Today Simulation is arguably one of the most multifaceted topics that can face an Industrial Engineer in the workplace. It can also be one of the most important to a corporation, regardless of the industry. Quality, safety and productivity are all affected by Simulation, whether the issues occur in the office, on the manufacturing floor, or in a warehouse. ENCON is focussed towards providing services on the development of Industrial Process Simulation where we use as a powerful tool for increasing the competitiveness and profits of the company
There are many scenarios that can be simulated. As a general rule systems that involve a process flow with events can be simulated. So any process you can draw a flowchart of, you can simulate.
The processes you'll gain most benefit from simulating are those that involve change over time and randomness.
Modelling & simulation system can handle as much complexity as you need it to, meaning you can get the results you need to make decisions fast.
ENCON Simulation is coming of age for industry that’s no longer just the domain of academics.
ENCON Simulation has advanced to such a stage that the software enables the user to model, execute, and animate any manufacturing system in any level of detail.
ENCON SIMULATION for the application of simulation in the field of industrial control processes as well as to synergies generated by simulation based on experimentation and analysis techniques, to discover exact solutions to typical industry and engineering problems.
ENCON Simulation to simulate an abstract model of a particular system. Our simulations system have become a useful part of mathematical modelling of many natural systems in physics, chemistry and biology, human systems in economics, psychology, and social science and in the process of engineering new technology, to gain insight into the operation of those systems. Also use adjunct to purely mathematical models in science, technology and entertainment.
The reliability and the trust people put in simulations model is close to 100%.
A computer model is the algorithms and equations used to capture the behavior of the system being modeled. By contrast, a computer simulation is the actual running of the program that contains these equations or algorithms. Simulation, therefore, is the process of running a model. Thus one would not "build a simulation"; instead, one would "build a model", and then either "run the model" or equivalently "run a simulation".
A computer simulation is a simulation, run on a single computer, or a network of computers, to reproduce behavior of a system. The simulation uses an abstract model to simulate the system. Computer simulations have become a useful part of mathematical modeling of many natural systems in physics (computational physics, astrophysics, climatology, chemistry and biology, human systems in economics, psychology, social science, and engineering. Simulation of a system is represented as the running of the system's model. It can be used to explore and gain new insights into new technology and to estimate the performance of systems too complex for analytical solutions.
|A||Sector of your industry i:e, Auto, Chemicals, etc. ....|
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Modelling & simulation is used in a wide variety of practical contexts, such as:
1) Analysis of air pollutant dispersion using atmospheric dispersion modeling
2) Design of complex systems such as aircraft, automobiles, trains, ships and also logistics systems.
3) Design of noise barriers to effect roadway noise mitigation modeling of application performance
4) Weather forecasting
5) Forecasting of risk
6) Simulation of other computers is emulation.
7) Forecasting of prices on financial markets
8) Behavior of structures (such as bridges, highways, hydroelectric dams, buildings industrial and commercial) under stress and other conditions
9) Design of industrial processes, such as oil & gas, petro-chemical processing plants
10) Strategic management and organizational studies
11) Reservoir simulation for the petroleum engineering to model the subsurface reservoir
12) Process engineering simulation tools.
13) Robot simulators for the design of robots and robot control algorithms
14) Urban simulation models that simulate dynamic patterns of urban development and responses to urban land use and transportation policies.
15) Traffic engineering to plan or redesign parts of the street network from single junctions over cities to a national highway network to transportation system planning, design and operations. Modeling car crashes to test safety mechanisms in new vehicle models.
16) Crop-soil systems in agriculture, via dedicated software frameworks.
The reliability and the trust people put in simulation depends on the validity of the simulation model, therefore verification and validation are of crucial technology.
Another important aspect of computer simulations is that of reproducibility of the results, meaning that a simulation model should not provide a different answer for each execution. Although this might seem obvious, this is a special point of attention in stochastic simulations, where random numbers should actually be semi-random numbers. An exception to reproducibility are human-in-the-loop simulations such as flight simulations and computer games. Here a human is part of the simulation and thus influences the outcome in a way that is hard, if not impossible, to reproduce exactly.
Vehicle manufacturers make use of simulation to test safety features in new designs. By building a copy of the car in a physics simulation environment, they can save the hundreds of thousands of dollars that would otherwise be required to build and test a unique prototype. Engineers can step through the simulation milliseconds at a time to determine the exact stresses being put upon each section of the prototype.
Computer graphics can be used to display the results of a simulation. Animations can be used to experience a simulation in real-time, e.g., in training simulators. In some cases animations may also be useful in faster than real-time or even slower than real-time modes. For example, faster than real-time animations can be useful in visualizing the buildup of queues in the simulation of humans evacuating a building. Furthermore, simulation results are often aggregated into static images using various ways of scientific visualization.In debugging, simulating a program execution under test (rather than executing natively) can detect far more errors than the hardware itself can detect and, at the same time, log useful debugging information such as instruction trace, memory alterations and instruction counts. This technique can also detect buffer overflow and similar "hard to detect" errors as well as produce performance information and tuning data.