manual of simulation with arena for lab - note_3

8/13/2019 Manual of Simulation With Arena for Lab - Note_3

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National Institute of Tecx nologyxalicut Department of Mechanical Engi xex ring1

Model thatxave no rx ndom input aredeterminixtic.

SIMULATION WITH ARENA

Simulation

x to describe thebehavior and str xcture of a comple xreal world system over extended px riods of time [1].

xto a broad collectixn of methods and application to mimic the behaviourof real system usually on a comxuter with app x oxriate softwx re.

What is being modelled

txrixg pl xntithxifx erent kinds of customers, servers, etc.

xgency facility in a hospital

Simulation is a numerical technique for conducting experiments on a digital computer,which involves logical and mathematical relationships that inter

Simulation refer

A manuxax Axankx A distribution network of plants, warehouses and transportation links

An eme Simulation languages

GPSS, SIMSCRIPT, SLAM AN x SIMxN

xa is based on the SIMAN simulation languxge

ions

Are

Arena combines moduxes to build a fairly wide variety of simxlation models.Different kinds of simulax

STAx IC VS DYNA xIC xTime doesnt play a natural role instaticmodel but does indynamicmodels.

xcus onsuchxodels.

Continuous vs Discrete

xanx e continuxusly oxer time.E.g. Levels of a water reservoir falls due to evapxration occur.

xchange canxcc xr only at separated poixts in time.E.g. A manufac xuring sysxem witxparts arrixing and lex ving at specific time

xa is mostly focused in discrete models.

Deterministic vs stochastix

Manufacturing system model describesxynamic model and Arena is primarilxf

InContinuousmodel state of the system can c

In a Discrete mode

Are


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National Institute of Technologyxalicut Department of Mechanical Engineering2

PIECES OF A SIMULATIxx MODELEntities:

The dynamic objects in the simxla xixn thx t move around, change status, affect a xd arexffectedxy other entities and the state oxthe system, and affect the outpuxperformance

E.g. Strict appointment-book with fixed service time

Stochaxticmodels operatex itxat least some inputs being randxx.

E.g. Axank with randomly arx ivingx ustomer requiring varying service times

General-Px rpo xe Languages, Simulation Languages and High-xevelSimulators

Genxral-Purposexanguages:

ully tedious and ex ror p xone

Sim xxation Languages:

tures and how to use themeffectively

High-Level Simulators:

xerate by intuitive graphical use xinte xface, menus and dialoxs

s txey move around and change

acturing or communication)

enerally not flexible

Performance measurestion

xber of parts that were ever waiting in thx xueueota x xime in sysxem

Highly customizable and flexible

But painx

Provide much better framework

Still have to invest a bit ofxime to learn about their fex

Very easy to use

O Select from available simxlation-moxelling constructs,xxnxect them, anxSelect from available simxlation-moxelling constructs,xxnxect them, anxxru

Dynamic graphical animation of system componentsx Domains of many simulators are rather restricted (like manux

x

Total produx

Average waiting time in queue

Maximum waiting time in queue

Time-average number of parts waiting in the queue

Maximum nu Average and maximumx

Utilisation


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Nationx l Institute o xTe xhnologyxalicx t Department o xMechanical Engineering3

They usually ar xcrex ted, move around for a while anxtxen are disposed ( xeave)E.g. parts to be processed, cuxxomers ix a banking syste x, etc

Resources

s often takexhe service from resources.

n available and re xeases it.E.g. Machines, Sex ver

Attribxtex lly attached to individual entitiesE.g. Part entities hx ve attributes ca xled due da xe, prioritx , colour, etc.

(xlobal) Varixbles

teristic of yourxystem, regardxess of howmany or what kinds of entities might be around

s:

xocktime, and so on)

ined variablx s (mean sx rvice time, travel time, current shift, and so on)

Statistical Acx umulat xrsxthe final output performance measures, it is nx cessary to keep track of thevariables as theximxlation progrx ss and such variables are called statistical accumulators

ht chx nge attributes, variablx s orstatistical accumulators

E.g. ArrivalA new px rt entersxhe system,Departurex part finishes its operations (service) and leaves the sx stem

Queues

ntity cant move on (due to unavailability of resource) it needs a place to wait,which is the purpose of a queue.

Simulationx lock

xled the simulation clock

nd event calendar a xe the imxortant pieces of any dynamic simulationStarting andxx opping

ified

t you ar xmodeling

Entitix

An entity seizes a resource whx

Attributes are generx

A piece of information that reflects soxe charax

Many different variables are poxsible in axMany different variables are poxsible in axxode

In Arena there arxtwo types of variablxBuilt-in variables (number-in queue, number of busy servers, current simulation c

User-dex

To ge

Arena take care of mosxof the statistical accumulatioArena take care of mosxof the statistical accumulatioo

EvenArena take care of mosxof the statistical accumulatioArena take care of mosxof the statistical accumulatioo

Evenn

Something that happen at an insxant of time that mix

When anx

Current value of time in txe simulation held in a variable is ca

Simulation clockx

Startinxand stopping conditions should be sxxx

It is imxortant to think about these conditions and make these conditions consistent withwxx


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National Institute o xTechnology Calicut Department of Mechanical Engineering4

You mxy have to think about whe xher it sxould stopx t a particulaxtime or ixshould stopwhen something specific happens (like asxoox x s 100 finisxed parts produxed when aproduction shop is simulatx d)

R xplication

Each r xn starts and stops ax cording to the same rule and uses same input parx metexse xxing (statistically identical) but use separate random numbers (inxependxnt)

ARENA

General-purpose simulation px ckage

xinto model window

ct them, so definxflow of entities

etaixmodules and entities in dialog boxes and in sprx adshext

Process-oriented

High-level (very easy to use by graphical user interfaces, menu and dialogues)

Animation

Model buildinx xonnx

x

Run independent replications

ARENA WINDOx


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Na x ion xl Insti x ute of Txchnology Cali xut Deparx ment of Mechanical Engineering5

Model building

Models are describx d with ARENA vex sion 11

SOME DETAILS FOR ARENA MODELLINGEXAMPLE: A SIx GLE COUNTER TRANSACTION

rive randomly: described by a distribution

Arena model

Customers ax

Transacts business: single counter

Leaves

E.g.: an ATM counterENTRANCE COUNTER EXIT

0... x... 0....

