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The Arena modeling system is a flexible and powerful tool that allows analysts to create animated simulation models that accurately represent virtually any system.

Arena employs an object-oriented design for entirely graphical model development. Simulation analysts place graphical objects—called modules—on a layout in order to define system components such as machines, operators, and material handling devices.

A programming paradigm that uses "objects" to design applications and computer programs.

Classical terms: class, object, method…

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1 - ARENA DISCRETE EVENT SIMULATION SOFTWARE

In Arena, modules are the flowchart and data objects that define the process to be

simulated. All information required to simulate a process is stored in modules.

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2 - THE CORE OF THE SOFTWARE

The core technology of Arena is the SIMAN simulation language.

Arena is a Microsoft® Windows® compliant product. The entire product is written in object-oriented Visual C++™. This allows users to leverage Microsoft’s open architecture to integrate external data and applications with Arena models.

Other possible connections: Microsoft Office, ActiveX, ODBC, Visual Basic.

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3 - FLOWCHART MODEL DEVELOPMENT

Arena was designed to make creating simulation models an entirely graphical process. All system behaviors are represented by using graphical modules. For system logic such as IF/THEN/ELSE-type branching and queue selection rules, the user creates a flowchart of his system by placing the appropriate graphical modules on the Arena layout and directly connecting these modules.

Model – Simulate – Visualize - Analyze

Before opening the program (which will approximately happen in Slide 10), let us speak about SOME components: entities, resources,

queues, variables, processes.

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3.1 - Entities

Entities are dynamic elements that pass through the system.

Entities are distinguished by their attributes.

Entities must be created to get them into the module and are disposed when they leave.

Attributes must be numerical values.

You may have different types of entities in the same model.

As we build the flowchart, it’s helpful to think of the process from the perspective of the entity.

The trigger for an action to be accomplished is the arrival of an entity.

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3.2 - Resources

Resources have a name and a capacity (number of identical units of the resource).

Resources may have a schedule (how many of them are available and when).

Resources are automatically defined by some modules (e.g., Process).

Resources can be defined manually, and the properties of all resources can be edited in the same way.

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3.3 - Queues

Entities queue when they need processing

An entity tries to seize a resource.

The time the entity uses the resource is the delay.

If the resource is not available, the entity waits in a queue.

The entity releases the resource when processing is complete.

Queues are created automatically by some modules (e.g., Process), and can be defined manually.

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3.4 - Variables

Arena allows the user to work with simulation variables. They contain information about particular dimensions of the model.

Many of them are built-in.

Time Attribute Variables, Cost Attribute Variables…

Variables can be referenced in modules, can be reassigned a new value with a particular module, and can be used in any expression.

See the “Variables Guide”

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3.5 - Processes

Entity must be processed.

This activity is performed by one or more resources and requires some time to complete.

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An Entity Generator…

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3.6 – Until Now

A Process……The Entity …Its Queue…

…And The Resource

The Output

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4 - OPENING THE PROGRAM

(Turn on the PC ) Start Programs Rockwell Software Arena

Project Bar

Spreadsheet View

Flowchart View

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4.1 – The Three Regions

The Project Bar hosts panel with the primary types of object to work with.

Basic Process, Advanced Process, Advanced Transfer Panels

Reports Panel

Navigate Panel

The Flowchart View is the real environment and it will contain all of your model graphics, including the process flowchart, animation, and other drawing elements.

The Spreadsheet View displays model data, such as times, costs, and other parameters.

Here the objects are connected by a particular instrument: there is no difference between data

connectors and logical connectors.

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4.1.1 – THE PROJECT BAR

We will mainly work with Basic Process modules.

The modules are the classes.

As you drag a module to the Flowchart View, you create an instance of that module; thus, you have an object.

It is a “visual representation” of object-oriented programming language (such as Java or VB.NET).

Esempio Classe: ASTRONAVE

Esempio Oggetto: MILLENNIUM FALCON

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4.1.1.1 – The Main Modules /1

Push (possibly) batches of entities into the model with a (possibly) random time between.

Models Queue-Seize-Delay-Release of Resource, or any part of this (like pure Delay).

Make decisions about where to go next based on conditions or chance.

Take entities out of the model and (perhaps) record statistics.

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4.1.1.1 – The Main Modules /2

Assign values (especially Attributes) when an entity passes through.

Record information when entities pass through, typically statistics on entities.

Combine multiple entities into a single entity.

Split multiple entities that were combined, or duplicate a single entity.

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4.1.2 – THE SPREADSHEET VIEW

Each time you create an instance of an object, you have to define its attributes, in order to completely definite it.

These attributes can be set in the prompt window obtained by double-clicking on the object itself.

You can see all the attributes of the modules watching the spreadsheet in the corresponding window.

There are elements not represented by modules: their attributes can only be set via spreadsheet.

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4.2 – Probability Distributions

Working with ARENA, you will have to spend very much time with probability distributions. Luckily, the software contains a set of built-in functions.

These distributions appear on pull-down menus in many Arena modules where they’re likely to be used.

To see them all together, you have to look for the filed “Expression” and follow the hints given by the program.

Beta, Continuous, Discrete, Erlang, Exponential, Gamma, Johnson, Lognormal, Normal, Poisson, Triangular, Uniform, Weibull

Probability distributions let you generate random numbers. The correct distribution can be known a

priori or can be obtained from an analyzer.

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4.3 - Analyzers

The Input Analyzer is useful for determining an appropriate distribution for input to an Arena model. The Input Analyzer allows the user to take raw data and fit it to a statistical distribution which can be incorporated directly into your model.

The Output Analyzer is used to display and analyze model data after the simulation run (or runs) has been performed. The Output Analyzer also provides analysis features such as confidence intervals.

