System Simulation & Modeling System And System Environment Steps in Simulation Study The Simulation Model Building Can Be Broken into 4 Phases The Elements of a Queuing System Are Simulation of Queuing Systems

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Introduction

Define Simulation?

Simulating the operation of a real-world process or system over time is called simulation.
A simulation model is used to study the behavior of a system as it evolves through time This model takes the form of a set of assumptions about how the system works.

When Simulation is the Appropriate Tool

Simulation allows researchers to investigate and experiment with the internal interactions of a complex system, or a subsystem within one.
Informational, organizational, and environmental changes can be simulated, and the impact on the model's behaviour can be monitored.
The insights gathered from creating a simulation model can be extremely useful in recommending improvements to the system under consideration.
Valuable insight into which factors are most essential and how variables interact can be gained by adjusting simulation inputs and analysing the subsequent outputs.
Simulation can be utilised as a teaching tool to enhance analytical problem-solving approaches.
Simulation can be used to test new designs or regulations before to deployment in order to anticipate what might occur.
Analytic answers can be verified via simulation.
Machine requirements can be established by modelling various capabilities.

When Simulation is Not Appropriate:

Simulation should be utilised when common sense cannot answer the problem.
If the problem can be solved analytically, simulation should not be used.
If performing direct experiments is easier, simulation should be avoided.
If the costs exceed the savings, simulation should not be used.
If resources or time are in short supply, simulation should be avoided.
If there is no data, even an estimate simulation is not recommended.
Simulation is not acceptable if there is insufficient time or if the person is unavailable.
Simulation may not be acceptable if managers have excessive expectations, such as expecting too much too quickly – or if the capacity of simulation is overestimated.
Simulation is not appropriate if the system behaviour is too complex or cannot be characterized.

Advantages of Simulation:

Simulation can also be used to investigate systems during the design phase.
Simulation models are used instead of solvers.
New policies, operating procedures, decision rules, information flow, and so on can be investigated without interfering with the real system's ongoing operations.
New hardware designs, physical layouts, and transportation systems can be tested without committing resources to purchase.
The feasibility of hypotheses about how or why certain phenomena occur can be tested.
Time can be compressed or expanded, allowing the phenomenon under investigation to be sped up or slowed down.
Information about the interaction of variables can be obtained.
Information about the importance of variables to system performance can be obtained.
A bottleneck analysis can be performed to determine where work-in-process, information materials, and so on are being delayed excessively.
A simulation study can aid in understanding how the system works rather than how individuals believe it works.

Disadvantages of simulation

Model building requires special training.
Simulation results may be difficult to interpret.
Simulation modelling and analysis can take time and money.
Simulation is used when an analytical solution is either possible or preferable.

Applications of Simulation:

Manufacturing Applications:

Examination of electronic assembly operations.
A selective assembly station for high-precision scroll compressor shells was designed and evaluated.
Using large facility models, compare dispatching rules for semiconductor manufacturing.
Cluster tool throughput evaluation for thin-film head production.
Choosing the best lot size for a semiconductor backend factory.
Cycle time and utilization optimization in semiconductor test manufacturing.
An examination of warehouse storage and retrieval strategies.
Dynamics in a service-oriented supply chain investigation
A model of a chemical munitions disposal facility for the Army.

Semiconductor Manufacturing:

Using large-facility models, compare dispatching rules.
Variability's corrupting influence
A new wafer fab lot-release rule.
Evaluation of potential productivity gains from proactive retirement management.
A 200 mm and 300 mm X-ray lithography cell are compared.
Planning capacity with time constraints between operations.

Construction Engineering:

Military Applications:

Simulating the effects of leadership and recruit type in an Army recruiting station.
Development and testing of an intelligent controller for self-driving underwater vehicles.
Simulating military requirements for non-conflict fighting operations.
Multi-trajectory performance for different scenario sizes.

Logistics, Transportation and Distribution Applications:

Assessing the potential advantages of a rail-traffic planning algorithm.
Assessing strategies for improving railroad performance.
The use of metric modelling in rail capacity planning.
Passenger flow analysis in an airport terminal
Proactive flight schedule analysis.
Logistic issues in self-sustaining food production systems for long-term space exploration.
Industrial rail-car fleet sizing
Distribution of production in the newspaper industry.
Conceptualization of a toll plaza
Selecting a rental car location.
Rapid response replenishment.

Business Process Simulation:

Human Systems

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