ISE 195
Introduction to Industrial
Engineering
Lecture 2
Modeling and Simulation
(Topic of ISE 471 System
Performance Modeling)
Simulation Is …
Simulation – very broad term – methods and
applications to imitate or mimic real systems,
usually via computer
Applies in many fields and industries
Very popular and powerful method, in fact many
surveys list simulation as among the most used
techniques
Today’s goal – Cover general ideas, terminology,
examples of applications, good/bad things, kinds
of simulation, software options, how/when
simulation is used
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Simulation Is …
Simulation is the process of designing a model of a
real or imagined system and conducting experiments
with that model
The purpose of simulation experiments is to
understand the behavior of the system or evaluate
strategies for the operation of the system
 Simulation is a “descriptive” technique, it generally requires
something to evaluate
Definition of Simulation: The technique of imitating
the behavior of some situation or system by means of
an analogous model, situation, or apparatus, either to
gain information more conveniently or to train
personnel.
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Systems
System – facility or process, actual or planned
 Many Examples …
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Manufacturing facility
Bank or other personal-service operation
Transportation/logistics/distribution operation
Hospital facilities (emergency room, operating room, admissions)
Computer network
Freeway system
Business process (insurance office)
Criminal justice system
Chemical plant
Fast-food restaurant
Supermarket
Theme park
Flight-line maintenance modeling
Simulator training systems
Emergency-response system
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What is a Model in Engineering?
A system used to study another system
 Physical: A prototype or mock-up of a system
 Live-action exercises
 Flight Simulators
 Mathematical
 Systems of Simultaneous Linear Equations
 “Closed Form” expressions (Force = mass x acceleration)
 Logical
 A chemical reaction
 Description of input/output of a logic circuit
 Computational: A combination of logical and mathematical with a
computer engine
 Numerical methods
– Newton’s method for finding a minimum of a convex function
– Iterative solutions to differential equations
 Computer Simulation: Using a computer-based model to mimic a real
system as it evolves through time
– Includes both mathematical aspects and logical aspects
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Example 1
An example of a “simulation” from the mechanical
engineer’s perspective
Vehicle Suspension Simulation (Inventor)
 http://www.youtube.com/watch?v=L0R5elR6nck
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Why Not Work With the Actual
System?
Study the system – measure, improve, design,
control
 Maybe just play with the actual system
 Advantage — unquestionably looking at the right thing
 But it’s often impossible to do so in reality with the
actual system
 System doesn’t exist
 Would be disruptive, expensive, or dangerous
 Examples:
 Examine configurations without disrupting manufacturing
operations
 Examine customer flows without re-configuring the store
 Examine new tactics without endangering planes or people
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Using Models
Study the model instead of the real system …
usually much easier, faster, cheaper, safer
Can try wide-ranging ideas with the model
 Make your mistakes on the computer where they don’t
count, rather than for real where they do count
Often, just building the model is instructive –
regardless of results
Model validity (any kind of model … not just
simulation)
 Care in building to mimic reality faithfully
 Level of detail incorporated must be determined
 Should get same conclusions from the model as from
system
 More on this during verification and validation material
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Studying Mathematical
or Logical Models
If model is simple enough, use ISE mathematical
analysis … get exact results, lots of insight into
model
 Queueing theory
 Differential equations
 Linear programming
But complex systems can seldom be validly
represented by a simple analytic model
 Danger of over-simplifying assumptions … model
validity?
 The simplified model can provide valid bounds
Often, a complex system requires a complex
model, and analytical methods don’t apply …
what to do?
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Simulation is just a
sampling experiment
that is performed
using a model.
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When Should We Use Computer
Simulation?
Can be used to study simple systems
 Usually not necessary if an analytical solution is
available
 You will often study simple systems via simulation in
classwork, its worth the effort to search for a
Real power of simulation is in studying complex
models
 Simulation can support complex models
Good for comparing alternative designs
 More complex techniques allow “optimization” using a
simulation model
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Advantages of Simulation
Flexibility to model things as they are (even if
messy and complicated)
 Avoid looking where the light is:
You’re walking along in the dark and see someone on hands and knees
searching the ground under a street light.
You:
“What’s wrong? Can I help you?”
Other person:
“I dropped my car keys and can’t find them.”
You:
“Oh, so you dropped them around here, huh?”
Other person:
“No, I dropped them over there.” (Points into the darkness.)
You:
“Then why are you looking here?”
Other person:
“Because this is where the light is.”
Allows uncertainty, nonstationarity in modeling
 The only thing that’s for sure: nothing is for sure
 Danger of ignoring system variability
 Model validity - is the system correctly captured
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Advantages of Simulation (cont’d.)
Advances in computing/cost ratios
 Estimated that 75% of computing power is used for
various kinds of simulations
 Dedicated machines (e.g., real-time shop-floor control)
Advances in simulation software
 Modern Tools are far easier to use (GUIs)
 There is a down-side to this
 No longer as restrictive in modeling constructs
(hierarchical languages exist, can program down to C)
 For ISE 471 we use ARENA
 Statistical design & analysis capabilities
 However, practitioners do not solely rely on these packaged
results
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Dangers of Simulation Modeling
Tendency to be too convinced by results without
validation of the model
 Animation is very compelling
 Numbers are very compelling
Results must be checked using statistical
techniques
 Did you collect enough data?
 Are you sure of your conclusions?
 How sure are you about your conclusions?
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ISE Simulation Models
Monte Carlo Simulation
 Using “Sampling” to estimate measures from systems
NCAA Tournament Pool Example
 Can you estimate the probability of picking the national
champion in Basketball if you could assign probabilities
to each game in your bracket?
 Could use probability theory, if you knew how to combine
probabilities
 Could use simulation to try it out many times on the computer,
and see what happens in many trial runs of the tournament
 Wayne Winston’s Simulation of the 2010 NCAA Men’s
Basketball Tournament
– http://waynewinston.com/wordpress/?p=509
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Example – Monte Carlo Model
in a Spreadsheet
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Discrete Event Simulation
“A model of a system as it evolves over time
where the state of the system changes at discrete
points in time”
Necessary when systems involve humans and
logical connections between components
The “engine” of common ISE simulation software
is built on the discrete event approach:
ARENA (used in ISE 471), FlexSim, etc.
The “interface” for the common ISE simulation
software is built on the “process flow” approach.
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Process Flow Description of Systems
Systems consist of:
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Entities (Customers, Parts)
Resources (Machines, People)
Routings (Logic, Networks)
Input Data (Times, Probabilities)
Performance Measures (Times, Utilizations)
ARENA Model of a Single Server System
 (Service Counter at a Bank)
ARENA Model of a Truck Assembly Line
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Example 2: Traffic Simulators
Vehicle Intersection Model with Pedestrians
(VisSim)
 http://www.youtube.com/watch?v=Yq9IAzNTAz0&featur
e=related
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Example 3: Agent Based Models
Subway Station Simulation: AnyLogic Subway
Entrance Hall Model
 http://www.xjtek.com/anylogic/demo_models/?applicati
on_area=Pedestrian++Dynamics
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Some Primary Uses of Simulation
Models in Operations
Find the bottlenecks
How are resources utilized
Capacity planning
Impact of configuration changes
Understand the system dynamics
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Questions?