Simulation Text

8/13/2019 Simulation Text

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Simulation-Based Lean Six-Sigma And Design ForSix-Sigma

Basem El-Haik Raid Al-Aomar

Copyright 2006 by John Wiley & Sons, Inc. All rights reserved.

P blished by John Wiley & Sons, Inc., !obo"en, #e$ Jersey.P blished si% lt neo sly in C n d .

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cc r cy or co%pleteness o' the contents o' this boo" nd speci'ic lly discl i% ny i%plied$ rr nties o' %erch nt bility or 'itness 'or p rtic l r p rpose. #o $ rr nty % y be cre ted ore(tended by s les represent tives or $ritten s les % teri ls.


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)0 + * 6 7 3 2 )

To our parents, families, and friends for their continuous support

Basem and Raid Fall 2006


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Summary Of Cha ter Contents

SS c p bilities nd to deliver bro d set o' opti%i ed sol tions. Wehighlights nd present the service 1>SS ph ses9 identi'y, ch r cteri e, opti%i e, nd veri'y.

!art ""

In Ch pter 7 $e introd ce the b sic concepts o' si% l tion %odeling $ith 'oc s on process%odeling nd ti%e/b sed per'or% nce %e s re%ent.We lso cl ri'y the role o' si% l tionst dies in serving the incre sing needs o' co%p nies th t see" contin o s i%prove%ent ndopti% lity in prod ction nd b siness processes.


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process, co%ponents, nd %ech nis%s. ?( %ples o' % n l nd co%p ter si% l tions re sedto cl ri'y the 1?S ' nction lity.

Ch pter 6 is 'oc sed on n ly ing the v rio s spects o' the si% l tion process nd the set o'techni8 es nd steps 'ollo$ed $hen cond cting si% l tion st dy. SS tools nd %ethods by the1>SS ph se, indic ting $here it is %ost ppropri te to st rt tool se.


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development of 3S projects $ased on the road maps discussed in Chapter ( &he guide $egins $y discussing the uni)ue characteristics of 3S projects
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!art ""# Simulation Fundamentals

Cha ter List

Ch pter 79 @ sic Si% l tion Concepts

Ch pter 9 1iscrete ?vent Si% l tion

Ch pter 69


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prod ction nd b siness syste%s. In these st dies, si% l tion is p rtic l rly essenti l 'or syste%represent tion, per'or% nce ev l tion, e(peri%ent l design, $h t/i' n lysis, nd opti%i tion.With s ch c p bility, si% l tion %odeling c n be tili ed s n i%port nt tool in si(/sig%

pplic tions 'or both 1>SS nd 1 AIC.

@e'ore presenting the det ils o' si% l tion tili tion in the 3S/;SS nd 3S/1>SS ppro ches,$e provide n introd ctory to the b sic concepts o' si% l tion %odeling, $ith 'oc s on process%odeling nd ti%e/b sed per'or% nce %e s re%ent.We lso cl ri'y the role o' si% l tionst dies in serving the incre sing needs o' co%p nies th t see" contin o s i%prove%ent ndopti% lity to prod ction nd b siness processes.


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2. ;isting syste% ele%ents S = 4 ) , 2, 3, . . . , n5 nd de'ining the ch r cteristics nd theindivid l role o' e ch ele%ent

3. An ly ing nd nderst nding the logic l rel tionships 4 R ) , R 2, R 3, $ $ $ , R m5 %ong the seto' syste% ele%ents de'ined

7. Speci'ying the set o' o tco%es 4 O5 th t sho ld be prod ced nd their speci'ic tions inorder to re ch the go l 4 ! 5 nd obDective speci'ied

. Speci'ying the syste% controls 4 # 5 nd their r les in %onitoring nd dD sting I"P"O 'lo$to %eet inp ts 4 I 5, process 4 P 5, nd o tp t 4 O5 speci'ic tions6. 1e'ining the go l 4 ! 5 or the over ll syste% obDective nd rel ting syste% str ct re

4inp ts, ele%ents, rel tionships, controls, nd o tp ts5 to go l tt in%ent

@ sed on this nderst nding o' the syste% concept, it beco%es essenti l th t ny rr nge%ent o'things or obDects to be c lled syste% h ve de'ined set o' ele%ents. S ch ele%ents sho ldh ve so%e logic l rel tionships %ong the%, nd there sho ld be so%e type o' go l, obDective,or se' l o tco%e 'ro% the inter ction o' the syste% ele%ents de'ined. in lly, the instr ctor pplies reg l tions nd r les o' cond ct in the cl ssroo%,ttend nce nd gr ding policies, nd so on, s sort o' control 4 # 5 on the ed c tion

process.

>in lly, it is $orth %entioning th t the ter% system covers prod cts nd processes. A prod ctsyste% co ld be n to%obile, cell l r phone, co%p ter, or c lc l tor. Any o' these

prod cts involves the de'ined co%ponents o' the syste% in ter%s o' inp ts, o tp ts, ele%ents,rel tionships, controls, nd go l.


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%&(&( )odeling Con$e t


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nderst nd its ' nction lity nd str ct re, nd try to represent it in process di gr %. 1oes thedi gr % e(pl in everything yo need 'or the s "e o' n ly ing the sse%bly lineK Wh t elsesho ld be 8 nti'ied nd %e s redK

%&(&* +y es of )odels

As %entioned in Section 7.2.2 , sever l %odeling %ethods c n be sed to develop syste%%odel. ollo$ing is s %% ry o' these types o'%odels.

Figure %&*# ig re 7.7 sho$s e( %ples o' prod ct prototypes. Physic l %odels c n lso be oper tion l%odels, s ch s 'light si% l tors nd re l/ti%e si% l tors o' che%ic l oper tions. Another 'or% o'physic l %odel c n be 'o nd in ;ego/type % chine nd conveyor str ct res, nd pl nts or re ctor%odels.


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Figure %&%#?( %ples o' prod ct prototypes. 4>ro% http9::$$$.centerpointdr 'ting.co% .5

Graphical Models Gr phic l %odels re bstr ctions o' ct l prod cts or processes singgr phic l tools.


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h ve 'or% l ted % the% tic l rel tionship nd then tested it g inst re l d t . 1esign 'or% l s'or stress str in n lyses nd % the% tic l progr %%ing %odels s ch s line r nd go lprogr %%ing re e( %ples o' % the% tic l %odels. >ig re 7.6 sho$s % the% tic l %odelb ilt sing the Aig re 7.* . Si%il rly, sever l % the% tic l %odels th t represent co%ple(% the% tic l oper tions, control syste%s, 'l id %ech nics, co%p ter lgorith%s, nd others c n
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be b ilt, ni% ted, nd n ly ed $ith co%p ter tools. So't$ re tools re lso v il ble to developst tic nd dyn %ic ni% tions o' % ny ind stri l processes.

Figure %&.# >inite ele%ent n lysis co%p ter %odel.

Acc r te nd $ell/b ilt co%p ter %odels co%pens te 'or the li%it tions o' the other types o'%odels. or e( %ple, 1?S pl nt %odel c n be sed toesti% te the sse%bly line thro ghp t by r nning the %odel dyn %ic lly nd tr c"ing itsthro ghp t ho r by ho r or shi't by shi't. ig re 7.+ , si% l tion so't$ re tools provide 'le(ible environ%ent o' %odeling nd n lyses th t % "es1?S inco%p r ble to % the% tic l nd physic l %odels.
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Figure %&/# 1?S environ%ent in the Si% l+ so't$ re p c" ge.

%&* Simulation )odeling

As sho$n e rlier, modeling is the rt nd science o' c pt ring the ' nction lity nd the relev ntch r cteristics o' re l/$orld syste%s nd presenting s ch syste%s in 'or% th t ' cilit tessyste% "no$ledge, n lyses, i%prove%ent, nd opti%i tion. Physic l, gr phic l, % the% tic l,

nd co%p ter %odels re the % Dor types o' %odels developed in di''erent engineeringpplic tions.


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in'or% tion bo t the beh vior o' the syste% by e(ec ting co%p teri ed %odel inste d o'observing the re l one.

