creativitatea -cap.3 prognoza tehnologică

8/8/2019 Creativitatea -cap.3 Prognoza Tehnologic

1/14

3

Prognoza = HYDOXDUHD SUREDELO VWDELOLW vQ PRG WLLQ LILF D HYROX LHL FDOLWDWLYH L

cantitative a unui domeniu ntr-un interval de timp (numit orizontul prognozei L VWDELOLUHD

HYROX LLORULVW ULORUSRVLELOHDOHGRPHQLXOXLSUHFXPLSUREDELOLW LOHDVRFLDWHORUFXVFRSXOGHD

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$XGLVS UXWFXWRWXO rigla de calcul tablele de logaritmi motorul de avion cu elice a fost practic total nlocuit n transportul aviatic civil de cel cu

UHDF LH

tuburile electronice cu vid ceasurile cu arc OHPQXOGLQUDFKHWHOHGHWHQLVGLQVFKLXULGLQSU MLQDGHODDWOHWLVP

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Caracteristicile prognozelor:

Orizontul de timp; Gradul de detaliere; 1DWXUDGHFL]LHLFHWUHEXLHOXDW SHED]DVWXGLXOXL 6WDELOLWDWHDVLVWHPXOXLOHJHDGHHYROX LHDVLVWHPXOXLWLSXOGHPRGHO CostulLPSOLFDWGHDFWLYLWDWHDGHSURJQR] costul de punere a punct a metodei; FRVWXULOHGHDFWXDOL]DUHDPHWRGHLLDGDWHORU ; FRVWXULOHGHUHDOL]DUHSURSULX]LV DSURJQR]HL costurile de comparare a rezultatelor cu cele ale altor metode. Precizia 8XULQ DGHDSOLFDUH

&HD PDLLPSRUWDQW FODVLILFDUH DWHKQLFLORUGHSURJQR] HVWH FHD FDUHOHvPSDUWH vQWHKQLFL

cantitativeLcalitative.

352*12=$7(+12/2*,&

3.1. Metode cantitative de previziune3.2. Metode calitative de previziune3.3. 6FHQDULLOHFDPHWRG GHSURJQR]


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3.1. Metode cantitative de previziune

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FXOHVHODPRPHQWHGLIHULWHGLQWUHFXW2E LQHPDVWIHOLUXO;W3HED]DYDORULORU;LFXLGHODOD

t (t fiind momentul prezent) putem calcula valorile estimate pentru perioada (sau, uneori,

SHULRDGHOH XUP WRDUH 6W 6WQ 3UH]HQW P vQ ILJ - VFKHPD GH FRUHVSRQGHQ D

variabilelor.

V a l RULP VXUDWH9DORULSURJQR]DWH

Valorile X(1) X(2) X(3) ..... X(t-1) X(t) S(t+1) S(t+2) S(t+3)

Perioada 1 2 3 ..... t-1 t t+1 t+2 t+3

momentul actual

Fig. 3.1. -9DORULOHP VXUDWHYDORULOHSURJQR]DWHLWLPSXO

S(t+1) = F [ x(1), x(2), ....., x(t)]

(URDUHDFDOFXODW FkQGHYHQLPHQWXOV-a produs) : e(t+1) = S(t+1) - x (t+1)

3.1.1. Tehnicile de regresie.

0HWRGDFHORUPDLPLFLS WUDWH

y = f(t) astfel nct: [y(t) - x(t)]2 = minim

Pentru dreapta: y = a + b t

a = [( X) - b ( t)] / nb = [n ( X.t ) - ( X)( t) ] / [n ( t2 ) - ( t)2 ]

Pentru plinomiala: y = a + b t + c t2 + d t3 + .....

