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Simulation
Lecture
6
Simulation
Chapter 18S
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Simulation
Simulation Is …
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Simulation – very broad term
 methods and applications to imitate or mimic real
systems, usually via computer
Applies in many fields and industries
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Simulation models complex situations
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Models are simple to use and understand
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Models can play “what if” experiments
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Extensive software packages available
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ARENA, ProModel
Very popular and powerful method
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Simulation
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Examples
Manufacturing facility
Bank operation
Airport operations (passengers, security, planes, crews,
baggage)
Transportation/logistics/distribution operation
Hospital facilities (emergency room, operating room,
admissions)
Freeway system
Business process (insurance office)
Fast-food restaurant
Supermarket
Emergency-response system
Military
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Simulation
A Simulation Model
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Simulation
Electronic Assembly/Test System
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Produce two different sealed elect. units (A, B)
Arriving parts: cast metal cases machined to accept the
electronic parts
Part A, Part B – separate prep areas
Both go to Sealer for assembly, testing – then to Shipping
(out) if OK, or else to Rework
Rework – Salvaged (and Shipped), or Scrapped
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Simulation
Part A
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Interarrivals: expo (5) minutes
 From arrival point, proceed immediately to Part A
Prep area
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Process = (machine + deburr + clean) ~ tria (1,4,8)
minutes
Go immediately to Sealer
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Process = (assemble + test) ~ tria (1,3,4) min.
 91% pass, go to Shipped; Else go to Rework
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Rework: (re-process + testing) ~ expo (45)
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80% pass, go to Salvaged; Else go to Scrapped
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Simulation
Part B
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Interarrivals: batches of 4, expo (30) min.
 Upon arrival, batch separates into 4 individual
parts
 From arrival point, proceed immediately to Part B
Prep area
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Process = (machine + deburr +clean) ~ tria (3,5,10)
Go to Sealer
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Process = (assemble + test) ~ weib (2.5, 5.3) min.,
different from Part A, though at same station
 91% pass, go to Shipped; Else go to Rework
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Rework: (re-process + test) = expo (45) min.
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80% pass, go to Salvaged; Else go to Scrapped 7
Simulation
Run Conditions, Output
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Start empty & idle, run for four 8-hour shifts
(1,920 minutes)
 Collect statistics for each work area on
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Resource utilization
 Number in queue
 Time in queue
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For each exit point (Shipped, Salvaged, Scrapped),
collect total time in system (a.k.a. cycle time)
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Simulation
Simulation Models Are Beneficial
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Systematic approach to problem solving
 Increase understanding of the problem
 Enable “what if” questions
 Specific objectives
 Power of mathematics and statistics
 Standardized format
 Require users to organize
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Simulation
Simulation Process
1.
Identify the problem
2.
Develop the simulation model
3.
Test the model
4.
Develop the experiments
5.
Run the simulation and evaluate results
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Repeat 4 and 5 until results are satisfactory
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Simulation
Monte Carlo Simulation
Monte Carlo method: Probabilistic simulation
technique used when a process has a random
component
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Identify a probability
distribution
Setup intervals of
random numbers to
match probability distribution
Obtain the random numbers
Interpret the results
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Simulation
Different Kinds of Simulation
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Static vs. Dynamic
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Continuous-change vs. Discrete-change
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Can the “state” change continuously or only at
discrete points in time?
Deterministic vs. Stochastic
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Does time have a role in the model?
Is everything for sure or is there uncertainty?
Most operational models:
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Dynamic, Discrete-change, Stochastic
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Simulation
Advantages of Simulation
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Solves problems that are difficult or
impossible to solve mathematically
 Flexibility to model things as they are (even
if messy and complicated)
 Allows experimentation without risk to
actual system
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Ability to model long-term effects
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Serves as training tool for decision makers
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Simulation
Limitations of Simulation
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Does not produce optimum solution
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Model development may be difficult
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Computer run time may be substantial
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Monte Carlo simulation only applicable to
random systems
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