In concl sion, the pri% ry re8 ire%ents 'or si% l tion re si% l tion n lyst 4e.g., si(/sig%core te % %e%ber or the te % itsel'5 co%p ter, nd si% l tion l ng ge or so't$ re tool.


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Figure %&'1# 1iscrete:contin o s A to od si% l tion %odel.

the% tic lly, $e c n represent %odel st te sing r ndo% v ri ble & , $here &(t) is st tev ri ble th t ch nges over ti%e t . >or e( %ple, *(t) is contin o s st te v ri ble th t representsthe del y o' the i th c sto%er in b n". Another e( %ple o' discrete/st te v ri ble is then %ber o' c sto%ers M + 4t 5N in 8 e e t ti%e t in n : :) 8 e ing syste%.

> rther%ore, %odels re either deterministic or stochastic depending $hether they %odelr ndo%ness nd ncert inty in process or not. A stoch stic process is prob bilistic %odel o' syste% th t evolves r ndo%ly in ti%e nd sp ce. >or% lly, stoch stic process is collection o'r ndo% v ri bles M & 4t 5N de'ined on co%%on s %ple 4prob bility5 sp ce. ?( %ples o' stoch stic%odels oper ting $ith r ndo% v ri bles incl de inter rriv l ti%es o' c sto%ers rriving t b n"

nd service or processing ti%es o' c sto%ers re8 ests or tr ns ctions, v ri ble cycle ti%es, nd% chinesE ti%e to ' il re nd ti%e to rep ir p r %eters.

1eter%inistic %odels, on the other h nd, involve no r ndo% or prob bilistic v ri bles in itsprocesses. ?( %ples incl de %odeling 'i(ed/cycle/ti%e oper tions, s ch the c se o' to% tedsyste%s nd rriv ls $ith preset ppoint%ents to doctor or l $yerEs o''ice.


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s ch dyn %ic ch nges do ''ect the syste% beh vior. !ence, in 1?S si% l tion, the ti%edi%ension is live. As sho$n in >ig re 7.)2 , %odel c n involve both st tic nd dyn %icresponses. ig re 7.)3 presents the t (ono%y o' di''erent si% l tion types $ith highlighted ttrib tes o' 1?S. As noted in the 'ig re, 1?S %odels re digit l 4discrete5, stoch stic, nd dyn %ic co%p ter%odels o' ter%in ting or nonter%in ting 4ste dy/st te5 response. S ch three ch r cteristics o'tenrese%ble the ct l beh vior o' % ny re l/$orld syste%s nd tr ns ction l processes. >ore( %ple, in % n ' ct ring syste%s, the 'lo$ o' r $ % teri l, sse%bly co%ponents, ndprod cts c n be %odeled s discrete, dyn %ic, nd stoch stic processes. Si%il rly, % ny service' cilities o'ten de l $ith discrete entities th t r n dyn %ic lly in stoch stic % nner.
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Figure %&'*# Si% l tion t (ono%y.

%&% +he Role Of Simulation

A'ter nderst nding the v rio s %e nings nd spects o' the ter% simulation modeling , it isnecess ry to cl ri'y the role th t si% l tion pl ys in %odern ind stri l nd b siness 'ir%s. In thissection $e cl ri'y the role o' si% l tion by 'irst D sti'ying the se o' si% l tion both technically ndeconomically nd then presenting the spectr % o' si% l tion pplic tions to v rio s ind stries inthe % n ' ct ring nd service sectors. It is lso $orth %entioning th t sing si% l tion inind stri l nd b siness pplic tion is the %ost co%%on b t not the only 'ield in $hich si% l tionis tili edO it is lso sed 'or ed c tion l nd le rning p rposes, tr ining, virt l re lity

pplic tions, %ovies nd ni% tion prod ction, nd cri%in l D stice, %ong others.

%&%&' Simulation 2ustified


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In short, si% l tion is o'ten tili ed $hen the beh vior o' syste% is co%ple(, stoch stic 4r therth n deter%inistic5, nd dyn %ic 4r ther th n st tic5. An lytic l %ethods, s ch s 8 e ingsyste%s, inventory %odels, nd r"ovi n %odels, $hich re co%%only sed to n ly eprod ction nd b siness syste%s, o'ten ' il to provide st tistics on syste% per'or% nce $henre l/$orld conditions intensi'y to over$hel% nd e(ceed the syste%/ ppro(i% ting ss %ptions.?( %ples incl de entities $hose rriv l t pl nt or b n" is not Poisson process, nd the 'lo$o' entities is b sed on co%ple( decision r les nder stoch stic v ri bility $ithin v il bility o'syste% reso rces.

*ecision support is nother co%%on D sti'ic tion o' si% l tion st dies. bvio sly, engineers nd% n gers $ nt to % "e the best decisions possible, especi lly $hen enco ntering critic l st geso' design, e(p nsion, or i%prove%ent proDects $here the re l syste% h s not yet been b ilt. @yc re' lly n ly ing the hypothetic l syste% $ith si% l tion, designers c n void proble%s $iththe re l syste% $hen it is b ilt. Si% l tion st dies t this st ge % y reve l ins r%o nt bleproble%s th t co ld res lt in proDect c ncell tion, nd s ve cost, e''ort, nd ti%e. S ch s vings

re obt ined since it is l$ ys che per nd s 'er to le rn 'ro% %ist "es % de $ith si% l tedsyste% 4 co%p ter %odel5 th n to % "e the% 'or re l. Si% l tion c n red ce cost, red ce ris",

nd i%prove n lystsE nderst nding o' the syste% nder st dy.

rther,the cost nd ti%e o' si% l tion st dies re o'ten red ced by n lyst e(perience nd beco%e%in sc le co%p red to the long/ter% s vings 'ro% incre sing prod ctivity nd e''iciency.

%&%&( Simulation A li$ations

A better ns$er to the 8 estion F$hy si% l teK c n be re ched by e(ploring the $ide spectr %o' si% l tion pplic tions to ll spects o' science nd technology.


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+a3le %&(# Exam les of Simulated Systemspen t ble s spre dsheet

Simulated System Exam les of )odel Elements 5E-R-"-C-O6

Co%p ter net$or" Server, client PCS, d%inistr tor, d t protocol

>ree$ y syste% C rs, tr ''ic lights, ro d eg%ents, interch nges

> st/'ood rest r nt Servers, c sto%ers, c rs, drive/thro gh $indo$s

@order crossing point C rs, c sto%s gents, booths ,i%%igr tion o''icers

Cl ss registr tion o''ice St dents, co rses, registr tion st tions, helpers

S pply ch in:logistics S ppliers nd vendors tr nsport tion syste%, clients

%&%&* Simulation !re$autions

;i"e ny other engineering tool, si% l tion h s li%it tions. S ch li%it tions sho ld be de lt $iths %otiv tion nd sho ld not disco r ge n lysts nd decision % "ers. no$ing li%it tions o'

the tool in h nd sho ld e%ph si e sing it $isely nd %otiv te the ser to develop cre tive%ethods nd est blish the correct ss %ptions th t bene'it 'ro% the po$er' l si% l tionc p bilities nd precl de si% l tion li%it tions 'ro% being d %ping ' ctor. !o$ever, cert inprec tions sho ld be considered in sing si% l tion to void the potenti l pit' lls o' si% l tion.?( %ples o' iss es th t $e sho ld p y ttention to $hen considering si% l tion incl de the'ollo$ing9

).


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%icro/level %odeling.


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Si% l tion so't$ re tools re in co%%on se %ong si% l tion nd si(/sig% pr ctitioners inv rio s types o' pplic tions nd 'or di''erent p rposes.


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i%prove%ent th t is che per, ' ster, nd e sier to nderst nd. Si% l tion is the rt nd scienceo' %i%ic"ing the oper tion o' re l/$orld syste% on the co%p ter. It is i%ed t c pt ring theco%ple(, dyn %ic, nd stoch stic ch r cteristics o' re l/$orld process, $here other types o'%odels ' ll short. @ sed on the type o' st te v ri bles, co%p ter si% l tion %odels c n bediscrete, contin o s, or co%bined. in lly, they c n be st tic or dyn %ic, b sed on the ch nges o' syste%st te.


