Generally, modeling and simulation are substitutes for physical experimentation in which computers are used to calculate the results of some physical phenomenon.
Modeling refers to the process of representing a model which includes its construction and working. This model is similar to a real system, which helps the analyst predict the effect of changes to the system.
Simulation of a system is the operation of a model in terms of time or space, which helps analyze the performance of an existing or a proposed system.
Simulation modeling solves real-world problems safely and efficiently. It provides an important method of analysis which is easily verified, communicated and understood. Across industries and disciplines, simulation modeling provides valuable solutions by giving clear insights into complex systems.
Computer-based simulations can involve everything from simple addition of a few numbers to intensive computations that challenge the fastest computing machines currently available. Models for simulation can be classified along four distinct dimensions:
System of Interest – The system of interest can be one of the following:
- A physical system, for example, a supply chain or production line
- A management system, for example, a CRM process
- A meta-model, for example, rules that establish whether a model is formulated properly
Visibility – Internally, a model may be:
- Transparent, that is, a description of actual mechanisms
- Black box, that is, a description that results in the same behavior as the real system but internally does not model the actual mechanism
Probability – A model can be:
- Probabilistic, that is, a single set of inputs that results in many possible outputs–the outputs exhibit variations that are described using statistics
- Deterministic, that is, the same set of inputs results in the same set of outputs; the outputs are causally determined by preceding events
Dynamics – A model can be:
- Steady-state, that is, the outputs show no variation over time and space
- Dynamic, that is , the outputs vary over time and across space
Modeling is a way to create a virtual representation of a real-world system that includes software and hardware. If the software components of this model are driven by mathematical relationships, you can simulate this virtual representation under a wide range of conditions to see how it behaves.
Modeling and simulation are especially valuable for testing conditions that might be difficult to reproduce with hardware prototypes alone, especially in the early phase of the design process when hardware may not be available. Iterating between modeling and simulation can improve the quality of the system design early, thereby reducing the number of errors found later in the design process.
Common representations for system models include block diagrams, schematics and state charts. Using these representations you can model mechatronic systems, control software, signal processing algorithms, and communications systems.
Want to know more about modeling and simulation? Tonex offers several courses in modeling and simulation.
Additionally, Tonex offers nearly 400 classes, seminars and workshops in close to four dozen categories of systems engineering training.
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