jonathan atzmon, ise/etm dr. joan burtner, advisor last revised 03/03/15 atzmon etm 691.001,...
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Jonathan Atzmon, ISE/ETMDr. Joan Burtner, Advisor
Last Revised 03/03/15
Atzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 1
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Background
Atzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 2
Modeling and simulation (M&S) allows for the evaluation of process improvement activities
Variety of applications of M&SHistory of M&SArena expands the M&S market
Summary of Research1) A Review of the Literature Concerning Queuing Theory2) A Review of the Literature Concerning Modeling and
Simulation3) Process Improvement Using Arena Simulation Software4) Discrete Event Simulation for Healthcare Organizations: A
Tool for Decision Making5) A Guide for Building Hospital Simulation Models6) Study on the Effect of Different Arrival Patterns on an
Emergency Department’s Capacity Using Discrete Event Simulation
7) Emergency Department Simulation and Determination of Optimal Attending Physician Staffing Schedules
8) Designed to Fail: How Computer Simulation Can Detect Fundamental Flaws in Clinic Flow
9) A Simulation Model of a Hospital’s Clinical Laboratory10) Using Queuing Theory and Simulation Model to Optimize
Hospital Pharmacy PerformanceAtzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 3
Home Screen
Atzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 4
General Arena (version 14.5) Model
Default Menu Bar & Toolbar
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General Arena (version 14.5) Model
Flowchart of the General Model
Atzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 6
General Arena (version 14.5) Model
Create ModuleLocated in the Basic Process template panelCreate Module
Generates entities that flow through the modelName = Entities Arrive to ProcessEntity Type = EntityType of Time Between Arrivals = ScheduleSchedule Name = Arrival Schedule
Schedule Module(Arrival Rate, Duration) = (40, 1); (35, 1); (25,
2); (0, 1); (35, 1); (25, 2); and (35, 1)
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General Arena (version 14.5) Model
Process ModuleLocated in the Basic Process template panelSimulates an amount of time for an entity to perform or
undergo some type of procedureName = ProcessLogic
Action = Seize Delay Release Resources
Type = Resource Resource Name = Process Resource Quantity = 1
Delay Type = Triangular Units = Minutes Minimum = 1 Value (Most Likely) = 2 Maximum = 3
Atzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 8
General Arena (version 14.5) Model
Variable & FailuresVariable
Placed above the Process moduleIndicates the current number of entities in the queue
waiting to be processed by the Process ResourceFailures
File/Template Panel/Advanced ProcessAllows for the simulation of resource downtimeResource Module
Failure Name = Resource Failure Failure Rule = Preempt
Failures Module Type = Time Up Time = 4 hours Down Time = 1 hour
Atzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 9
General Arena (version 14.5) Model
Decide ModuleLocated in the Basic Process template panelSimulates decision-making based on chance
or a conditionName = DecideType = 2-way by ChancePercent True (0 – 100) = 15
Atzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 10
General Arena (version 14.5) Model
Dispose ModuleLocated in the Basic Process template panelRemoves entities from the modelRecords entity statistics for the reportName = Entities Depart Process
Atzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 11
General Arena (version 14.5) Model
Record ModuleLocated in the Basic Process template panelName = Record # of Entities Sent to True
NodeType = CountValue = 1Counter Name = # of Times Entities Sent to
True Node
Atzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 12
General Arena (version 14.5) Model
Assign ModuleLocated in the Basic Process template panelName = Change Entity PictureAssignment
Type = Entity PicturePicture.Box
Atzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 13
General Arena (version 14.5) Model
Plot of the Measure of InterestData Series tab/Add buttonSeries 1 Properties/Source Data/ExpressionBasic Process Variables/Queue/Current Number
in QueueAxes tab
Maximum value of the Time (X) Axis = 540MajorIncrement value of the Time (X) Axis = 60Maximum value of the Left Value (Y) Axis = 40AutoScaleMaximum = False
Titles tabHeader’s Text = Number in Process Queue
Legend tabUncheck the Show Legend menu option
Atzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 14
General Arena (version 14.5) Model
Running the ModelRun/Setup
Project Parameters Project Title Analyst Name Statistics Collection
Reports Category Overview
Replication Parameters Replication Length Base Time Units Number of Replications
Run/Check ModelPlay button
Atzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 15
General Arena (version 14.5) Model
Reduction of the Queue LengthScenario 1 – Base Scenario
No changes to general model previously definedScenario 2 – Probability Distribution of the Process
Use Arena’s Input Analyzer to develop a probability distribution of the Process delay Data file in the format Formatted Text (Space Delimited) File/New File/Data File/Use Existing Fit/Fit All
Weibull distribution with scale parameters (β, α) = (0.734, 0.795)
Scenario 3 – Increased Capacity of the ResourceIn the Resource module, change the capacity of the
Process Resource from one to twoAtzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 16
Arena’s Input and Output Analyzer
Reduction of the Queue Length (Continued)
Number of Replications = 100Statistic module
Name = # Entities in Process QueueType = OutputExpression = NQ(Process.Queue)Report Label = # Entities in Process QueueOutput File = scenario#
For # is 1, 2, or 3
Atzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 17
Arena’s Input and Output Analyzer
Reduction of the Queue Length (Continued)
One-Way Analysis of Variance (ANOVA)Objective = Determine which scenario resulted
in the smallest number of entities in the Process queue
Procedures Arena’s Output Analyzer/Analyze/One-Way ANOVA Add the three data files (one for each scenario) with
the replications lumped Comparison Method = Tukey Confidence Level = 0.95
Atzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 18
Arena’s Input and Output Analyzer
Reduction of the Queue Length (Continued)
One-Way Analysis of Variance (ANOVA)Purpose = Compare the mean number of
entities in the Process queue for each of the three scenarios
Hypotheses H_0: μ_1 = μ_2 = μ_3 H_1: At least one scenario differed in the mean
number of entities in the Process queue
Atzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 19
Arena’s Input and Output Analyzer
Reduction of the Queue Length (Continued)
One-Way Analysis of Variance (ANOVA)Results
Atzmon ETM 691.001, Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 20
Arena’s Input and Output Analyzer
Research OpportunitiesBusiness, industry, education, healthcare,
and governmentProcess Improvement Tools
One-Way ANOVAControl ChartsCheck SheetsPareto ChartsCause-and-Effect DiagramsDefect Concentration DiagramsScatter Plots
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Further OpportunitiesResources
Courses: ISE 403 – Modeling and Simulation; ETM 607 – Modeling and Simulation
Dr. Scott Schultz; Dr. Pablo Biswas YouTube
Other ApplicationsFit a statistical distribution to a data set using
Arena’s Input AnalyzerOther modeling capabilities such as forklifts
and conveyor beltsReminder = ONE directory folder per project
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