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Cha ter ,# Dis$rete E4ent Simulation

,&' "ntrodu$tion

As disc ssed in Ch pter 7 , co%p ter si% l tion, is techni8 e th t i%it tes the oper tion o'

re l/$orld syste% s it evolves over time . 4See Section 7.2.) 'or the de'inition o' system sed inthis boo".5 It is considered n e(peri%ent l nd pplied %ethodology th t see"s to describe thebeh vior o' syste%s, constr ct hypotheses th t cco nt 'or observed beh vior, nd predict ' t rebeh vior. A si% l tion is there'ore the e(ec tion o' %odel, represented by co%p ter progr %th t gives in'or% tion bo t the syste% being investig ted.

Process si% l tion, o'ten sed to %odel prod ction nd b siness processes in both the% n ' ct ring nd service sectors, is re'erred to s discrete e-ent simulation 41?S5. 1iscreteevent syste%s re dyn %ic syste%s th t evolve in ti%e by the occ rrence o' events t possiblyirreg l r ti%e interv ls. Since this rese%bles the n t re o' the % Dority o' re l/$orld prod ction

nd b siness syste%s, 1?S %odels re sed $idely in re l/$orld pplic tions. ?( %ples incl detr ''ic syste%s, % n ' ct ring syste%s, co%p ter/co%% nic tions syste%s, c ll centers, b n"oper tions, hospit ls, rest r nts, prod ction lines, nd 'lo$ net$or"s. ost o' these syste%sc n be %odeled in ter%s o' discrete events $hose occ rrence c ses the syste% to ch nge 'ro%one st te to nother in stoch stic % nner.

or e( %ple, 1?S c n be sed to esti% te the n %ber o'reso rces needed in syste% 4e.g., ho$ % ny oper tors, % chines, tr c"s5.


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be sed to rr nge nd b l nce reso rces to void bottlenec"s, cross/tr ''ic, b c"tr c"ing, nde(cessive $ iting ti%es or inventories.


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+a3le ,&'# Exam les of Stru$tural Elements in DESpen t ble s spre dsheet

Stru$tural Element )odeled )odel !erforman$e Fa$tor Affe$ted

1og sp cing o' po$er nd 'ree syste% Po$er nd 'ree thro ghp t

1i%ensions o' stor ge nits Stor ge nd retriev l ti%e

,&(&( System Layout

A syste% l yo t is si%ply the con'ig r tion pl n 'or syste%Es str ct r l ele%ents.


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+a3le ,&(# Data Colle$ted for 9arious DES Elementspen t ble s spre dsheet

Element )odeled !ertinent Simulation Data

per tor W l" speed, $or" se8 ence, $ l" p th

@ ''er C p city, discipline, inp t:o tp t r les

A to% ted g ided vehicle Speed, cceler tion:deceler tion, ro te

Po$er/ nd/'ree syste% Speed, dog sp cing, ch in length

P rt:lo d Attrib tes o' si e, color, 'lo$, %i(

,&(&% System Logi$

Syste% logic co%prises the r les nd proced res th t govern the beh vior nd inter ction o'v rio s ele%ents in si% l tion %odel. It de'ines the rel tionships %ong %odel ele%ents ndho$ entities 'lo$ $ithin syste%.


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,&(&, System Statisti$s

Syste% st tistics re %e ns o' collecting r n/ti%e in'or% tion nd d t 'ro% syste% d ring r nti%e nd ggreg ting the% t the end o' si% l tion r n ti%e. 1 ring r n ti%e, s ch st tistics renecess ry to control the oper tion nd 'lo$ o' syste% ctivities nd ele%ents. At si% l tion end,these st tistics re collected to s %% ri e syste% per'or% nce t v rio s syste% design nd

p r %eter settings. In syste% 1?S %odel, there'ore, st tistics re collected nd cc % l ted toprovide s %% ry o' res lts t the end o' r n ti%e. S ch st tistics re sed to %odel re l/ti%e%onitoring g ges nd cloc"s in re l/ $orld syste%. @ec se o' %odel 'le(ibility, ho$ever,so%e st tistics th t re sed in the %odel % y not ct lly be in the re l/$orld syste%.


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Figure ,&(# 1?S syste% ele%ents.

,&*&' System Entities

?ntities re ite%s th t enter syste% s inp ts, re processed thro gh the syste% reso rces ndctivities, nd dep rt the syste% s o tp ts. As 1?S dyn %ic obDects, entities re %odel/

tr ce ble ele%ents th t re o'ten o' interest to syste% designers, % n gers, nd si(/sig%oper tives s ch s green belts, bl c" belts, nd % ster bl c" belts. ?( %ples incl de p rts orprod cts in % n ' ct ring, c sto%ers in b n"ing, c lls in c sto%er/service center, p tients inhe lth syste%s, letters nd p c" ges in post l services, doc %ents in n o''ice, ins r ncepolicies in n ins r nce co%p ny, d t in n in'or% tion syste%, nd so on.

In 1?S, entities re ch r cteri ed by ttrib tes s ch s price, type, cl ss, color, sh pe, I1n %ber, origin, destin tion, priority, d e d te, nd so on. Speci'ic v l es o' s ch ttrib tes retied to entities nd c n di''er 'ro% one entity to nother. !ence, ttrib tes c n be considered slocal v ri bles th t re tied to individ l entities.


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+a3le ,&,# exam les of states of different model Elementspen t ble s spre dsheet

)odel Element System State

@ ''er ?%pty, ' ll, h l'/' ll

Conveyor ?%pty, ' ll, bro"en, bloc"ed, st rved

; bor Idle b sy, $ l"ing

Lehicle oving, stopped, bro"en, p r"ing

1?S records ch nges in syste% st te s it evolves over ti%e t discrete point in ti%e toprovide represent tion o' syste% beh vior nd to collect st tistics nd per'or% nce %e s resth t re essenti l to syste% design nd n lysis. Syste% st te v ri bles re sed to 8 nti'y thedescription o' syste% st te.

,&*&* State 9aria3les

1?S %odels incl de collection o' v ri bles th t describe the syste% st te t ny speci'ic pointin ti%e. S ch v ri bles cont in the in'or% tion needed to describe %odel co%ponent st t s nd%e s re its per'or% nce. ?( %ples incl de the n %ber o' nits in the syste%, the percent ge o'e ch reso rce st t s 4i.e., Q idle, Q b sy, Q bro"en, Q bloc"ed5, nd the n %ber o' b sy or idleoper tors.

In ddition to the over ll syste%/level v ri bles, %odel v ri bles incl de inp t ' ctors 4 & ) , & 2, . . . , & n5. ig re .3 is sche% tic

represent tion o' st te v ri bles.

Figure ,&*# Syste% st te v ri bles.

,&*&% System E4ents An event is n inst nt neo s occ rrence th t ch nges the syste% st te. As disc ssed e rlier, thesyste% st te is the description o' syste% st t s t ny ti%e, $hich is de'ined by set o' st tev ri bles.


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the events nd their i%plic tionsO hence, %odel beh vior is re'erred to s event/driven. >ig re .7 sho$s ho$ syste% st te is pd ted t event occ rrences.

Figure ,&%# ?vent/driven syste% st te.

?vent occ rrence in 1?S %odel c n be the rriv l o' n entity, the st rt o' co''ee bre ", theend o' shi't, the ' il re o' reso rce, ch nge in b tch si e, the st rt o' ne$ prod ctionsched le, the dep rt re o' n entity, nd so on. Since 1?S %odel ele%ents re interrel ted nd1?S environ%ents re dyn %ic, the occ rrence o' s ch events o'ten le ds series o' ch nges tothe syste% st te. >or e( %ple, the rriv l o' c sto%er t b n" incre ses the $ iting line i' theb n" teller is b sy, or ch nges the teller st t s 'ro% idle to b sy i' teller is v il ble. Si%il rly,$hen the c sto%er dep rts the b n", the server is ch nged b c" to idle, nother c sto%er isre8 ested 'ro% the $ iting line, nd the n %ber o' c sto%ers served is incre sed. !ence, thest te v ri bles ''ected re pd ted, relev nt st tistics re cc % l ted, nd the si% l tion cloc"is dv nced to the ne(t event in the event list.

