to

Ex: Arrival of customers

Why Simulation is required?

 We can study the effect of certain informational, organizational and

Detailed observation of the system being simulated may lead to better

Easy to identify constraints

Easy to diagnose problems

Simulation process is expensive

It requires experts to understand

Select an appropriate experimental design as per

 Induce the experimental conditions on the model and

predict conditions for different situations.

 The Monte Carlo simulation is one example of stochastic model.

implementing trade strategies.

Stochastic variables or Random variables:

 A random variable is a set of possible values from a random experiment.

Ex: Tossing a coin

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