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Introduction to Simulation - Coggle Diagram
Introduction to Simulation
Advantages
Avoid risk and danger that might occur
Able to adjust variables that to study various possible outcomes
True understanding on how the system operates
Time period can be sped up to simulate behavior of system for a long period of time
Able to simulate ideas or upgrades to current system without disrupting the operations and commiting resources for acquisition
Able to answer "What If" question which is essential for system design
Bottleneck analysis can be done to identify areas where where tasks are delayed excessively.
Appropriate tool for Simulation
Simulation enables the study of, and experimentation with, the internalinteractions of a complex system, or of a subsystem within a complexsystem
Informational, organizational, and environmental changes can be simu-lated, and the effect of these alterations on the model’s behavior can be observed.
The knowledge gained in designing a simulation model may be of greatvalue toward suggesting improvement in the system under investigation.
By changing simulation inputs and observing the resulting outputs, valuable insight may be obtained into which variables are most important andhow variables interact.
Simulation can be used as a pedagogical device to reinforce analytic solution methodologies.
Simulation can be used to experiment with new designs or policies priorto implementation, so as to prepare for what may happen.
Simulation can be used to verify analytic solutions.
By simulating different capabilities for a machine, requirements can be determined
Simulation models designed for training allow learning without the costand disruption of on-the-job learning.
Animation shows a system in simulated operation so that the plan can bevisualized.
The modern system (factory, wafer fabrication plant, service organization,etc.) is so complex that the interactions can be treated only through simulation.
Disadvantages
Unaccounted factors/variables can affect outcome of simulation drastically
Creation of simulation might be time consuming and expensive
Simulation results might be difficult to interpret
Simulation results might not be accurate
Unaccounted factors/variables can affect outcome of simulation drastically
It is difficult to simulate complex system
Applications
Semiconductor
The corrupting influence of variability
A new lot-release rule for wafer fabs
Comparison of dispatching rules using large-facility models
Assessment of potential gains in productivity due to proactive reticle management
Comparison of a 200-mm and 300-mm X-ray lithography cell
Capacity planning with time constraints between operations 300-mm logistic system risk reduction
Construction
Construction of a dam embankment
Trenchless renewal of underground urban infrastructures
Activity scheduling in a dynamic, multiproject setting
Investigation of the structural steel erection process
Special-purpose template for utility tunnel construction
Manufacturing
Analysis of electronics assembly operations
Design and evaluation of a selective assembly station for high-precision scroll compressor shells
Comparison of dispatching rules for semiconductor manufacturing using large-facility models
Evaluation of cluster tool throughput for thin-film head production
Determining optimal lot size for a semiconductor back-end factory
Optimization of cycle time and utilization in semiconductor test manufacturing
Analysis of storage and retrieval strategies in a warehouse
Investigation of dynamics in a service-oriented supply chain
Model for an Army chemical munitions disposal facility
Military
Modeling leadership effects and recruit type in an Army recruiting station
Design and test of an intelligent controller for autonomous underwater vehicles
Modeling military requirements for nonwarfighting operations
Multitrajectory performance for varying scenario sizes
Using adaptive agents in U.S. Air Force pilot retention
Business Process Simulation
Impact of connection bank redesign on airport gate assignment
Product development program planning
Reconciliation of business and systems modeling
Personnel forecasting and strategic workforce planning
Logistics, Transportation and Distributions
Evaluating the potential benefits of a rail-traffic planning algorithm
Evaluating strategies to improve railroad performance
Parametric modeling in rail-capacity planning
Analysis of passenger flows in an airport terminal
Proactive flight-schedule evaluation
Logistics issues in autonomous food production systems for extended-duration space exploration
Sizing industrial rail-car fleets
Product distribution in the newspaper industry
Design of a toll plaza
Choosing between rental-car locations
Quick-response replenishment
Human Systems
Modeling human performance in complex systems
Studying the human element in air traffic control
Inappropriate usage of Simulation
When a problem can be solved through common sense such as methods of computation
When a problem can be solved analytically
When it is easier to perform direct experiments
When costs exceeds savings
When resources are not available
When time is not available
When data and estimates are not available
When there is no ability of time or personnel to validate or verify the model
When the power of simulation is overestimated
When system is too complex or cannot be defined