Play the ATM 2.exe file tx know the method of data inputting in this model.

Modules

asixmodules

ate

Advanced modules

Flow chart modules & Data modules

Crx Process

Dispose


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National In xtitute of Technolog xCalicut Departmx nt of Mechanical Engineering6

Creaxe module

Process module

Name Entity type Time between arrixals Entities per arrival

Name Action Resources

Add Delay t xpe


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National Institute of Technolox y Calicx t Departmex t of Me xhax ical Engi xeering8

Run Setup

EXAMPLE 2: A MANUFACTx RING Sx STEM

Stations wixh multiple servers Machine fx ilxres defined xictorial representatioxof machine state

ARENA Model of a Manufax turing system with 4 machines used in seque xcx

Crea te 1 Pro c e s s 1 Pro c e s s 2 Pro c e s s 3 Pro c e s s 4 Di x p x s e 1

00 0 0

00


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National Institute of Tx chnology Calicut Department of Mechanical Enginex ringx

Setting capacities & assigx ingxailures

Failure definition


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National Institut xof Technolog xCalicut Department of Mechanical Engineering10

Machix e state representation

Uxing schedules: for resources & arrivals

EXAMx LE 3: A BANK

Tellers: no. of tellers vary during the day Calendar based xx faultxalue t x pe: numeric

xanager: Availability baxed on time of day Calendar ba x ed Default va xuxtype: state

Arrival: Rate of arrivalxepends on time of day Duration basxd

Customer arrives toxbank; some of the customers collect coupon and proceed to a counter(teller) for processing. Another stream of cusxomer xdirectly goes to a re xeptionist and thenproceedsx itxer to txe Bankxanager o x x orx oupon collex tixn and then txthe counter.

ARENA Modxl


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National Institute of Tx chnology Calicut Department of Mech xnicxl Engineering11

C1

C2

COUPON COUNTE RS E XIT

RECEPTIONT ru e

F a l s e

Decide 1B ANK

MANAGER

0

0

0

x0

0

0

x

0Cxeating schex ules

Click Schedule in Basic Pr xcessAdd and name a new scheduleSelect f xrmx t type

For calendar t xpe Go to: EditCalendar schedules- Time patterns: select the name & edit

For duration type: click durationsxin scheduxe spread sxeet itself & edit

Editing sxhedule


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xational Institute x f Tx chnolx gy Calicut Department of Mechanical Engineeringx2

Numeric value type

Statx type


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National Institute o xTechnology Calicut Departme xxof Me xhanical Engineering13

Assixning the schedule

Forxesources Go to Resource spread sheet,

selx ct the sch xdule name. Schedule rule :preempt

For schedule based arrivals: Edit Create module,

type of arx ival : schedulx

select schedule nameDecision module

2- way bxchance N- way by chance 2- way by condition N- waxby condition

2-wa xby chancx


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Nationx l Institute of Technolox y Calicut Departmx nt of Mech xnical Engineering1x

EXx MPLE 4: ELECTRONIC ASSEMBLY AND TEST SYSTEM

Pax t A prepTRIA(1, x,8)

Part A

EXPO(5)

Part B PrepTRIA(3,5,10)

Part BB ATCHEx O F 4

EXPO(30)

PART A

TRIA(1,3,4)

PART B

x EIx (2.5,5.3)

9%

91%

ReworkEXPO(45) Scrx ppex

20%

80%SALVAG EDAND SxIPPE D

Shipxed

Electronic Asse x bly and Tex t System

Sealer

ARENA MODEx OF THE ABOVE EXAMPLE

part A Arrivx s

p xrt B Arrives

paxt A sealertimeandarrivetime

part B sealertimeandarrix etime

prepA process

prepBpro x ess

sealerprocess

Failedsealerinspec xio xTru x

Fal xe

Rework processfailx dreworkins x ection

True

Fa x se

Recordsc xxppedxx rts

scra x ped

Recordsalvagedparts

salvaged

Recor x shippedparts

shipped

0

0

0

x

0

0

0 0 x

0

0

x

0


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National Insx it xte ofxechnox ogy Cx licut Dx partment of Mechanical Engineering16

Play the electronic 2.xx e file to know the data in xxtting in this model.

REx ERENCE MA xERIAL

[1].Ravindran A., Philips, D. T. a xd Solberx , J. J., (1987) Opera xionsxesearch: Prixciplesand Practices, Second edition, John Wiley & Sons, New York

[2].Book: Kx ltxn,x.D., Sadowski, R.P., and Stux rock, D.T: Simulation with Arx na, FourthEdition, 2007, McGraw Hill (withximited student edition of Arx na oxCD-xom).

[3].I xa coxputer where Arena ixstalled, use the folxowing path:Start/Programs/Rxckwell Software/Arx na/Onxine BooksV xry useful examples are available when you opened Arena in a computer and usxtxehelp. You can uxe Arena help and Arena SMARTx iles from txe help menu

manual of simulation with arena for lab - note_3

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