Introduction to System Modelling and
Simulation
By:
Sharmila Chidaravalli
Assistant Professor
Dept. of ISE
What is a
SYSTEM?
The term system is derive from the Greek word systema, which means an
organized relationship among functioning units or components.
System exists because it is designed to achieve one or more objectives.
We come into daily contact with the transportation system, the telephone
system, the accounting system, the production system, and for two decades the
computer system.
There are more than a hundred definitions of the word system, but most seem
to have a common thread that suggests that a system is an orderly grouping of
interdependent components linked together according to a plan to achieve a
specific objective.
System
The study of the systems concepts, then, has three basic
implications:
• A system must be designed to achieve a predetermined
objective
• Interrelationships and interdependence must exist
among the components
• The objectives of the organization as a whole have a
higher priority than the objectives of its subsystems.
What is a Model
?
Simplified Representation of a Real or Theoretical System at some
particular point of time and space intended to provide the
understanding of the system.
Whether a model is good or not depends on
the extent to which it provides understanding.
What Level of Model Detail ?
All the models are simplification of reality.
Exact copy of a reality can only be the reality itself.
There is always a trade off as to what level of
detail is included in the model:
– Too little detail: risk of missing relevant
interactions.
– Too much detail: Overly complicated to
understand
What is a Simulation
?
It is an experiment in a computer where the real system is replaced by the execution
of the program.
It is a program that mimics (imitate) the behaviour of the real system
A Simulation is the imitation of the operation of a real-world process or system over time.
It can be done by hand or on a computer.
The behaviour of a system as it evolves over time is studied by developing a simulation model.
This model takes the form of a set of assumptions concerning the operation of the system.
The assumptions are expressed in
•Mathematical relationships
•Logical relationships
•Symbolic relationships between the entities of the system.
Modelling and Simulation
Discipline of understanding and evaluating the interaction
of parts of a real or theoretical system by;
•
Designing its representation (model)
Executing (running) the model including the time and
space dimension (simulation).
Why Simulation?
Accurate Depiction of Reality
Parts of the system may not be observable (e.g., internals of a silicon chip or
biological system)
Insightful System Evaluations
It may be too difficult, hazardous, or expensive to observe a real,
operational system
Uses of Simulations
1. Analyse systems before they are built
2. Reduce number of design mistakes
3.Optimize design
4. Analyse operational systems
5. Create virtual environments for training, entertainment
When to use Simulation
Over the years tremendous developments have taken place in computing capabilities and in
special purpose simulation languages, and in simulation methodologies.
The use of simulation techniques has also become widespread.
Following are some of the purposes for which simulation may be used.
Simulation is very useful for
experiments with the internal
interactions of a complex system, or
of a subsystem within a complex
system.
Simulation helps in suggesting
modifications in the system under
investigation for its optimal
performance.
Simulation can be employed
to experiment with new
designs and policies, before
implementing
Simulation is very useful in
determining the influence
of changes in input
variables on the output of
the system.
Simulation can be used to
verify the results obtained by
analytical
methods
and
reinforce
the
analytical
techniques.
When Simulation is Not Appropriate
Simulation should not be used when the problem can be solved using common sense.
Not, if the problem can be solved analytically.
Not, if it is easier to perform direct experiments.
Not, if the costs exceeds savings.
Not, if the resources or time are not available.
No data is available, not even estimate simulation is not advised.
If there is no enough time or the people are not available, simulation is not appropriate.
If managers have unreasonable expectation say, too much soon – or the power of simulation
is over estimated, simulation may not be appropriate.
If system behaviour is too complex or cannot be defined, simulation is not appropriate.
Advantages of Simulation
New policies, operating procedures, decision rules, information flow, etc can be explored without disrupting
the ongoing operations of the real system.
New hardware designs, physical layouts, transportation systems can be tested without committing resources
for their acquisition.
Hypotheses about how or why certain phenomena occur can be tested for feasibility.
Time can be compressed or expanded allowing for a speedup or slowdown of the phenomena under
investigation.
Insight can be obtained about the interaction of variables.
Insight can be obtained about the importance of variables to the performance of the system.
Bottleneck analysis can be performed indication where work-in process, information materials and so on are
being excessively delayed.
A simulation study can help in understanding how the system operates rather than how individuals think the
system operates.
“what-if” questions can be answered. Useful in the design of new systems.
Disadvantages of Simulation
Model building requires special training. It is an art that is learned over time and through
experience.
If two models are constructed by two competent individuals, they may have similarities, but it is
highly unlikely that they will be the same.
Simulation results may be difficult to interpret. Since most simulation outputs are essentially
random variables (they are usually based on random inputs), it may be hard to determine whether
an observation is a result of system interrelationships or randomness.
Simulation modeling and analysis can be time consuming and expensive. Skimping on resources
for modeling and analysis may result in a simulation model or analysis that is not sufficient for the
task.
Simulation is used in some cases when an analytical solution is possible, or even preferable.
Areas of Applications
Manufacturing: Design analysis and optimization of production system,
materials management,
performance evaluation
capacity
planning,
layout
planning,
and
Business:
Market analysis, prediction of consumer
behaviour, and optimization of marketing strategy and
logistics, comparative evaluation of marketing campaigns.
Military:
Testing of alternative combat strategies, air
operations, sea operations, simulated war exercises, practicing
ordinance effectiveness, inventory management.
Healthcare applications:
such as planning of health
services, expected patient density, facilities requirement,
hospital staffing , estimating the effectiveness of a health care
program.
Communication Applications:
Such as network design, and
optimization, evaluating network reliability, manpower planning, sizing of
message buffers.
Computer Applications: Such as designing hardware
configurations and operating system protocols, sharing networking.
Client/Server system architecture
Economic applications:
such as portfolio management, forecasting
impact of Govt. Policies and international market fluctuations on the economy.
Budgeting and forecasting market fluctuations.
Transportation applications: Design and testing of alternative
transportation policies, transportation networks-roads, railways, airways
etc. Evaluation of timetables, traffic planning.
Environment
application:
Solid
waste
management,
performance evaluation of environmental programs, evaluation of
pollution control systems.
Biological applications: Such as population genetics and spread
of epidemics.
Business process Re-engineering: Integrating business process re-engineering
with image –based work flow, using process modelling and analysis tool.