FRHILFLHQ LLDEFGVHFDOFXOHD] FXDMXWRUXOXQRUUHOD LLVLPLODUHFHORUGHPDLVXV

3HQWUXDOWHIXQF LLVHIDFHRlinearizare. Exemple:

y = a ebt (logaritmare) ln y = ln a + b t similar cu y' = a' + bt ;

y = a + b / x (x' = 1 / x) y = a + b x'

$OHJHUHDIXQF LHLRSWLPH

Criteriul lui Gauss. ,QGLFHOHGHFRQFRUGDQ vQWUHPXO LPHDSXQFWHORU;WLQWURGXVHLDpunctelor Y(t) calculate cu

IXQF LDDOHDV


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0HWRGHGHSURJQR] SULQILOWUDMDGDSWLY

Metoda mediilor mobile:

S(t+1) = [X(t) + X(t-1) + ...... + X(t -n +1)] / n

0HWRGDQHWH]LULLH[SRQHQ LDOH

S(t+1) = x(t) + (1-) x(t-1) + (1-)2 x(t-2) + (1-)3 x(t-3) + ...... [ 0


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3.2.1. Metoda curbelor logistice

Fig.3.2.-(YROX LDXQHLWHKQRORJLLGXSDRFXUE ORJLVWLF

y = p / (1 +a e-bx) unde: p = plafonul; a,b = parametrii.

'HPRQVWUD LH3HQWUXSHULRDGDLQL LDO VHSRDWHDGPLWHF FUHWHUHDYDILSURSRU LRQDO FX

nivelul atins, deci:dy / dt = k.y(t)

9DORDUHDOXLNYDULD] SHP VXU FHQHDSURSLHPGHSILHEN- y(t) / p)

dy / dt = k ( 1 - y / p) y

ceea ce prin separarea variabileloULLQWHJUDUHQHG \WS>S\- 1) e-bx ]

DGLF H[DFWHFXD LDORJLVWLFLLFXDS\R-XQGH\RHVWHYDORDUHDLQL LDO DOXL\

Tab. 2.2.-1 Caracteristicile economice ale diferitelor tipuri de procese tehnologice

Tehnologii emergente evolutive mature n declin

&XPS -

U WRUL

cu venituri mari WRWPDLPXO L FRQVXPGHPDV U PkQFHLILGHOL

Produs FDOLWDWHPHGLRFU

OLSV VWDQGDUGH

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GLIHUHQ LHULPDUL

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norme respectate de

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calitate mai

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noilor produse

DS UXWH

Riscuri

fabricant

nalte minime, acoperite

de cererea n

FUHWHUH

mici certitudinea

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curnd.

Profituri mici mari f. mari vQVF GHUHConcu-

UHQ

cteva firme multe firme, dar

este loc pt. toate

DFHUE SULQSUH XUL vQVF GHUH

)DEULFD LH serii scurte, costuri

mari

subcapacitate,

serii mari

RSWLPL]DW FRVWXUL

minime

supra-capacitate

Vnzare UHFODP IVXV LQXW vQFUHWHUH

PDUFDW

segmen-WDUHSLD UHGXFHUHSLD


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Fig. 3.2. - (YROX LD vQ WLPS D

familiilor posednd produse din

domeniul electro - PHQDMHUvQ )UDQ D

1985.

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PDLQLGHVS ODWYDVH

Fig. 3.2. -6LWXDUHDSHORJLVWLF DFXSWRDUHORU

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Fig..3.2. - (YROX LD GLIHULWHORU

PDVH SODVWLFH SULQ SULVPD VLWX ULL ORU SH

ORJLVWLF vQ

Fig.3.2.-6XFFHVLXQHDXQRUWHKQRORJLLvQGRX YDULDQWH$%GH

HYROX LHDGRPHQLXOXLWHKQRORJLF


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Fig. 3.2.-6 Efectele

economice ale unei

noi tehnologii

6SD LXOWUDQVIHUXULORUGHWHKQRORJLH

3URJQR]DH[SORUDWLY

Nivelul tehnologic:

Treapta 1: 5HVXUVHWLLQ LILFH.Treapta 2: Resurse tehnologice.

Treapta 3: Tehnologii elementare.

Treapta 4: Sisteme tehnologice.

NivelulFRQVHFLQ HORU:

Treapta 5: Aplicatii.

Treapta 6: Mediul ambiant.

Treapta 7: Sistem social

Treapta 8: Societatea.

