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PRESENTATIONon
Physical Modelling
BYDeeksha Porwal
(M.TECH.)
(MANUFACTURING SCIENCE &
TECHNOLOGY)
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THE CONCEPT OF A SYSTEM
A system is:-
A set of components which are related by
some form of interaction and which act
together to achieve some objective or purpose.
Components are the individual parts or
elements that collectively make up the system.
Objective is the desired state or outcome
which the system is attempting to achieve.
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ENTITIES ATTRIBUTES AND
ACTIVITIES
Entity : object of interest in the system
Attribute : property of an entity
Activity : process that causes change insystem
Example : An Elevator System
Entities : Elevators, people
Attributes: Elevators – capacity, speed,
destination, current location of each elevator
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Entities Attributes Continue......
People – inter-arrival time at each floor,
destination of each people.
Activities
Load/Unloading passenger
Travel to next floor (speed and distance)
Persons travel to elevator
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SYSTEM ENVIRONMENT
It can be defined as:-
A system is often affected by changes occurring outside
the system. Some system activities may also produce
changes that do not react on the system. Such changes
occurring outside the system are said to occur in system
environment.
Endogenous : activities occurring within thesystem.
Exogenous : activities in the environment
that affect the system. Closed system :for which there is no
exogenous activity.
Open system : which does have exogenous
activity.
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Example: Environment of a business
system
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CONTINUOUS AND DISCRETE SYSTEMS
Continuous System: The state variables change in
a continuous way, and not abruptly from one state
to another (infinite number of states).
Discrete System: The state variables change only
at a countable number of points in time.
These points in time are the ones at which the
event occurs/change in state.
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SALES OF A CERTAIN PRODUCT
OVER TIME
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LINEAR AND NON LINEAR SYSTEMS
Linear systems satisfy the properties of
superposition and homogeneity.
Linear systems have one equilibrium point at
the origin.
Any system that does not satisfy these
properties is nonlinear.
Nonlinear systems may have many equilibriumpoints
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STOCHASTIC ACTIVITY
•When the effects of activity vary randomly overvarious possible outcomes, the activity is said to bestochastic.
•Stochastic activity is one whose behavior cannotbe entirely predicted i.e.; non-deterministic, inthat a system's subsequent state is determined
both by the process's predictable actions and by arandom element.
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TYPES OF MODELS
MODELS
PHYSICAL MATHEMATICAL
STATIC DYNAMIC
NUMERICAL ANALYTICAL NUMERICAL
SYSTEM
SIMULATION
STATIC DYNAMIC
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STATIC AND DYNAMIC MODELS
A static model:-
• takes a single snapshot of a situation.
• everything occurs in a single interval.
Dynamic models are:-
• time dependent.
• state variable change over time.
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PRINCIPLES OF MODELLING
Block Building-: the description of the system should
be organised in a series of blocks.
The system may be described as the interconnection
between the blocks.
Block represents a part of a system that depends upon
few input variables and results in output variables.
Relevance-: Only those aspects of the system that arerelevant to objectives of studies should be included in
the model.
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Accuracy-: The accuracy of the information
gathered for the model should be considered.
Aggregation-: A further factor to be
considered to which the number of individual
entities can be group together into lager entity.
Principles of Modelling Continue......
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BASIC SIMULATION MODELLING
Simulation Modelling is therefore an experimental
and applied methodology which seeks to-:
Describe the behaviour of the system.
Construct theory or hypothesis that account for the
observed behaviour.
Use these theories to predict future behaviour i.e. the
effects that will be produced changes in the system orin its method of operation.
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The steps involved in simulation analysis are-:
Step 1. Identify the problem.
Step 2. Formulate the problem.
Step 3. Collect and process real system data.
Step 4. Formulate and develop a model.
Step 5. Validate the model. Step 6. Document model for future use.
Step 7. Select appropriate experimental design.
Step 8. Establish experimental conditions for runs.
Step 9. Perform simulation runs.
Step 10. Interpret and present results.
Step 11. Recommend further course of action.
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ADVANTAGES OF SIMULATION
Most complex, real-world systems with stochastic elements
can be investigated.
Simulation allows one to estimate the performance of an
existing system under some projected set of operating
conditions.
Alternative proposed system designs can be compared via
simulation to see which best meets a specified requirement.
We can maintain much better control over experimental
conditions than would generally be possible whenexperimenting with the system itself.
Relatively straight forward and flexible.
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