Chapter 1 Introduction to Simulation

1. Chapter 1Introduction to Simulation

2. System How to evaluate? Experiment Analysis Simulation Given a system, how do you evaluate its performance?

3. How to study a system? • Measurements on an existing system - What to do, if system does not exist in reality? - What to do, if changes are very expensive or time consuming? • Mathematical analysis - Good solutions, but only feasible for simple systems. - Real world systems are too complex, e.g, factory,computer, network etc. • Simulation - Build the behavior of a system within a program

4. What is a simulation? • A simulation is the imitation of the operation of real-world process or system over time. • What is the method? • Generate an artificial history of a system • Draw inferences from the artificial history concerning the characteristics of the system • How it is done? • Develop a model • Model consists of entities (objects)

5. Goal of modeling and simulation • A model can be used to investigate a wide verity of “what if” questions about real-world system. • Analysis tool for predicating the effect of changes • Design tool to predicate the performance of new system • Find adequate parameters before implementation • It is better to do simulation before Implementation.

6. When Simulation Is the Appropriate Tool ? • Simulation enable the study of internal interactions of a complex system. • Informational, organizational and environmental changes can be simulated to find their effects on the behavior of the model. • A simulation model help us to gain knowledge about improvement of system. • By changing simulation inputs and observing the resulting outputs valuable insights can be obtained. • Simulation can be used to experiment with new design and policies before Implementation

7. Simulation can be used to verify the analytic solutions. • Simulation models designed for training make learning possible without the cost and disruption of on-the-job training. • A plan can be visualized with animated simulation. • The modern system (factory, wafer fabrication plant, service organization) is too complex that its internal interaction can be treated only by simulation

8. When Simulation Is Not Appropriate ? • When the problem can be solved by common sense. • When the problem can be solved analytically. • If it is easier to perform direct experiments. • If cost exceed savings. • If resource or time are not available. • If no data is available. • If no enough time is available to verify and validate the simulation model. • If system behavior is too complex. 􀂅 Like human behavior

9. Advantages of simulation • New policies, operating procedures, information flows and so on can be explored . • New hardware designs, physical layouts, transportation systems and … can be tested without committing resources for their acquisition. • Time can be compressed or expanded. • Insight can be obtained about interaction of variables and importance of the variables to the performance. • Bottleneck analysis can be performed to discover where work in process, the system is delayed. • A simulation study can help in understanding how the system operates. • What if” questions can be answered.

10. Disadvantages of simulation • Produces only estimates of the model . • Model building requires special training. • If appropriate model is not constructed it gives wrong idea of the system. • Simulation modeling and analysis can be time consuming and expensive. • Simulation results can be difficult to interpret.

11. Areas of Application • Manufacturing applications • Semiconductor manufacturing • Construction engineering and project management • Military applications • Logistics, supply chain and distribution applications • Transportation models and traffic • Business process simulation • Health care • Call-center • Computers and Networks • Games

12. Systemand System Environment • A system is a group of objects that are joined together in some regular interaction or interdependence toward the accomplishment of some purpose. • Example1: Automobile factory • Example 2: Computer network • System environment : A system is often affected by changes occurring outside the system Factory : Arrival orders Banks :Arrival of customers

13. Components of system • Entity : • Attribute: • Activity: • State: • Event: An object of interest in the system : Machines in factory The property of an entity : speed, capacity A time period of specified length :welding, stamping A collection of variables that describe the system in any time : status of machine (busy, idle, down,…) A instantaneous occurrence that might change the state of the system: breakdown

14. Components of System – Examples

15. Discrete and Continuous Systems • A discrete system is one in which the state variables change only at a discrete set of points in time • Example: Bank

16. A continues system is one in which the state variables change continuously over time: Head of water behind the dam

17. Model of a System • What is a model? • A model is a representation of a system for the purpose of studying the system. - It is necessary to consider those aspects of the system that affect the problem under investigation (unnecessary details must remove)

18. Types of Models

19. Physical model :Prototype of a system for the purpose of study • Mathematical model :A mathematical model uses symbolic notation and mathematical equations to represent a system. • Simulation Model : simulation model is a particular type of mathematical model of a system.

20. SimulationModels

21. Types of simulation models • Static: Represent a system at a particular point in time. • Dynamic: Represent a system over a time interval. • Deterministic: Simulation models without random variables. • Stochastic: Simulation models with random variables. • Discrete: System state changes occur only at discrete time points. • Continuous: System state changes occur continuously. We will focus on discrete, dynamic, and stochastic simulation models

22. Discrete-event Simulation • System state changes only at discrete set of points in time. • Simulation model is analyzed by numerical methods. • Numerical methods employ computational procedures to “solve” mathematical models. • The model is rather “run” than “solved”

23. Steps in simulation study 1.- Clearly understand problem - Reformulation of the problem 2. - Which questions should be answered? - Is simulation appropriate? - Costs? 3. -complexity - Model user 5. Program 6. - Does the program performs, what the model describes? 7. –Is the model accurate representation of real system 8. - Which alternatives should be run? - Which paramters should be varied? - length of initialization period -length of simulation run - No. of replications to be made of each run. 11.- Program documentation – how does the program work - Progress documentation – chronology of the work