JGM1-090288 TDM
TDM SBD MBR TDM
TDM
1.0 Introduction Answer TDM TDM
1.0 Introduction TDMAnswer Answer
1.0 Introduction TDMAnswer Answer P 0.299246 1.578061 0.80742 Pc 0.097709 P 1.9491 1.080442 MR 0.14806 MR 16.83318 0.05198 Twg 3.97e 05 2 0.1314m 1.6761m 4.6805 0.5344 Td( Pexin, Texin, m&, Tc, tp, tc, tw, ) 2 0.0423 Td c 0.3203 Tdc 1.1148 Td 0.534 Td Pexin Texin m& Tc Pexin Texin m& Tc Td Td tw tw
1.0 Introduction TDM TDM TDM TDM
TDM TDMTotal Design Management SBD MBR
SBD MBR CAE
TDM SBD MBR TDM
SBD GG MC y=ax+b
SBD X M E R C XME Y Y X[Y M1 ] X[Y M1 ]
SBD EXCEL
MBR P 0.299246 1.578061 0.80742 Pc 0.097709 P 1.9491 1.080442 MR 0.14806 MR 16.83318 0.05198 Twg 3.97e 05 2 0.1314m 1.6761m 4.6805 0.5344 Td( Pexin, Texin, m&, Tc, tp, tc, tw, ) 2 0.0423 Td c 0.3203 Tdc 1.1148 Td 0.534 Td Pexin Texin m& Tc Pexin Texin m& Tc Td Td tw tw
TDM
TDM
MBR 1.2 1.2 SBD MBR SBD1.2 1.2
GG MC
GG MC SBD MBR
Td tw tw Td tc tc Td tp tp Td Tc Tc Td m m Td Texin Texin Td Pexin Pexin Td tw tc tp m Tc Texin Pexin Td & & & ),,,,,,, ( 0.5344 1.1148 0.3203 0.0423 0.5344 4.6805 1.6761 0.1314 05 3.97 0.05198 16.83318 0.14806 1.080442 1.9491 0.097709 0.80742 1.578061 0.299246 2 2 2 2 2 c c m m Twg e Twg MR MR Pc Pc P * 0.510897 1 1 tan 1 1 4 1 1) 2( 1 2 2 1 L D pinjf pinjo MR Tc Tc MR pinjf pinjo MR MR
SBD MBR GG MC
GG MC SBD MBR
SBD MBR
SBD MBR SBD MBR
GG GG MC MC SBD MBR
SBD MBR
101/2 SBD MBR SBD MBR
102/2
MC GG GG MC GG MC TDM P/N S/N SN
3D FEM CFD 3D FEM CFD 3D FEM CFD TDM GG MC 3D FEM CFD 3D FEM CFD
QFD X E R C + CFD XE Y Y X[Y] X[Y] isight GA
TDM X TDM M E R C X M E R 1 XME Y XME Y Y Y SN S/N X[Y M1 ] X[Y M1 ] X, X SN
TDM X TDM M E R C X M E R 1 XME Y XME Y Y Y SN S/N X[Y M1 ]X[Y M1 ] X, X SN
TDM X TDM M E R C X M E R 1 XME Y XME Y Y Y SN S/N X[Y M1 ] X[Y M1 ] X, X SN
TDM X XME Y Y TDM M X[Y M1 ] E X[Y M1 ] R SBDMBR C SBDMBR X XME Y X, M 1 Y X S/N SN E R SN
SDB ITIT DSM SOM
QFDFMEAFTADSM D FORM CAE (1) SNAIC (2) RBFSVR LPQP SAGA SN SOM DFSS isight, ModelCenter
CFDFEM LL FORM CCD) TDM FMEA/FTA, GA AHP OR 2 S/N 22 QFD
TDM
TDM (2007)
TDM TDM (2007)
QFDTOPSIS
. TDM TDM QFD TRIZ TRIZ VE TOPSIS A HOPE Combined Array B
. QFD (1/6) (QFD) RFP (Request For Proposal) X-Prize - 100[km] - - (3G) - 3000[m] () -
. QFD (2/6) RFP / () (/) / (/) ()
. QFD (3/6) () AHP* 100km100km 2 3G 3G 4 6 8 10 12 6 6 14 16 18 20 *AHP: Analytic Hierarchy Process ()
. QFD (4/6) () (/) (/) 100km100km 2 3G 3G 4 6 / 8 () / 10 12 6 6 14 16 18 20 ()
. QFD (5/6) QFD ()
. QFD (6/6) QFD 100km 3G 6 QFD ()
1/3 () () ()
2/3 Morphological Matrix I (Morphological Matrix I) Morphological Matrix I?
3/3 Morphological Matrix II Morphological Matrix I Morphological Matrix II () No3 No3 ()
TOPSIS1/8 Pugh Evaluation Matrix (Decision Matrix) QFD Pugh Evaluation Matrix 100km 3G QFD QFD (+) (+) (-) (-) (s) (s) *TOPSIS: Technique for Order Preference by Similarity to Ideal Solution ()
TOPSIS2/8 (1/3) Pugh Evaluation Matrix (+) (+) 9 9 (-) (-) 5 5 (s) (s) 1 1 *TOPSIS: Technique for Order Preference by Similarity to Ideal Solution ()
TOPSIS3/8 (2/3) 0.48 5 2 5 2 5 2 5 2 1 2 1 2 1 5 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2
TOPSIS4/8 (3/3) QFD 0.46 0.48 0. 022 QFD QFD
TOPSIS5/8 ideal negative
TOPSIS6/8 S S i i V V i ideal V ivnegative 2 2 NO,3 S i S i ideal negative Vi V ideal V nagative 2 V V S i ideal 2 V V S i negative i i
TOPSIS7/8 TOPSIS C i S * i S i S i Ci Ci worse Ci 0 S i negative S i ideal better Ci 1 *1(DATUM) No.2No.6No.8 BETTER ANSWER No.6 No.2 No.8
TOPSIS8/8 TOPSISDATUM TOPSIS QFD
:TOPSIS Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Pugh Matrix Concept Selection Best: Concept #2 Concept #3 Worst: Concept #1 +/- Ideal Solution QFD +/- TOPSIS Euclidean Differences + #1 #2 -
2003 TOPSIS
The MADM Techniques Type of Information from the Decision Maker No Information Salient Feature on Information Major Classes of Methods Dominance Maximin Maximax Standard Level Conjunctive Method Disjunctive Method Lexicographic Method Multiple Attribute Decision Making Information on Attribute Ordinal Cardinal Marginal Rate of Substitution Elimination by Aspect Permutation Method Linear Assignment Method Simple Additive Weighting Method (SAW) Hierarchical Additive Weighting Method ELECTRE TOPSIS Hierarchical Tradeoffs Information on Alternative Pairwise Preference Order of Pairwise Proximity LINMAP Interactive SAW Method MDS with Ideal Point
TDM QFD TRIZ TRIZ VE TOPSIS HOPE A B Combined Array
TDM FMEAFTA Combined Array
IHI TDM