,&*&, System A$ti4ities

An ctivity is t s" per'or%ed in %odel th t h s speci'ied ti%e d r tion. Activities redeter%ined si%ply by est blishing se8 ence 'or the oper tions needed to process n entity.?( %ples o' s ch oper tions incl de receiving, directing, tr ns'erring, cle ning, % chining,p c" ging, nd shipping. S ch ctivities either process the entity 4v l e/ dded5 directly, s ch sc tting nd serving, or indirectly, s ch s % teri l h ndling, inspection, nd stor ge ctivities4non/v l e/ dded5.

A process % p o'ten incl des se8 ence o' ll ctivities or oper tions re8 ired to process nentity, long $ith speci'ic tions nd the cl ssi'ic tion o' di''erent types o' oper tions. A processch rt o'ten cl ssi'ies oper tions into process 4 circle5, tr nsport 4 n rro$5, stor ge 4 tri ngle5,del y 415, nd inspection 4 s8 re5, s sho$n in < ble .6 . Si%il rly, ctivities in 1?S %odelc n be cl ssi'ied to provide better nderst nding o' the process 'lo$ nd deeper "no$ledgeo' process oper tions.+a3le ,& # A$ti4ities in a !ro$ess O erations Chart

pen t ble s spre dsheet

Sym3ol !ro$ess )eaning Exam le

Processing oper tion 1rilling oper tion

or"li't tr ns'ers nit lo d to stor ge

Stor ge oper tion >inished goods re stored be'oreshipping

1el y oper tion Wor"/in/process nits re del yed be'ore'in l sse%bly
http://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/viewer.asp?bookid=16837&chunkid=792074382#wbp09Chapter5P266ABCEE34C-FFF0-4531-8465-E3FB89C37299%23wbp09Chapter5P266ABCEE34C-FFF0-4531-8465-E3FB89C37299http://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/viewer.asp?bookid=16837&chunkid=792074382#wbp09Chapter5P271ABCEE34C-FFF0-4531-8465-E3FB89C37299%23wbp09Chapter5P271ABCEE34C-FFF0-4531-8465-E3FB89C37299http://popimage%28%27img_57%27%2C%27http//images.books24x7.com/bookimages/id_16837/fig05_04_0.jpg','588','120')http://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/viewer.asp?bookid=16837&chunkid=792074382#wbp09Chapter5P266ABCEE34C-FFF0-4531-8465-E3FB89C37299%23wbp09Chapter5P266ABCEE34C-FFF0-4531-8465-E3FB89C37299http://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/viewer.asp?bookid=16837&chunkid=792074382#wbp09Chapter5P271ABCEE34C-FFF0-4531-8465-E3FB89C37299%23wbp09Chapter5P271ABCEE34C-FFF0-4531-8465-E3FB89C37299


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+a3le ,& # A$ti4ities in a !ro$ess O erations Chartpen t ble s spre dsheet

Sym3ol !ro$ess )eaning Exam le

Inspection oper tion ne o' every )00 nits is inspected t 8 lity control st tion

Syste% ctivities c n be lso cl ssi'ied s v l e/ dded or non/v l e/ dded9). alue added 4LA5 acti-ities . L l e is dded thro gh ctivities th t tr ns'or% the

ch r cteristics o' n entity 'ro% one 'or% to nother.L l e is de'ined by the c sto%er. @y% "ing ch nges to entities, s ch ctivities incre se their v l es. !ence, the price o' tono' rein'orce%ent steel is % ch higher th n the price o' ton o' steel billet. Steel billets rehe ted, 'or%ed, 8 enched, cooled, nd c t be'ore beco%ing rein'orce%ent steel. S choper tions gr d lly incre se the v l e o' steel entities.

2. .on -alue added 4#LA5 acti-ities . ny oper tions per'or%ed on entities % y not ddv l e to the% b t they re still needed to co%plete the process. ?( %ples incl detr nsporting nd tr ns'erring oper tions, storing nd del ying % teri ls, nd 8 lity controlinspections.


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+a3le ,&.# Exam les of System Resour$espen t ble s spre dsheet

)anufa$turing System Ser4i$e System

Asse%bly st tions nd tools 1rive/thro gh $indo$s

ey ' ctors th t ''ect the per'or% nce o' reso rces incl de c p city, speed, nd reli bility.C p city ''ects reso rce tili tion, $hich %e s res the percent ge o' reso rce se. Sincereso rces cons %e c pit l, syste% designers nd % n gers pre'er to incre se the tili tion o'reso rces thro gh better sched ling nd reso rce lloc tion. eso rce speed deter%ines theprod ctivity o' the reso rce, o'ten %e s red s thro ghp t or yield. Si%il rly, reso rcethro ghp t is l rger/the/better %e s re. ?li%in ting $ ste in ti%e nd ine''iciencies inoper tion incre ses thro ghp t. >in lly, reso rce reli bility deter%ines the percent ge o'reso rce pti%e 4 v il bility5. It is l$ ys re8 ired to incre se the pti%e percent ge o'reso rces thro gh better % inten nce nd $or"lo d b l ncing. < ble .+ s %% ri es the threereso rce ' ctors9+a3le ,&/# Fa$tors Affe$ting System Resour$es

pen t ble s spre dsheet

Resour$e Fa$tor !erforman$e)easure

:nit )etri$ Exam le

C p city -tili tion Percent b sy 2 is + Q tili ed

Speed


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>or e( %ple, % chine $ith cycle ti%e o' 60 seconds prod ces ):60 nit per second or) nit per %in te. < "t ti%e is o'ten sed to indic te the speed o' to% tic prod ctionlines.

3. Resource relia'ility3 reso rce ' ctor th t deter%ines the reso rce pti%e or v il bility.It is o'ten %e s red in ter%s o' %e n ti%e bet$een ' il res 4 5, $here reso rce' il re is e(pected to occ r t ti%e nits. ep ir ti%e, 'ter ' il re occ rs, is%e s red by %e n ti%e to rep ir 4


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thoro gh nd pr ctic l nderst nding o' the nderlying prod ction or b siness process is nessenti l ingredient 'or developing represent tive si% l tion logic.

,&% DES )e$hanisms

As disc ssed e rlier, 1?S %odels re dyn %ic, event/driven, discrete in ti%e, stoch stic

4r ndo%i ed nd prob bilistic5, nd co%p ter/ ni% ted. S ch ch r cteristics re est blished inthe 1?S %odel b sed on cert in po$er' l %ech nis%s. in 1?S %ech nis%s incl de thecre tion nd pd ting o' n events list, the ti%e/ dv nce%ent %ech nis%, the c p bility o's %pling 'ro% prob bility distrib tions $ith r ndo% n %ber gener tion, the c p bility o'

cc % l ting st tistics over r n ti%e, nd the po$er o' t$o/ or three/di%ension l dyn %icgr phic l represent tion $ith ni% tion %ech nis%.


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,&%&' Dis$rete E4ent )e$hanism

?vents in 1?S re discrete since they t "e pl ce t discrete points in ti%e. 1?S ' nction lity is,there'ore, b sed on cre ting n event list nd e(ec ting the events o' the list chronologic lly.S ch ' nction lity is b sed on discrete event nd cloc"/ dv nce%ent %ech nis%. ig re .6 59

Figure ,& # ?vent list oper tions.). -ent remo-al . -pon the occ rrence o' n event, the list % y be pd ted by re%oving

one or %ore events 'ro% the list, res lting in ch nging the chronologic l order o' evente(ec tion. So%e events % y be deleted 'ro% the list be'ore their e(ec tion. An event % y

be deleted 'or % ny re sons9 'or e( %ple, $hen the occ rrence o' one event precl desthe occ rrence o' nother. ?vent re%ov l c n t "e pl ce in t$o loc tions in n eventlist9. From the top of the 1 . When n event is re%oved 'ro% the top o' n ?;, it is

done or e(ec ted. >or e( %ple, event ) in >ig re .6 $ s processedO hence theevent is re%oved 'ro% the top o' ?; ) $hen pd ting the list to beco%e ?; 2.

b. From any other location 4ithin the 1 . When n event is re%oved 'ro% ny otherloc tion in the ?; other then the top o' the list, it is c nceled. >or e( %ple, event 7in >ig re .6 $ s c nceledO hence the event is re%oved 'ro% ?; ) nd did not sho$

p in ?; 2.2. -ent addition . -pon the occ rrence o' n event, the list % y be pd ted by dding one

or %ore events to the list, res lting in ch nging the chronologic l order o' event e(ec tion.?vent ddition c n t "e pl ce in t$o loc tions in n ?;9

. To the top of the 1$ When n event is dded to the top o' the ?;, it isconsidered s the %ost i%%inent event to t "e pl ce. >or e( %ple, event * in>ig re .6 $ s dded to the top o' ?; 2 nd $ill be processed 'irst. ? * $ s not %e%ber o' ?; ) $hen pd ting the list to beco%e ?; 2.

b. To any other location 4ithin the 1$ When n event is dded to ny loc tion in n?; other then the top o' the list, it is D st being dded s ' t re event. >ore( %ple, event 6 in >ig re . $ s dded to ?; 2 nd $ill be processed right 'ter

2.


