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IF-UTAMA1 Simulation Sesi 12 Dosen Pembina: Danang Junaedi.

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Presentation on theme: "IF-UTAMA1 Simulation Sesi 12 Dosen Pembina: Danang Junaedi."— Presentation transcript:

1 IF-UTAMA1 Simulation Sesi 12 Dosen Pembina: Danang Junaedi

2 IF-UTAMA2  In DSS, simulation refers to a technique for conducting experiments with a computer on a model of a management system.  Major Characteristics of Simulation –Simulation imitates reality and capture its richness –Simulation is a technique for conducting experiments It can describe and/or predict the characteristics of a given system under different circumstances. –Simulation is a descriptive not normative tool –Simulation is often used to solve very complex, risky problems Simulation

3 IF-UTAMA3 What is Simulation

4 IF-UTAMA4 Problem:  Siemens Solar Industries (SSI), the world’s largest maker of solar electric products, suffered continuous problems in poor material flow, unbalanced resource use, bottlenecks in throughput & schedule delays. Solution:  SSI built a cleanroom contamination-control technology.  The simulation provided a virtual laboratory for engineers to experiment with various configurations before the physical systems were constructed. Results:  SSI improved their manufacturing process significantly.  The cleanroom facility saved SSI over $75 million/ year. Case : Simulation Saves Siemens Millions

5 IF-UTAMA5 Advantages and Disadvantages of Simulation Slow and costly construction process Cannot transfer solutions and inferences to solve other problems So easy to sell to managers, may miss analytical solutions Software is not so user friendly

6 IF-UTAMA6 Set up a model of a real system and conduct repetitive experiments 1. Problem Definition 2. Construction of the Simulation Model 3. Testing and Validating the Model 4. Design of the Experiments 5. Conducting the Experiments 6. Evaluating the Results 7. Implementation Simulation Methodology

7 IF-UTAMA7 Probabilistic Simulation –Discrete distributions : systems monitor the systems each time a change in its state takes place –Continuous distributions : system monitor changes in a state of system at descret points in time –Probabilistic simulation via Monte Carlo technique –Time Dependent versus Time Independent Simulation –Simulation Software –Visual Simulation –Object-oriented Simulation Simulation Types

8 IF-UTAMA8 Simulation Development

9 IF-UTAMA9 Some Applications of Simulation

10 IF-UTAMA10 Visual Spreadsheets User can visualize models and formulas with influence diagrams Not cells--symbolic elements

11 IF-UTAMA11 Visual Interactive Modeling (VIM) and Visual Interactive Simulation (VIS) Visual interactive modeling (VIM) Also called –Visual interactive problem solving –Visual interactive modeling –Visual interactive simulation Use computer graphics to present the impact of different management decisions. Can integrate with GIS Users perform sensitivity analysis Static or a dynamic (animation) systems

12 IF-UTAMA12 Generated Image of Traffic at an Intersection from the Orca Visual Simulation Environment (Courtesy Orca Computer, Inc.)

13 IF-UTAMA13 Visual Interactive Simulation (VIS) Decision makers interact with the simulated model and watch the results over time Visual interactive models and DSS –Queueing

14 IF-UTAMA14 Monte Carlo Simulation

15 IF-UTAMA15 Monte Carlo Technique

16 IF-UTAMA16 Step 1. Probability Distribution

17 IF-UTAMA17 Step 2. Building a Cumulative Probability Distribution

18 IF-UTAMA18 Step 3. Setting Random Number Interval

19 IF-UTAMA19 Step 4. Generating Random Numbers

20 IF-UTAMA20 Step 5. Simulating the Experience


22 IF-UTAMA22 Simulation of Queuing Problem

23 IF-UTAMA23 Queuing Problem

24 IF-UTAMA24 Dist 1. Interval Arrival Times Dist 2. Unloading Times

25 IF-UTAMA25 Example

26 IF-UTAMA26 Example-contd : Some Simple Statistic

27 IF-UTAMA27 Simulation and Inventory Analysis The Basic Model

28 IF-UTAMA28 Referensi 1.Dr. Mourad YKHLEF,2009,Decision Support System-Simulation, King Saud University 2.Richard K. Min.2002.Information Systems for Management. OUR LADY OF THE LAKE UNIVERSITY SCHOOL OF BUSINESS 3.Insoo Hwang.-. Modeling and Analysis. Department of MIS, Jeonju university 4.Efraim Turban and Jay E. Aronson.2001. Decision Support Systems and Intelligent Systems 6th edition. Prentice Hall

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