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sistemul n mai multe nivele n cadrulF URUDWRDWHSUREOHPHOHDXHJDO LPSRUWDQ

12345678 :

prognozprognoz

explorativnormativ

alte ramuriindustriale

alte firmealte ri

Prognoza normativ

8. Obiective globale7. Obiective naionale

6. Misiuni

5. Sarcini de ndeplinit

4. Uzine noi

3. Tehnologii noi2. Cereri de brevete

1. Contracte de cercetare


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courier Problemele pe care le ntlnim la nivelul imediat inferior sunt turbina, compresorul,

giroscRSXOLVLVWHPXOGHFLUFXOD LHDJD]HORU

Tab.3.2. -&DOFXOXOSHUWLQHQ HLSUREOHPHORUGHUH]ROYDWGHODQLYHOXOi + 1.

Criteriul :

putere PDV manevrabilitate cost SHUWLQHQ

Pondere : 0,4 0,3 0,1 0,2

7XUELQ 0,25 0,4 0 0,2 0,26Compresor 0,25 0,4 0 0,3 0,28

Giroscop 0 0 0,8 0,25 0,13

&LUFXOD LHgaze

0,5 0,2 0,2 0,25 0,33

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(2) [curbaa]UHVSHFWLYSHQWUXF ]LOHGHEDLHGLQIRQW LGLQSODVWLFHFRPSR]LWH[curbab]


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fig. 3.2 - 8. Ponderea maselor plastice n structura

unei aeronave.

(1) Helicoptere militare;

DYLRDQHGHYkQ WRDUH

(3) avioane civile.

&XUEHOH L "indicatori de avanstehnologic".

3.2.5. Metoda Delphi

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ele:

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tehnologicului);

UXSWXULOHGHULWPVXQWLHOHGHRVHELWGe rapide; factorii demografici, socio-FXOWXUDOLSROLWLFLOHHQHUJHWLFHFXQRVFGLQFRQWU XQJUDGPDUHGH

LQHU LHFHHDFHFUHD] QXPHURDVHWHQVLXQL

Fig. 3.3. - 1. Utilizarea scenariilor pentru stabilirea politicii firmei.

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Fig. 3.3. - 2. Principalele etape ale construirii unui scenariu.

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V ILHGHWDOLDW LDSURIXQGDW SHSODQFDOLWDWLYLFDQWLWDWLY V ILHJOREDO OXkQGvQ FRQVLGHUD LHIDFWRULLWehnologici, economici, politici, sociologici, de

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Delimitarea sistemului LPSOLF PDL vQWkL VWDELOLUHD OLPLWHORU VLVWHPXOXL GH VWXGLDW

Determinarea variabilelor. WUHEXLHI FXW ROLVW FRPSOHW DYDULDELOHORUFDUHWUHEXLHV FRQ LQ

variabilele interne, cele care caraFWHUL]HD] GRPHQLXOQRVWUX YDULDELOHOH H[WHUQH FHOH FH DSDU LQ HQYLURQPHQWXOXL H[SOLFDWLY L FDUH SRW LQIOXHQ D

comportarea domeniului interesant pentru noi;

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1. CONSTRUIREA BAZEI

2. ELABORARE SCENARIU

3. ELABORARE PROGNOZE

4. DEFINIRE STRATEGII

5. ALEG(5(175(23 ,81,675$7(*,&(


11/14

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YDULDELOHOHGHULYDWHFHOHFHHYROXHD] FDXUPDUHDDF LXQLLGHWHUPLQDQ LORU2DOW FODVLILFDUHPDLDSURSLDW GHWHRULDVLVWHPHORUGLVWLQJHYDULDELOH

explicative ( variabile independente comandabile), de releu (intermediare), autonome (independente necomandabile), UH]XOWDQWHGHLHLUH

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vQWUHE UL FKHFN-list),. Pornind de la trecut spre prezent (retrospectiva) se pot separa elementele

aleatorii de moment (ale prezentului) de tHQGLQ DJHQHUDO LQYDULDQ LLGHWHUPLQDQ L'HDVHPHQHD

se pot identifica germenii de schimbare, semnalele slabe.

