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Bio
• Eng.D in Production Systems from Ecole des Mines de Paris, France
• Ph.D in Operations Research from MIT
• Research: Revenue Management, DynamicPricing, Auctions, Procurement, StochasticModels of Manufacturing Systems…
• Experience in eCommerce Fulfillment,Electronics, Aeronautics, Transportation andSoftware
Copyright 2003 © Jérémie Gallien
What is Simulation?
Input A OutcomeSystem Model Input B OutcomeSystem
Model
Input B OutcomeReal SystemInput A OutcomeReal
System
Modeling
Scenario Generation
Inference
Validation / Accuracy AssessmentInput Data
Collection Output Data Collection
Copyright 2003 © Jérémie Gallien
Types of Simulation
Static / Monte-Carlo
(Crystal Ball)
Discrete Events
(Simul8)
Continuous Time
(application-specific)
Examples: Examples: Examples:
• Options Contracts • Business Processes • Weather models • Insurance • Education • Engineering design • Demand Models • Military • Scientific research
• Entertainment • Education
Copyright 2003 © Jérémie Gallien
Simulation Module Goals
• Develop the practical skills necessary todesign, implement and analyze discrete-event simulation systems;
Practice of Modeling!!!
• Cover the basic theory underlying discrete-event simulation methods.
Copyright 2003 © Jérémie Gallien
Class Date Topic Reading Assignment
TUT MIT 11/2 SG 11/3 Simul8 Tutorial “Introduction to
Simul8”
1 MIT 11/3 SG 11/4 Introduction, Simulation Process
and Stochastic Modeling ClearPictures, Inc. (in this document)
Proba/Stat Review 1 (in this document)
2 MIT 11/8 SG 11/9
Monte-Carlo Theory and Examples (with Crystal Ball)
“Common Probability Distributions for Simulation Modeling”
3 MIT 11/10 SG 11/11 Discrete-Event Framework and
Examples
4 MIT 11/15 SG 11/16 Design and Analysis of
Simulation Experiments Proba/Stat Review 2 (in this document)
MIT 11/30 SG 12/1
Individual Assignment Due (in this document)
Copyright 2003 © Jérémie Gallien
Optional References
• Law, A. and W. Kelton, Simulation Modelingand Analysis, 3rd ed., McGraw-Hill (2000).
• Ross, S., Simulation, 3rd ed., Academic Press (2002).
• Swain, J., “Power Tools for Visualization and Decision-Making,” OR/MS Today, February2001. Available online at http://www.lionhrtpub.com/orms/surveys/Simulation/Simulation.html
Copyright 2003 © Jérémie Gallien
From the Trenches
“There have been a lot of course changes,basically because I didn't have the problem Iwas trying to solve and the model structure wellthought out before starting. So if I can offer you one piece of advice it would be to spend asmuch time up front as you need thinking aboutexactly what you want to model.”
LFM Intern, 2003
Copyright 2003 © Jérémie Gallien
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The Simulation Process
Define the simulation goal
Model the system
Implement the model
Debug, Validate, Sensitivity
Design the experiment
Run the experiment
Analyze and communicate
• Keep the goal in mind! • Customer feedback!
• Choice of tool is key
• Never skip! • Customer feedback!
• Never skip!
• Use confidence intervals!
• Run length, warm start, variance reduction…
Copyright 2003 © Jérémie Gallien
Simulation Goal
System Design Vs. System Analysis
Strategic? Key Performance Measures?Tactical?
Control?
• What about ClearPictures, Inc.?
Copyright 2003 © Jérémie Gallien
ClearPictures: Simulation Goals
• Estimate the average and standard dev. of delivery leadtime through the pull section;
• Estimate the average and standard dev. of WIP inventory through the pull section;
• Determine the production bottleneck;• Estimate the impact of purchasing more
machines on leadtime and inventory;• …
Copyright 2003 © Jérémie Gallien
System Modeling
• “Everything should be made as simple as possible, but notsimpler.” Albert Einstein.
• The simulation goal should be the guiding light when deciding what to model
• Start to build your model ON PAPER!
• Get client/user feedback early, and maintain model + assumption sheet for communication purposes
• For random variables, collect data and fit distributions… after modeling the system, with sensitivity analysis in mind!
Copyright 2003 © Jérémie Gallien
System Modeling
2a Model on paper
2b User/Client feedback
2c Sensitivity analysis
• Process Flow Diagram, Flow Chart…
• Model assumption sheet!
•
2d Data collection & Fit • Prioritize, mock data example, fitting software
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3 Implement the model
4 Debug, Validate, Sensitivity
2 Model the system
5 Design the experiment
Theoretical: TOC, Queueing theory…
Define simulation goal
Copyright 2003 © Jérémie Gallien
ClearPictures Production ModelSensor Firmware
Test Inspection
assy
Box / Sensor Board Assembly
ST2
ST1 insp.
85%
15% TRIAN[5,10,15]
360
U[15,25] N[9.5,4]
1 2
Exp(12)
Customer Notes and Assumptions:1/ Service time at ST1 is U[13,24] first passage, U[10,15] rework. Rework has priority.2/ There can be at most 1 rework cycle for each part (passes inspection second time).
Copyright 2003 © Jérémie Gallien
Model Implementation
• General programming language (C++, Java…) • Simulation-oriented language (MODSIM…) • Simulation software with GUI (Simul8, Witness…) • Excel Add-in (Crystal Ball, @Risk…)
l Low Low
Si i High High High
Si i High
l Low Low Low
FLEXIBILITY COST REQ. SKILLS DEV. TIME RUN TIME
Genera Prog. Language Very High Very High High
mulat on Language Medium Low
mulat on Software Medium Medium Low Medium
Exce Add-in Lowest High
Copyright 2003 © Jérémie Gallien
Validation & Debugging
• Slow Graphical Animation
• Step-by-step event list
Copyright 2003 © Jérémie Gallien
Experiment Design
• Warm-up Period? • Run Length? • Number of Trials? • How to analyze and interpret the results?
Copyright 2003 © Jérémie Gallien
Class 1 Wrap-Up
Copyright 2003 © Jérémie Gallien
1. Simulation Process
2. Modeling
3. Choice of simulation tool
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