Simulation and Modelling 4 – System Definition

1. Simulation and Modelling4 – System Definition Yumarsono Muhyi STMIK Supra Even Semester 2008/2009 June 4th, 2009

2. About Me • Yumarsono Muhyi • Head of Information System Dept., STMIK Supra • Undergraduate of Electrical Engineering, Telecommunication - ITB • Management Magister, Sistem Informasi - UPN (final semsester dan thesis) • Research Field: Computation, Operational Research, Optimation, Simulation • y.muhyi@gmail.com (email and chat) • y.muhyi@yahoo.com (mostly chat) • 0856-9117-2669 / (021) 93131-633

3. Lessons • Introduction • System Classifications • High-Level Flow Chart Basics • Components and Events to Model • Data to Be Included in the Model • Output Data

4. 1. Introduction • A system is a group of components that receives inputs and delivers outputs. • The system definition and model formulationprocess consists of determining: • The system classification • How much of the system to model • What components and events to model • What input data to collect • What output data to generate with the model • By defining our system andformulating the model nearly simultaneously, we are in a better position to understand how the systemcomponents will be modeled.

5. 2. System Classifications • Systems can be classified with respect to two different dimensions: • A system may be discrete,continuous, or combined. • A system is either terminating or non-terminating.

6. Discrete Event Systems • Systems that jump between events are considered as discrete event systems (with respect to time). • It is important to note that the type of entities in the system can cause the way that the system jumps between events. • Entities that are also individual or discrete in nature promote the advancement of the clock in discrete jumps. • Examples of discrete event systems include: • Stores • Service centers • Manufacturing facilities • Transportation centers

7. Continuous Event Systems • The system’s(or some components of the system) status is continuously changing with respect to time. • Systems that are continuous usually involve some sort of fluid or fluid-like substance. • Continuous event systems must be modeled with differential equations. • Examples of continuous event systems include: • Water treatment plants • Chemical industries not including distribution points

8. Combined Event Models • Combined event models contain both discrete and continuous components. • This type of situation occurs in many processing plants where the fluid orfluid-like substance is canned or packaged. • Combined event systems are typically the most difficult type of system to model. • Examples can be found in: • Food industries • Chemical distribution points

9. Terminating versus Non-terminating • Terminating and non-terminating systems are distinguished by: • Initial starting conditions • Existence of a natural terminating event • Initial Starting Conditions: • Terminating systems generally start each time period withoutany influence from the previous time period. • The non-terminating system may begin with entities already inthe system from the previous time period. • Existence of a Natural Terminating Event: • The existence of naturally occurringterminating events means that these systems may be classified as terminating systems.

10. Statistical Analysis Approach Based on Type of Simulation • Terminating system analysis issignificantly easier to perform than non-terminating analysis. • For this reason, many practitioners incorrectlymodel and analyze non-terminating systems as terminating systems. • Practitioners who are notconfident with the non-terminating system analysis approach may attempt to modify the system in orderto use the less demanding terminating system approach. • The usual technique is to look at only a smallperiod during the long non-terminating system run and to use a terminating system analysis approach.

11. 3. High-Level Flow Chart Basics • There are four basic flow chart process symbols. These are the: • Oval • Rectangle • Tilted parallelogram • Diamond

12. Start and Stop Oval

13. Process Rectangle

14. Input/Output Tilted Parallelogram

15. Decision Diamond

16. Sample Flow Chart

17. 4. Components and Events to Model • Components: • Personnel • Machines • Transporters • Conveyors • Processes and Events: • Service System Processes and Events • Service Processing • Payment for the Goods or Services

18. Manufacturing System Processes and Events • Components: • Types of job orders • Machine queue behavior • Machine processing • Machine buffers • Material transportation • Machine failures • Preventive maintenance • Product inspection failures

19. Input data: Input Data Collection Principles Types of Input Data Interarrival Times Batch Sizes Balking, Reneging, and Jockeying Classifications Service Times Failure Rates Scheduled Maintenance Break Times Movement Times Output data: Primary Measure of Performance: Average time in the system Average time in a queue Time average number in queue Average utilization rates Counters Counters 5. Data to Be Included in the Model

20. The End • Discussion. • Question and answer. • Case study.