Strategia actorilor. 7UHEXLH LQXWVHDPDGHIDSWXOF GLIHUL LLDFWRULQXDXLQWHUHVHLGHQWLFHL

nici strategii convergente.Deci vor treEXLVWDELOLWHVWUDWHJLLOHDFHVWRUDUDSRUWXULOHGHIRU HGLQWUHHL

LHYHQWXDOHOHPHQWHOHFDUHSRWGHWHUPLQDHYROX LDvQYLLWRUDUDSRUWXULORUGHIRU H9RUUH]XOWDDVWIHO

VHQVXOLW ULDIRU HORUUH]XOWDQWHFHOHFDUHGHWHUPLQ vQIRQGHYROX LDVLVWHPXOXL.

&RQVWUXF LDVFHQDULXOXLPentru n ipoteze vor rezulta 2n scenarii posibile !

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matrice):

p (i / j) = probabilitatea ca ipoteza i V VHFRQILUPHGDF VHFRQILUP LSRWH]Dj;

p (i /j ) = probabilitatea ca ipoteza i V VHFRQILUPHGDF LSRWH]Dj QXVHFRQILXUP

4. 1RUPDOL] PGDWHOHDVWIHOvQFkW0 p(i) 1p(i/j) . p(i) = p(j/i). p(j) = p(i,j)

DWHQ LHSLMSLSMGHRDUHFHSLLSMQXVXQWLQGHSHQGHQWHvQWUHHOH p(i/j).P(j) + p(i/j ).p(j ) = p(i)

5. 3ULQLWHUD LLVXFFHVLYHVHUHFDOFXOHD] SLSLMLSLj ), folosind fie metoda Monte CarloILHPHWRGDODQ XULORU0DUNRY

6. &DOFXODUHDSUREDELOLW LORUGHUHDOL]DUHDVFHQDULLORU36P(Sj) = p(i)

7. 6HHOLPLQ YDULDQWHOHDEVXUGH.8. 6HUHFDOXOHD] SHQWUXFHOHS VWUDWHYDORUL P(Sj) = k.P(Sj)

XQGHNVHFDOFXOHD] DVWIHOvQFkW P(Sj) = 1,


12/14


13/14

Descompunerea sistemului n subsisteme independente la momentul m

(YROX LDILHF UXLVXEVLVWHPWHQGLQ HVWUDWHJLLLQYDULDQ LDPG.

5HFRPSXQHUHDVLVWHPXOXLHYLGHQ LHUHFRQIOLFWHWHQGLQ HQRL

FRQVHFLQ HHYROX LHUXSWXUL

Fig. 3.3. -(YROX LDVXEVLVWHPHORUvQWUHPRPHQWHOHPLP

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Incertitudini RISC intuitiv Obiective pe termen lung

SCENARII STRATEGII

variabile cheie Criterii

beneficiu sperat Beneficii cerute IXUHW EHQHILFLL RISC cuantificat Beneficii posibile

GHFL]LHVWUDWHJLF

6FHQDULXSULYLQGHYROX LDXQXLDHURSRUWFLYLO

Ne intereseD] HYROX LDXQXLDHURSRUWFLYLOGDWSHXQLQWHUYDOGHWLPSGDW,SRWH]HOHGHOXFUX

vor fi:

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4. 3UH XOXQXLELOHWGHDYLRQYDVF GHDFXFHOSX LQ65. 3kQ ODRUL]RQWXOGHWLPSVWXGLDWYHQLWXOSRSXOD LHYDFUHWHvQPHGLHFX9SHDQ6. ([WLQGHUHDRUDXOXLspre aeroport va impune o anulare a zborurilor de noapte cu un procent de

RZ %

(unde evident NT, CP, MN, S,V,RZ primesc valori numerice concrete)

6 SUHVXSXQHP GH DVHPHQHD F LQL LDO FHORU LSRWH]H OL V-DX DWULEXLW SUREDELOLW LOH SS

egale resSHFWLYFXLDUSUREDELOLW LOHFRQGL LRQDWHLQL LDOHVXQWFHOHGLQ

tab. 3.3. - 1.

