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Modeling and simulation can be
defined as the use of models and simulations, either statistically or overtime,
to develop data as a basis for making managerial or technical decisions. It can
also be defined as the use of physical-based systems to map a natural
phenomenon to a computer simulation. This includes, but is not limited to, emulators,
prototypes, simulators, and stimulators. A model is a simplified representation
of a system at some particular point in time or space intended to promote
understanding of the real system, whilst simulation is the imitation of the
operation of a real-world process over time.

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Georges-Louis Leclerc, Comte de
Buffon (1707-1788), was a French naturalist (an expert in or student of natural
history) who anticipated many of the ideas of Darwin and Lamarck on evolution.
He is remembered in the history of probability theory for his famous needle
problem which is the first example of a simulation experiment. The
needle-tossing experiment is the earliest known example of using independent
replications of a simulation to approximate an important physical constant.

William Sealy Gosset (1876–1937),
trained in mathematics and chemistry, was a brewer with Arthur Guiness, Son
& Co. Ltd. and made numerous contributions to statistical methodology in
his spare time. He was tasked with maintaining consistent quality of Guiness’s
ale. To solve his problem Gosset conducted a precomputer simulation experiment.
Gosset’s inaugural application of simulation to industrial process control is
an example of synergy of simulation-based experimentation and analytic
techniques in the discovery of the exact solution of what is arguably a
classical industrial-engineering problem.

During World War II two
mathematicians Jon Von Neumann ad Stanislaw Ulam were faced with the puzzling
problem of the behavior of neutrons. Hit and trial experimentation were too
costly and analysis wasn’t an option as the problem was too complicated. Hence,
the Roulette technique was suggested by he mathematicians. The basic data regarding the occurrence of various events
were known, into which the probabilities of separate events were merged in a
step by step analysis to predict the outcome of the whole sequence of events. With
the remarkable success of the techniques on neutron problem, it soon became
popular and found many applications in the business and industry.


It’s important because description
of system behavior by experimentation might not be feasible as the experiment
cost may be too high or time constants of the system may not be compatible with
human dimensions. It may also be due to inaccessible inputs and outputs, the
experiment may also be too dangerous or experimental behavior might be obscured
by disturbances. However it is worth emphasizing that the intention of modeling
and simulation isn’t to replace actual experiments in the real world and should
not be viewed as a substitute.

Modeling and simulation also
supports early evaluation and optimization of designs and ongoing verification
as changes occur, making sure the right product is developed and delivered with
the required speed and quality. The operation of the model can be studied, and
hence, properties concerning the behavior of the actual system or its subsystem
can be inferred. To explain further, it helps in understanding how a process
would behave in various conditions. Basically, what output can be expected for
a given inputs It’s a tool to evaluate the performance of a system, existing or
proposed, under different configurations of interest and over long periods of
real time.

Models are useful for formalizing intuitive understandings, even
if those understandings are partial and incomplete. What appears to be a solid
verbal argument about cause and effect can be clarified and put to a rigorous
test as soon as an attempt is made to formulate the verbal arguments into a
mathematical model. This process forces clarity of expression and consistency
(of units, dimensions, force balance, or other guiding principles) that is not
available in natural language. As importantly, it can generate predictions
against which intuition can be tested. Because they run on a computer, simulation
models force the researcher to represent explicitly important components and
connections in a system. Thus, simulations can only complement, but never
replace, the underlying formulation of a model in terms of biological,
physical, and mathematical principles. That said, a simulation model often can
be used to indicate gaps in one’s knowledge of some phenomenon, at which point
substantial intellectual work involving these principles is needed to fill the
gaps in the simulation.



Modeling and simulation are both
enabling and very important technology in many application areas. Virtual
simulation involves the use of virtual equipment and real people (sometimes
referred to as the human-in-the-loop) in a simulation study.

A good example would be a flight
simulator; this is a device that artificially re-creates aircraft flight and
the environment in which it flies, for pilot training. This includes
replication of equations that govern how aircraft fly, aircraft reactions to
the application of flight controls, the effects of different aircraft systems
on each other and how aircraft reacts to external factors such as turbulence.
Although a flight simulator is quite expensive, it has proven to be one of the
most cost-effective methods for training pilots as the pilot gets trained
without damaging the real aircraft or endangering any lives. It may also be
used in the design and development of actual aircraft, to research specific
aircraft characteristics and control handling qualities.

The educational arena uses
simulations as a way of providing experience; basically it allows students to
gain real world experience while in the classroom. This encourages them to be
creative, innovative and limitless. From the classroom students can simulate
being a pilot, an engineer, an animator or a computer programmer. These
opportunities afford students the opportunity to excel in non-traditional core
classroom disciplines. Educators too benefit from the use of simulations as it
allows leadership and team building skills to be cultivated in a variety of
socio-economic, allowing for low-risk development of transferable experiences.

environments allow you to test out new ideas before you make a complex business
decision. This analysis technique lets you manipulate different parameters,
such as revenue and costs, to discover opportunities for improvement in your
current operations. Simulation models can give you a graphical display of
information that can be edited and animated, showing you what might happen if
you take certain actions. Applying these results to your business helps you
manage risk and make better choices. Using spreadsheets, you can
simulate what might happen if certain conditions exist. This helps you generate
more accurate forecasts. You can use your existing data and manipulate it based
on potential changes, such as winning new deals or losing a major client

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