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syste%s 4e.g., pl nts, b n"s, hospit ls5 oper te in discrete % nner 4tr ns ction/ or event/b sed5. Since these syste%s o'ten involve $ iting lines, si%ple discrete event %ech nis% iso'ten %odeled sing 8 e ing %odels. 1?S %odels c n be vie$ed s 8 e ing net$or"s th t % yor % y not be %en ble to 8 e ing theory. 1iscrete events occ r in the si% l tion %odel si%il rto the $ y they occ r in the 8 e ing syste% 4 rriv l nd dep rt re o' events5. >or inst nce, c sto%er Doins 8 e e t discrete inst nt o' ti%e, nd t l ter discrete inst nt the c sto%erle ves the b n". or e( %ple, >ig re .* sho$s n event list o' )0 events 4 ) , 2,

3, . . . , )0 5 ordered chronologic lly s T ) , T 2, T 3, . . . , T )0 . In 1?S, the ti%e periods bet$een

events 4e.g., ) nd 25 re s"ipped $hen e(ec ting the %odel, res lting in compressed si% l tion ti%e. !ence, the tot l ti%e re8 ired to process the )0 events in the 1?S co%p ter%odel is % ch shorter th n the ct l cloc" ti%e.

Figure ,&.#


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>ro% pr ctic l point o' vie$, r ndo% n %bers re b sic ingredients in the si% l tion %odels o'%ost re l/$orld syste%s. chine cycle ti%es, c sto%er service ti%es, e8 ip%ent ' il res, nd8 lity control tests re e( %ples o' r ndo%ness ele%ents in 1?S %odels. ndo% %odel d tinp ts o'ten le d r ndo% %odel o tp ts.


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r ndo% n %bers c n be repe ted g in nd g in. >or this re son, #G %ethods re o'tenc lled pseudo R.! . < bles o' re dy/to/ se r ndo% n %bers re v il ble, especi lly 'or onteC rlo si% l tions, $here r ndo% s %pling is sed to esti% te cert in e(peri%ent l o tp t. Also,%ost si% l tion so't$ re p c" ges h ve the c p bility o' to% tic r ndo% n %ber gener tion.

Appendi( @ presents t ble o' r ndo% n %bers.

ampling with the !n"erse Method -sing n #G $ith ni'or%40,)5 v l es, s ccessive r ndo%s %ples c n be gener ted 'ro% prob bility distrib tions sing three %ethods9

). In-erse method3 sed 'or s %pling 'ro% e(ponenti l, ni'or%, Weib ll, nd tri ng l rprob bility distrib tions s $ell s e%piric l distrib tions.

2. #on-olution method3 sed 'or s %pling 'ro% ?rl ng, Poisson, nor% l, nd bino%i ldistrib tions.

3. /cceptance"re7ection techni8ue3 sed 'or s %pling 'ro% bet nd g %% distrib tions.

5, s ch s the e(ponenti l nd ni'or% distrib tions. 5 o' the e(ponenti ldistrib tion is

f( ) T e / $here 9 0

o' the e(ponenti ldistrib tion by integr ting f 4 5 'ro% 0 to , $hich res lts in

f( ) T ) / e / $here 9 0


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or e( %ple, the si(/sig% te % c n observecontin o sly the ch nges th t occ r to the n %ber o' nits or c sto%ers in the syste%.

2. #onducting scheduled simulation re-ie4s$ In % ny si% l tion st dies it is o'tennecess ry to revie$ the syste% st te t cert in points in si% l tion r n ti%e.


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,&%&, Animation )e$hanism

Ani% tion in syste% si% l tion is se' l tool to both the si% l tion %odeler nd the decision% "er. ost gr phic lly b sed si% l tion so't$ re p c" ges h ve de' lt ni% tion ele%ents 'orsyste% reso rces, b ''ers, oper tions, l bor, nd so on.


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n lytic l %odels th t c n be n ly ed $ith si% l tion incl de inventory %odels, 'in nci l%odels, nd reli bility %odels.

Since $e h ve closed/'or% 'or% l s to n ly e si%ple 8 e ing %odels, the need to ppro chs ch %odels $ith si% l tion is o'ten 8 estion ble. Si% l tion is o'ten sed in s ch c ses tocl ri'y the pplic tion o' 1?S %ech nis%s. Also, $hen ss %ptions th t re re8 ired 'ordeveloping n lytic l 8 e ing syste%s do not pply, si% l tion is sed to n ly e the syste%s.?vents rriv l nd dep rt re, deter%ining e ch eventEs ti%e o' occ rrence, nd pd ting theevent list re e( %ples o' those %ech nics. @ sed on the %ech nics o' %odeling discreteevents, the %odeling st te v ri bles nd st tistics collected re deter%ined t di''erent inst nts$hen e(ec ting the %odel.

5 discipline.#o ' il res re e(pected to occ r t the oil/ch nge b y.

I> sched le. nce the c r 'inishes service, n inter rriv l ti%e 4 a 5 is s %pledr ndo%ly sing the #G, nd ne$ rriv l is sched led t ti%e t = T + a . St tistics re

cc % l ted nd collected nd si% l tion contin es si%il rly 'or nother rriv l. ig re . .
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Figure ,&0# ?(ec tion o' c r rriv l dep rt re process.

C rs inter rriv l ti%e is gener ted r ndo%ly 'ro% contin o s e(ponenti l distrib tion 4%e n = 20 %in tes5, $hile the service ti%e is gener ted r ndo%ly 'ro% discrete distrib tion 4) %in tes$ith prob bility +0Q nd 20 %in tes $ith prob bility 20Q5. S %pling 'ro% the e(ponenti ldistrib tion $ith C1> o' f 4t 5 = ) e t , t > 0, res lts in t = 4): 5 ln4) R 5, $here R = f 4t 5.L l es o'R sed to obt in s ccessive r ndo% ti%e s %ples 4 t 5 re selected 'ro% ni'or% 40,)5distrib tion sing the ;CG %ethod. Si%il rly, R is gener ted 'or s %pling 'ro% the discretedistrib tion to deter%ine the service ti%e 4 s 5, $here s = ) %in tes i' 0 R 0.+ nd s = 20%in tes i' 0.+ < R ).0.


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dv nced to the ne(t event 4 25 ti%e 4T = ) .00 %in tes5 in order to e(ec te 2.


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+a3le ,&''# Simulation +a3le for the First (1 Carspen t ble s spre dsheet

A B C D E F ; H "

)6 ) . 0 2 0.62 ) .00 2 +.+ +.2* 3)3.+ 23.2* 0.00

)* 2+.*0 3) .32 ) .00 3) .32 0.00 337.32 ) .00 .73

)+ 2 .6 377. * ) .00 377. * 0.00 3 . * ) .00 )0.6

) 22.7 36*.72 20.00 36*.72 0.00 3+*.72 20.00 *.7

20 )2. 0 3* . 2 ) .00 3+*.72 *. 0 702.72 22. 0 0.00

Sum $>2


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ele%ents nd p tient 'lo$ nd to gener te si% l tion d t 'ro% relev nt s %pling distrib tions.We brie'ly disc ss %odel ss %ptions, %odel constr ction, nd %odel v lid tion nd veri'ic tion.>in lly, %odel n lysis s %ple $ill be presented to de%onstr te ho$ 1?S provides ns$ers to"ey 8 estions on the beh vior o' the clinic syste%.