Tab. 3.3.-3UREDELOLW LOHFRQGL LRQDWHLQL LDOHSLMSLj )

1 2 3 4 5 6

1 0,5 / 0,3 0,7 / 0,4 0,8 / 0,1 0,6 / 0,1 0,4 / 0,5

2 0,8 / 0,3 0,5 / 0,7 0,9 / 0,6 0,7 / 0,7 0,9 / 0,6

3 0,7 / 0,6 0,4 / 0,7 0,7 / 0,6 0,7 / 0,6 0.8 / 0,4

4 0,8 / 0,1 0,6 / 0,3 0,4 / 0,4 0,4 / 0,1 0,1 / 0,7

5 0,7 / 0,6 0,6 / 0,6 0,6 / 0,6 0,8 / 0,6 0,6 / 0,6

6 0,5 / 0,8 0,8 / 0,5 0,5 / 0,7 0,7 / 0,7 0,9 / 0,7

,QXUPDSUHOXFU ULLSULQPHWRGD0RQWH&DUORUH]XOW PDWULFHDGLQWDE- 2.


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Tab. 3.3. -3UREDELOLW LOHSUHOXFUDWHSULQDSOLFDUHDPHWRGHL0RQWH&DUOR

p(i / j) / p (i / j )p(i)

1 2 3 4 5 6

1 0,55 / 0,14 0,50 / 0,29 0,83 / 0,13 0,50 / 0,25 0,35 / 0,57 0,41

2 0,89 / 0,51 0,57 / 0,83 0,85 / 0,55 0,66 / 0,69 0,77 / 0,42 0,67

3 0,72 / 0,52 0,51 / 0,79 0,63 / 0,58 0,60 / 0,60 0,63 / 0,54 0,60

4 0,81 / 0,11 0,51 / 0,18 0,42 / 0,38 0,47 / 0,28 0,31 / 0,62 0,40

5 0,78 / 0,54 0,63 / 0,67 0,64 / 0,64 0,75 / 0,57 0,66 / 0,61 0,64

6 0,59 / 0,78 0,81 / 0,48 0,73 / 0,66 0,54 / 0,81 0,72 / 0,68 0,70

9RP HOLPLQD DD FXP DP VSXV 3 GDU L GH H[HPSOX 3 FDUH DU

preVXSXQHF QXP UXOGHWXULWLDUVF GHDvQFRQGL LLOHvQFDUHSUH XOELOHWHORUVFDGHLDUYHQLWXULOH

FUHVF5H]XOWDWHOHRE LQXWHILQDOYRUFODVLILFDVFHQDULLOHDVWIHO

S 12 P(0,0,1,0,1,1) = 0,158

S 14 P(0,1,0,0,1,1) = 0,110

S 30 P(0,1,0,0,0,1) = 0,097 Nucleul (6 p ! 0,.5)S 01 P(1,1,1,1,1,1) = 0,092

S 60 P(0,0,1,0,0,0) = 0,070

:

S 33 P(1,1,1,0,1,0) = 0,057

: scenarii contrastante

S 48 P(0,0,0,1,0,1) = 0,029

:

S 18 P(0,1,1,1,0,1) = 0,017

S 63 P(1,0,0,0,0,0) = 0,014 scenarii posibile dar improbabile

S 53 P(1,1,0,1,0,0) = 0,004

S 36 P(0,0,1,1,1,0) = 0,0019RP FDOFXODDSRL PDWULFHD GHHODVWLFLWDWH SH FDUH R SUH]HQW P vQ WDE - 3. pentru o

YDULD LHDSUREDELOLW LORUp = 0,1.

Tab. 3.3. - 3. Matricea de elasticitate.

1 2 3 4 5 6 6~~1 - 0,12 - 0,24 - 0,47 - 0,23 - 0,54 1,60

2 0,4 - 1,1 (**) 0,24 (*) - 0,71 - 0,21 2,66

3 - 0,28 - 0,96 - 0,64 - 0,74 - 0,64 3,26

4 - 0,37 - 0,20(*) - 0,39 - 0,30 - 0,61 1,87

5 - 0,13(*) - 0,71 - 0,74 - 0,26 - 0,69 2,53

6 - 1,32(**) - 0,09(*) - 0,73 - 1,60(**) - 0,76 4,506~~ 2,50 2,08 3,20 3,21 2,74 2,69

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