System Simulation & Modeling


  • Define Simulation?

  • When Simulation is an appropriate tool and when it is not appropriate.

  • Advantages and Disadvantages of Simulation.

  • Application areas of Simulation.

  • Systems.

  • Components of a System.

  • Discrete and Continuous System.

  • Model of a System.

  • Types of Model.

  • Discrete Event System Simulation.

  • Steps in Simulation Study.

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:

  1. Manufacturing Applications

  2. Semiconductor Manufacturing

  3. Construction Engineering

  4. Military Applications

  5. Logistics, Transportation and Distribution Applications.

  6. Business Process Simulation

  7. Human Systems


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:

  • The building of a dam embankment.

  • Underground urban infrastructure renewal with no trenches.

  • Scheduling activities in a dynamic, multi project environment.

  • Examine the structural steel erection process.

  • Utility tunnel construction special purpose template

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:

  • The effect of redesigned connection banks on airport gate assignment.

  • Program planning for product development.

  • Business and system modelling reconciliation.

  • Personal forecasting and workforce strategic planning. 

Human Systems

  • Human performance modelling in complex systems.

  • Investigating the human factor in traffic control.