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Figure ,&''# A to od si% l tion %odel o' the clinic e( %ple.


49/79


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press red to co%plete tre t%ent 8 ic"ly. Still, ho$ever, d e to ro ting p tients, the t$o clinice( %in tion physici ns re tili ed 3.6Q nd + . Q. irst, cle r cl ssi'ic tion o' the proDect b siness processes is needed s prod ct develop%ent

nd prod ction process 'or proble% solving, incl ding distrib tion processes or service/b sedprocesses. Process cycle ti%es nd reso rce re8 ire%ents re s lly h ndled by si% l tion,
http://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/viewer.asp?bookid=16837&chunkid=279833062#wbp09Chapter5P1203ABCEE34C-FFF0-4531-8465-E3FB89C37299%23wbp09Chapter5P1203ABCEE34C-FFF0-4531-8465-E3FB89C37299http://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/viewer.asp?bookid=16837&chunkid=279833062#wbp09Chapter5P1203ABCEE34C-FFF0-4531-8465-E3FB89C37299%23wbp09Chapter5P1203ABCEE34C-FFF0-4531-8465-E3FB89C37299http://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/viewer.asp?bookid=16837&chunkid=279833062#wbp09Chapter5P1203ABCEE34C-FFF0-4531-8465-E3FB89C37299%23wbp09Chapter5P1203ABCEE34C-FFF0-4531-8465-E3FB89C37299http://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/outputobject.asp?bookid=16837&chunkid=279833062&objectid=wbp09Chapter5P1203&objecttype=spreadsheethttp://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/viewer.asp?bookid=16837&chunkid=279833062#wbp09Chapter5P1203ABCEE34C-FFF0-4531-8465-E3FB89C37299%23wbp09Chapter5P1203ABCEE34C-FFF0-4531-8465-E3FB89C37299http://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/viewer.asp?bookid=16837&chunkid=279833062#wbp09Chapter5P1203ABCEE34C-FFF0-4531-8465-E3FB89C37299%23wbp09Chapter5P1203ABCEE34C-FFF0-4531-8465-E3FB89C37299http://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/outputobject.asp?bookid=16837&chunkid=279833062&objectid=wbp09Chapter5P1203&objecttype=spreadsheet


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prod cing %ore cc r te res lts. ny 1?S si% l tion p c" ges re c p ble o' representinghighly v ri ble steps $ith tightly co pled reso rces. odeling shi'ts, do$nti%e, overti%e, ndle rning c rves $ith % ltiple replic tions 'or reso rces re so%e o' the i%port nt consider tionsin b ilding v lid si% l tion %odel.

In the conte(t o' si(/sig% , discrete event si% l tion is 8 ite s it ble 'or prod ction processproble% solving, $here o tp ts re prod ced in b tch or contin o s/'lo$ %ode in rel tivelyhigh vol %es. < s"s s ch s sse%bly, dis sse%bly, set p, inspection, nd re$or" re typic lsteps in prod ction processes $ith 8 e ing r les nd do$nti%e %odeling. S ch processes re

s lly %odeled to obt in ste dy/st te beh vior p st the $ r%/ p period.

In %odeling distrib tion processes in prod ction environ%ent, it is i%port nt to de'ine ttrib tes'or 'lo$ entities in order to "eep tr c" o' ni8 e ch r cteristics s ch s v l e/ dds, cost, nddist nce tr veled. 1 e to the tr nsient n t re o' distrib tion processes, the si% l tion %odel$ r%/ p period is s lly longer th n other prod ction processes.

In service/b sed ind stry, processes present % Dor re 'or e%ploy%ent o' si% l tionst dies.


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Cha ter # +he Simulation !ro$ess

&' "ntrodu$tion


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% Dor e(p nsions o' % n ' ct ring syste%, ne$ clinic, ne$ b n", ne$ vehicle progr %,nd ne$ tr nsport tion net$or".

1esigning ne$ syste% or process $ith or $itho t si% l tion o'ten involves testing ne$concepts, b ilding ne$ str ct res or l yo ts, nd developing ne$ logic.


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ele%ents. ?( %ples incl de % chine cycle ti%es nd reli bility d t , % teri l h ndlingnd tr ns'er speed, b ''er c p city, nd so on. 1i''erent levels o' s ch p r %eters re

tested sing the si% l tion %odel thro gh e(peri%ent l design nd opti%i tion se rch torrive t the p r %eter settings th t le d to best syste% per'or% nce. >or e( %ple,

di''erent p r %eters in % n ' ct ring process 4e.g., n %ber o' oper tors, % chine cycleti%es, conveyor speeds, b ''er c p cities5 re set so th t the thro ghp t o' pl nt is% (i%i ed.

Syste% str ct r l, logic l, nd p r %etric design ''ects syste% per'or% nce 4%odel response5directly in ter%s o' syste% thro ghp t, le d ti%e, inventory levels, nd so on. In designingsyste%s, s ch responses H) re sed to g ide the design process. >or e( %ple, one l yo t % yres lt in longer % teri l 'lo$ nd conse8 ently, longer % n ' ct ring le d ti%e. 1el ys cre tedbec se o' i%proper logic l design lso ''ect le d ti%e nd thro ghp t. >in lly, longer cycleti%e or high percent ge o' do$nti%e t cert in $or"st tion % y cre t syste% bottlenec"th t c ses del ys nd res lts in thro ghp t. ig re 6.7 , si% l tion %odeling is tili ed to per'or% the % in proble%/solving techni8 es o' di gnosingsyste%s, testing oper tion l sche%es, nd v lid ting prescribed sol tions. ig re 6.7 , solving proble%s $ith si% l tion incl des proble% di gnostic ndde'inition, testing sol tion sche%es, nd v lid ting proble% sol tion.

). Proble% di gnostic $ith si% l tion is not l$ ys n e sy t s". It depends he vily on thecredibility o' the %odel b ilt.


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role in proble% di gnostic by $ tching the %odel. In other c ses it is necess ry to per'or%so%e tests, inserting so%e logic, or st dying the si% l tion report in order to di gnose theso rce o' the proble%.

2. A'ter di gnosing the proble%, si% l tion c n be sed to test v riety o' proble% sol tionsche%es. S ch sche%es re o'ten tested sing $h t/i' n lysis, $here the i%p ct o' e chsche%e on %odel per'or% nce is tested nd n ly ed. in lly, the vi bility nd rob stness o' the sol tion sche%e proposed 'or the nderlyingproble% is tested. Sensitivity n lysis c n be sed to test sol tion rob stness to v rio sso rces o' v ri tions. #ot ll sol tion sche%es re ble to ' nction properly $ith othersyste% ele%ents nder syste% constr ints nd $or" conditions. S% ll v ri tions in s chconditions % y le d to dr stic ch nges in syste% per'or% nce. !ence, si% l tion is sedto test sol tion sensitivity nd rob stness be'ore considering the sol tion sche%e to be'in l.

&(&* Continuous "m ro4ement Simulation

It is o'ten sserted th t the s ccess o' prod ction nd b siness syste%s in s st ining cert inlevel o' per'or% nce depends on e''ort in est blishing nd i%ple%enting pl ns 'or contin o si%prove%ent. Co%p nies do not l$ ys $ it ntil proble% rises to t "e correction ndi%prove%ent ctions. n gers nd engineers o'ten believe th t there is l$ ys $indo$ 'ori%prove%ent in the $ y th t co%p nies prod ce prod cts or provide services.


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Ch nges s ggested nd ide s r ised by te % %e%bers c n be tested nd ev l ted8 ic"ly t virt lly no cost.

