COMPUTER SIMULATION

 
Effective evaluations of many real-world situations are too complex. Alternative methods must be used to evaluate the performance of such systems. Simulation is a modeling and analysis tool widely used for the purpose of designing, planning, and control of manufacturing systems. Simulation in general is to pretend that one deals with a real thing while really working with an imitation. In operations research, the imitation is a computer model of the simulated reality. The task of executing simulations provides insight and a deep understanding of physical processes that are being modeled.

Simulation is generally referred to as computer simulation, which simulates the operation of a manufacturing system. A computer simulation or a computer model is a computer program which attempts to simulate an abstract model of a particular system. Computer simulation was developed hand-in-hand with the rapid growth of the computer, following its first large-scale deployment during the Manhattan Project in World War II to model the process of nuclear detonation. Computer simulation is often used an adjunct to, or substitution for, modeling systems for which simple closed form analytic solutions are not possible. There are many different types of computer simulation; the common feature they all share is the attempt to generate a sample of representative scenarios for a model in which a complete enumeration of all possible states of the model would be prohibitive or impossible.

Computer simulations have become a useful part of modeling many natural systems in physics, chemistry and biology, human systems in economics and social science and in the process of new technology in the field of engineering, to gain insight into the operation of those systems. Traditionally, the formal modeling of systems has been via a mathematical model, which attempts to find analytical solutions to problems which enables the prediction of the behaviour of the system from a set of parameters and initial conditions. Computer simulations build on, and are a useful adjunct to purely mathematical models in science and technology and entertainment.
With a computer simulation model, a manager or system analyst is able to observe the behaviour of a process without the necessity of experimenting with the actual system. In order to evaluate the system‟s performance given various disturbances, or to identify the 6 Control and Simulation of CIM

bottlenecks, they may try out different manufacturing runs, new operational conditions, new equipment layouts or different cycle times.
A simple example of a simulation involves the tossing of a ball into the air. The ball can be said to "simulate" a missile, for instance. That is, by experimenting with throwing balls starting at different initial heights and initial velocity vectors, it can be said that we are simulating the trajectory of a missile. This kind of simulation is known as analog simulation since it involves a physical model of a ball. A flight simulator on a PC is a computer model of some aspects of the flight: it shows on the screen the controls and what the "pilot" (the youngster who operates it) is supposed to see from the "cockpit" (his armchair).
11.2 CHARACTERISTICS OF COMPUTER SIMULATION
The technique of computer simulation used as an aid to decision-making has many desirable features and, unfortunately, some disadvantages when compared to other approaches.
11.2.1 Advantages of Computer Simulation
 




 Flexibility

To fly a simulator is safer and cheaper than the real airplane. For precisely this reason, models are used in industry commerce and military: it is very costly, dangerous and often impossible to make experiments with real systems. Provided that models are adequate descriptions of reality (they are valid), experimenting with them can save money, suffering and even time. Moreover, additional alternatives can be evaluated by changing the input data for the same model.

(ii) Study of Transient Behaviour

Systems that change with time, such as a gas station where cars come and go (called dynamic systems) and involve randomness is a good example. Nobody can guess at exactly which time the next car should arrive at the station, are good candidates for simulation. Modeling complex dynamic systems theoretically need too many simplifications and the emerging models may not be therefore valid. Simulation does not require that many simplifying assumptions, making it the only tool even in absence of randomness. Simulation can provide much better control over experimental conditions that would be possible when experimenting with physical models.
(iii) Communication

Whether a particular experiment is fruitful can best be spotted by watching a dynamic graphics display, and thus can act as a means of communication. Animation of the process under investigation results in benefits for the model builder, beneficial communication between the model builder and model user, and 7 Introduction to Simulation


benefits in presentation to users and management. The model user can be actively involved with a simulation model throughout the model development cycle because of the increased ease of communication that animation allows. This leads to the increase in benefits of users and significant improvement in the model.

(iv) Possibility to study systems that are nonexistent.

(v) Compression or expansion of time.

(vi) Compare to other decision support techniques.

(vii) Observation of diverse performance indicators.

(viii) Sensitivity analysis.

(ix) Dynamic visualizations, education.
11.2.2 Limitations of Computer Simulation
 (i) Large-scale-manufacturing systems tend to be very complex. Writing computer programs to model such systems can be a long and expensive task. Even given the best circumstances, however, simulation projects are always time consuming – frequently needing many months before useful results are realized.