Both the Input and Output Analyzers are directly available on the Arena Tools menu.

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4.4 – Internal Variables

Arena keeps a number of internal variables continually updated.Create – Name.NumberOutProcess – Name.NumberIn, Name.NumberOut, Name.WIP, Name.WaitTimeDecide - Name.NumberOut True, Name.NumberOut FalseAssign – Name.NumberOutBatch – Name.NumerOutSeparate – Name.NumberOut Orig, Name.NumberOut DupRecord – Name.NumberOutDispose – Name.NumberOut

The time on the simulation clock is accessible through the Arena variable TNOW.

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4.5 – The Menus

• File – Classic Windows File Menu

• Edit – Classic Windows Edit Menu

• View – Zoom, grid, layers, toolbars

• Tools – Input/Output Analyzer, Add-Ins, VBA

• Arrange – Drawing, group, rotate

• Module – Connections, panel, breakpoint

• Run – Run, check, pause step through

• Windows – Classic Windows Windows Menu

• Help – Help about Arena

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4.6 - Running

Go Step Fast-Forward Pause Start Over End

Check Model Like compilingReview Errors For most recent checkView Results Summary for most recent runSIMAN See, save underlying SIMAN filesCommand Interactive command-line windowBreak Set times, conditions to interruptTrace Generate detailed historyWatch Watch a variable or expression during runReport See a numerical status when pausedSetup Alter run conditionsSpeed Control speed of animation display

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5 - AN EXERCISE /1

The first model we are going to build is a single server queuing model. The underlying system can be defined as follows.

- Customers arrive in the system one at a time.

- The inter-arrival times, follow a certain probability distribution.

Further assumptions of the arrival process are not made at this point.

- There is a single server that can serve one customer at a time.

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5 - AN EXERCISE /2

- The processing times follow a certain probability distribution.

Further assumptions of this distribution are not made yet.

- If the server is busy at the time when a customer arrives in the system, the customer is placed in a queue to wait for the server to become free.

- The customers in the queue are served according to FIFO queuing discipline, i.e. the first of the customers to arrive in the queue is served first.

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5.1 – Performance Figures /1

Expected average queuing time of a customer

D is the delay in queue of the ith customer.

Expected average number of customers in the queue

Q(t) is the number of customers in queue at time t and T(n) the total

simulation time when simulatingthe passage of n customers

through the system.

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5.2 – Performance Figures /2

Utilization of the server

Let B(t) be 0, if the server is idle at time t and 1, if it is working.

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5.3 – The Model With Arena

Now, your model should look like the following picture.

The create-module represents the arrival of customers into the system. The process module represents customer service and the dispose-module represents the departure of customers from the system.

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5.3.1 – THE CREATE MODULE

Correct namingName-field: Customer arrivalsEntity type-field: Customer

Distribution of inter-arrival time of customersConstant inter-arrival time of 1 hour

Parameters- Entities per arrival: 1 – It states that each customer arrives alone.- Max arrivals: 3 – Defines the maximum number of customers created during the simulation.- First creation: 0 – The first customer is created at time 0.

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5.3.2 – THE PROCESS MODULE /1

The process-module defines, what happens during customer service.

Correct namingName-field: Customer serviceEntity type-field: Standard

Define the logic of the processAction-field: Seize-Delay-ReleaseThis means that an entity that is being processed first takes the control of (seizes) the required resources. Then, the entity experiences a processing delay and, when done, releases the control of the resources it has held.

The resource is seized and released. The activity is delayed.As we selected Seize-Delay-Release, a queue named Customer service.Queue was automatically created by Arena to handle

entities that wait for service.

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5.3.2 – THE PROCESS MODULE /2

Selecting the Seize-Delay-Release option opens another field named Resources to define what resources are required to complete the task. Click Add and define in the opening dialogue box: Type Resource, Name Server and Quantity 1.

The Server resource takes care of customer service and serves 1 customer at a time.

Lastly, define a constant 2 hour processing delay.

Still, make sure that the Report statistics option is selected and leave the dialogue box.

This value is the number of resources simultaneously used by the resource.

The capacity of the resource (how many resource-items are in the system) must be edited in the spreadsheet

field.

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5.3.3 – THE DISPOSE MODULE

Correct namingName-field: Departures

Check that the Record entity statistics -option is selected.

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5.4 - Simulation

Our model is now complete and we can start simulating. The specifics of the simulation run are defined by selecting from the Run-menu Setup.

Our simulation ends when the three entities leave the system. So, we don’t need to make specifications. Usually, it is possible to specify the run simulation length.

Start the simulation by selecting Go from the Run-menu and wait.

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5.5 – Viewing The Results /1

The type of report that Arena will show is by default the Category overview –report. It basically lists the values of all performance indicators for which the statistics collection option was activated.

Remember that we used constant inter-arrival (1 hour) and processing times (2 hours) as input data and created only 3 customers.

This allows us to say, without simulating the system, that the expected average queuing delay for a customer is 1 hour, the expected average queue length is 0.5 and that the server utilization is 1.

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5.5 – Viewing The Results /2

The simulation results should tell us exactly the same thing and allow us to be a little more confident about the implementation of the model.

Now, go through the report and locate the values of Wait time in the Entity-category, Number waiting in the Queue-category as well as Instantaneous utilization in the Resource-category.

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BIBLIOGRAPHY

• Arena Software Tutorial; David A. Takus, David M. Profozich

• Simulation with Arena, Chapter 4; Working with Arena

• Mat-2.170 Simulation Spring 2006, Exercise 3 – Introduction to Arena Software

• Arena Basics; ISyE 6644; Seong-Hee-Kim (Georgia Tech), Barry Nelson (Nortwestern)

• Arena User’s Guide; Doc ID ARENA-UM001A-EN-P