2. A'ter cert in i%prove%ent opport nity is de'ined, it o'ten necess ry to provide pl nnd %ech nis% 'or chieving the de'ined i%prove%ent. 1i''erent %ethods nd techni8 es

c n be sed to i%prove per'or% nce, c t cost, nd red ce $ ste. ;e n % n ' ct ringtechni8 es re co%%only sed by engineers to chieve i%prove%ent pl ns. In le n% n ' ct ring, the 'oc s is on cost nd $ ste red ction, red cing % n ' ct ring le d ti%e

nd co%p ny response ti%e, nd incre sing e8 ip%ent nd l bor e''ectiveness.Si% l tion c n id in pplying nd testing the i%p ct o' the i%prove%ent pl ns proposed.

3. >in lly, the vi bility nd rob stness o' the i%prove%ent ction or pl n proposed is tested.Sensitivity n lysis c n be sed to test the pl nEs rob stness to v rio s so rces o'v ri tions. -sing the si% l tion %odel, i%prove%ent ctions re i%ple%ented ndper'or% nce is ev l ted to 8 nti'y the i%prove%ent.


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). 1e'ining the set o' sol tion ltern tives is ppro ched by e(ploring the sol tion do% innd listing the potenti l sol tion %ethods. In ddition to thoro gh nderst nding nd

solid e(perience in the nderlying syste%, co%bin tion o' cre tivity nd engineerings"ills is re8 ired to gener te set o' sol tion ltern tives. @r instor%ing sessions ndide /gener ting techni8 es c n be sed in this reg rd in % nner si%il r to th t sed 'orgener ted i%prove%ent ide s. With si% l tion, ho$ever, sol tion ide s c n be gener tedin % ch e sier $ y. @y providing close/to/re lity represent tion o' the syste%, the%odel c n be sed to observe the syste%Es dyn %ic beh vior, pro%ote ide gener tion,

nd predict the per'or% nce 'or e ch ide gener ted.2. ?(ploring the sol tion do% in o' the nderlying proble% o'ten le ds to de'ining set o'

potenti l sol tion ide s. in lly, so%e o' the %e s res,s ch s 8 lity, cost, nd n %ber o' nits processed, c n be rel ted to the syste% entity.

2. nce the set o' per'or% nce %e s res re de'ined, si% l tion %odel c n be sed toev l te the set o' sol tion ltern tives. ? ch si% l tion/b sed ev l tion provides seto' per'or% nce %e s res. Sol tion ltern tives re then co%p red nd the ltern tive$ith the best per'or% nce is selected.


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&*&% Sele$tion of the Best Alternati4e

In this st ge, the best sol tion or i%prove%ent ltern tive is selected b sed on the si% l tionev l tion in the preceding step.


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Figure &.#


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>or% l ting design proble% incl des st ting the over ll design obDective nd the constr ints onthe design process. >or e( %ple, the go l %ight be to design % teri l/h ndling syste% th t isc p ble o' tr ns'erring cert in ite% 'ro% point A to point @.


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co%ple( gr phic l represent tion, s ch s bloc" di gr %, 'lo$ch rt, or process % p th tdepicts "ey ch r cteristics o' the si% l ted syste%, s ch s inp ts, ele%ents, p r %eters, logic,'lo$, nd o tp ts. S ch represent tion sho ld event lly be progr %% ble nd tr ns'er bleinto si% l tion %odel sing v il ble si% l tion so't$ re tools. or e( %ple, developing concept th t incl des po$er/ nd/'ree conveyor syste%sho ld 'ind o t i' there is c p bility 'or %odeling s ch syste% in the si% l tion so't$ re toolbeing sed. ey p r %eters o' syste% ele%ents re lso speci'ied s p rt o' the %odelconcept. >or e( %ple, the concept o' sing convey nce syste% to tr ns'er entities 'ro% point Ato point @ sho ld incl de p r %eters o' conveyor type, speed, reli bility, nd c p city. S chp r %eters g ide d t collection nd ele%ent selection.

>in lly, the %odel concept is developed t "ing into consider tion the proble% s it $ s'or% l ted nd the obDectives o' the si% l tion st dy. >ig re 6.+ sho$s the re8 ire%ents 'orconcept l %odeling.

Figure &/# 1eveloping %odel concept.

&%&% Data Colle$tion

Si% l tion %odels re d t /driven co%p ter progr %s th t receive inp t d t , e(ec te the logicdesigned, nd prod ce cert in o tp ts. !ence, the d t collection step is "ey co%ponent o' nysi% l tion st dy. Si% l tion d t c n, ho$ever, be collected in p r llel to b ilding %odel singthe si% l tion so't$ re.


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1epending on the n t re o' the si% l tion st dy, %odel d t re collected by revie$ing historic ld t , by observing nd %onitoring syste% oper tions, nd by sing bench% r" d t

ss %ptions. in lly,theoretic l st tistic l distrib tions $ith esti% ted p r %eters c n be sed 'or %odel d t . Alltypes o' ss %ed d t re s bDect to %odi'ic tion nd lter tion s the %odel b ildingprogresses nd %ore insight is g ined into %odel beh vior.

!nput Modeling


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ddition to the v ri bility o' d ption over the r n ti%e, di''erent r ndo% n %ber stre %s o'tenres lt in di''erent sets o' d t s %pled, $hich le ds to stoch stic v ri bility in %odel o tco%es.!ence, % ltiple si% l tion replic tions re o'ten sed to esti% te e ch %odel per'or% nce%e s re in ter%s o' %e n nd v ri nce.

ny st tistic l %ethods re typic lly sed 'or %odeling si% l tion inp ts. !o$ever, the b sicconcept in these %ethods is si%ple. I' $e co%p te the %e n o' s %ple o' 20 n %bers, thev l e obt ined $ill gener lly be % ch di''erent 'ro% the pop l tion %e n 4i.e., the s %plingdistrib tion is not good ppro(i% tion o' the d t distrib tion5. @ t i' $e s %pled % ny sets o'20 n %bers over nd over g in, co%p ted the %e n 'or e ch set, nd constr cted rel tive're8 ency distrib tion o' ll sets, $e $o ld event lly 'ind th t the distrib tion o' %e ns is verygood ppro(i% tion to the s %pling distrib tion.


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+a3le &'# Summary of Commonly :sed Distri3utions in Simulation Studiespen t ble s spre dsheet

Simulation 9aria3le !ro3a3ilityDistri3ution

=ey Distri3ution !arameters

g ided vehicle 4AGL5,'or" tr c",etc.


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Figure &'1# odel/b ilding proced re.


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tools strive to red ce the progr %%ing e''ort, $riting code is still necess ry to i%ple%ent the%odel logic.

nce the %odel logic is developed, $e st rt r nning the %odel. !o$ever, the %odel per'or% ncend res lts % y not re'lect the beh vior o' the syste% o' interest $itho t inserting represent tive

d t into the %odel nd setting the p r %eters o' v rio s syste% co%ponents. S ch d t sho ldbe collected $hile the 'irst three steps in the %odel/b ilding proced re re being e(ec ted. As the%odel d t beco%e v il ble, $e st rt inserting the d t in the %odel 'ollo$ing the instr ctionss ggested by the si% l tion tool sed. Gener lly, this is n e sy nd 8 ic" step in the %odel/b ilding proced re.

ore( %ple, does the %odel re d the inp t d t properlyK 1oes the %odel send the right p rt to theright pl ceK 1oes the %odel i%ple%ent the prod ction sched le prescribedK 1o c sto%ers in the%odel 'ollo$ the 8 e ing discipline proposedK 1oes the %odel provide the right o tp tK And soon. ther veri'ic tion techni8 es incl de pplying r les o' co%%on sense, $ tching the %odel

ni% tion periodic lly d ring r n ti%e, e( %ining %odel o tp ts, nd s"ing nother %odeler torevie$ the %odel nd chec" its beh vior.


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to the %odel concept. in lly,se rch lgorith%s incl de the pplic tion o' opti%i tion se rch %ethods s ch s e(h stivese rch, genetic lgorith%, si% l tion nne ling, nd t b se rch to opti%i e n obDective' nction.

Figure &''# Contin o s i%prove%ent $ith si% l tion.


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o' d t , cond cting e(tensive e(peri%ent tion, nd going thro gh sever l progress revie$s nd%ilestones.


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b. Proble% ss %ptionsc. St dy obDectives

3. ig re 6.)3 , the ? e( %ple consists o' three st tions9the tri ge st tion, $here p tients record their n %es nd 'ill o t the tri ge 'or%O the receptionst tion, $here the st tion ttend nt enters their d t into co%p ter nd cre tes %edic l 'iles 'orne$ p tientsO nd the tre t%ent roo%, 'or physici n di gnosis. I' p tient needs ' rthertre t%ent, he or she $ill be sent to speci list doctor 4i.e., internist, c rdiologist, gynecologist,ophth l%ologist, etc.5 >or serio s %edic l e%ergencies 4i.e., ccidents, he rt tt c"s,
http://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/viewer.asp?bookid=16837&chunkid=775345360#N678ABCEE34C-FFF0-4531-8465-E3FB89C37299%23N678ABCEE34C-FFF0-4531-8465-E3FB89C37299http://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/viewer.asp?bookid=16837&chunkid=775345360#N678ABCEE34C-FFF0-4531-8465-E3FB89C37299%23N678ABCEE34C-FFF0-4531-8465-E3FB89C37299http://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/viewer.asp?bookid=16837&chunkid=775345360#N678ABCEE34C-FFF0-4531-8465-E3FB89C37299%23N678ABCEE34C-FFF0-4531-8465-E3FB89C37299http://0-library.books24x7.com.innopac.library.unr.edu/viewer.asp?bkid=16837&destid=387#387http://0-library.books24x7.com.innopac.library.unr.edu/viewer.asp?bkid=16837&destid=738#738http://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/viewer.asp?bookid=16837&chunkid=954389117#wbp10Chapter6P266ABCEE34C-FFF0-4531-8465-E3FB89C37299%23wbp10Chapter6P266ABCEE34C-FFF0-4531-8465-E3FB89C37299http://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/viewer.asp?bookid=16837&chunkid=954389117#wbp10Chapter6P266ABCEE34C-FFF0-4531-8465-E3FB89C37299%23wbp10Chapter6P266ABCEE34C-FFF0-4531-8465-E3FB89C37299http://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/viewer.asp?bookid=16837&chunkid=775345360#N678ABCEE34C-FFF0-4531-8465-E3FB89C37299%23N678ABCEE34C-FFF0-4531-8465-E3FB89C37299http://0-library.books24x7.com.innopac.library.unr.edu/viewer.asp?bkid=16837&destid=387#387http://0-library.books24x7.com.innopac.library.unr.edu/viewer.asp?bkid=16837&destid=738#738http://0-library.books24x7.com.innopac.library.unr.edu/book/id_16837/viewer.asp?bookid=16837&chunkid=954389117#wbp10Chapter6P266ABCEE34C-FFF0-4531-8465-E3FB89C37299%23wbp10Chapter6P266ABCEE34C-FFF0-4531-8465-E3FB89C37299


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p rt ritions, etc.5, p tients re tre ted directly by doctors $itho t p ssing thro gh the tri ge ndd t /entry st tions.

Figure &'*# Concept l %odel o' the ? e( %ple.

An ? syste% c n be vie$ed s 8 e ing syste% $ith single ch nnel 4i.e., d%ission,tre t%ent, rele se5.


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Data Collection and !nput Modeling A'ter getting per%ission 'ro% the hospit l d%inistr tion,the proDect te % st rted their $or" by observing the sit tion in the ? nd collecting pertinentd t , incl ding co nting the 8 e e o' p tients, %e s ring the service ti%e t v rio s processst ges nd the inter/ rriv l ti%e o' p tients, tr c"ing p tient 'lo$, nd so on. Also, historic l d t'ro% the ? $ere revie$ed nd s %% ri ed.


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+a3le &(# ER Data Colle$tedpen t ble s spre dsheet

!atient@um3er

+ime ofArri4alat+riage5'6

+ime ofArri4alatRe$e tion 5(6

+ime ofStarting the+reatment

+ime of!atientDe arture 5*6

+imeBet7eenArri4als5min6

Ser4i$e+ime'5min6

Ser4i$e+ime(5min6

Ser4i$e+ime*5min6

)7 )29)0

)29)) )29)2 )29) )0 ) ) 7

) )2930

)293) )293 )293+ 20 ) 7 3

)6 )2930

)293) )2936 )2970 0 ) 7

)* )2930

)293) )293+ )2970 0 ) * 2

)+ )293 )2936 )2936 )2970 ) ) 7

) )2970

)297) )297 )29 0 )

20 )290

)29 ) )29 )3900 )0 )

2) )290

)29 ) )29 + )39)0 0 ) + )2

22 )290

)29 ) )29 6 )39) 0 ) 6 )

23 )290

)29 ) )29 )3900 0 )

27 )3920

)392) )3922 )3930 30 ) 2 +

2 )3930

)393) )393 )7900 )0 ) 2

26 )3930

)393) )393 )3970 0 )

2* )393 )3936 )7900 )7930 ) 2 30

2+ )7900

)790) )79)0 )79)2 2 ) )0 2

2 )790 )790) )790 )7920 0 ) )


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+a3le &(# ER Data Colle$tedpen t ble s spre dsheet

!atient@um3er

+ime ofArri4alat+riage5'6

+ime ofArri4alatRe$e tion 5(6

+ime ofStarting the+reatment

+ime of!atientDe arture 5*6

+imeBet7eenArri4als5min6

Ser4i$e+ime'5min6

Ser4i$e+ime(5min6

Ser4i$e+ime*5min6

0

30 )797 )7976 )797+ ) 930 7 ) 3 72

3) ) 930

) 93) ) 93 )6900 3 ) 2

32 +92 +933 +973 +9 0 7 )0 )0

33 +9 * +9 900 90 )+ 2 )

37 90 906 936 970 + ) 30

3 90* 90+ 9)6 92) 2 ) + 7

36 970 97) )0900 )0920 33 ) ) 20

3* 9 0 9 ) )0920 )0930 )0 ) 2 )0

3+ 9 9 6 )0930 ))900 ) 37 30

3 )090

0

)090) )0970 ))900 ) 3 20

70 )0900

)090) )09 0 ))970 0 ) 7 0

7) )09)0

)09)) )09)2 ))900 )0 ) ) 7+

72 )093 )0936 )0970 ))920 2 ) 7 70

73 )093 )0936 )097) ))900 0 ) )

77 )0970 )097) )097 ))930 ) 7 7

7 )09 )09 6 )09 + )29)0 ) ) 2 *2

76 ))900

))90 ))9)0 )2930 +0

7* ))9) ))9)6 ))920 )2900 ) ) 7 70


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1istrib tion9e(ponenti l?(pression9 0.00) ? P 4)7.65S8 re error90.002 0

1 t s %% ry# %ber o' d t points T

in.d t v l e T 0(.d t v l e T )2S %ple %e n T )7.6S %ple std.dev. T 2).2

Chi/s8 re test# %ber o' interv ls T21egrees o' 'reedo% T 0ig re 6.)7 .


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Figure &'%# A to od ni% tion o' the ? %odel.ntity3 p tients

/ttri'utes3 he lth 4cl ssi'ic tion o' ? p tients5 /cti-ity3 tre t%ent

ogenous e-ent3 rriv l o' p tientsndogenous e-ent3 co%pletion o' tre t%ent 4dep rt re o' p tients5

State -aria'le3 n %ber o' p tients $ iting, n %ber o' b sy doctors, etc.

Model Results ig re 6.) , tot l o' )00) p tients $ere tre ted t the ? , o' $hich 3*3 p tients $erecl ssi'ied s serio s. A tot l o' 62+ p tients $ent thro gh the three ? st tions, st rting $ithtri ge.


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Figure &' # S %% ry o' A to od reso rce st tistics.

@ sed on %odel observ tions nd %odel st tistics, the 'ollo$ing %e s res $ere t "en to i%prove? oper tions. I%prove%ent e''orts re 'oc sed on red cing p tient $ iting ti%e be'ore service,

registr tion ti%e, nd $ iting 'or tre t%ent ti%e.


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In this ch pter $e presented det iled description o' the si% l tion process, incl ding the det ilso' si% l tion proced res 'or proDect scoping, d t collecting, %odel b ilding, %odel n lyses, nd%odel doc %ent tion. SS ppro ches.

Simulation Text

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