THESIS FOR MASTER OF BUSINESS ADMINISTRATION GRADUATE SCHOOL OF MANAGEMENT SCIENCES
ALETHEIA UNIVERSITY
Jan, 2009
AdvisorRui-Yang Chen Ph. D.
THE INTEGRATION OF CROSS-INDUSTRIAL PRODUCT
INTERFACE: A CASE STUDY OF CAR ELECTRONIC CONTROL UNIT
Graduate Student: Jia-Hau Ke
-
90
ECU
KT
AHPAnalytic Hierarchy Process
KT AHP
Title of ThesisThe Integration of Cross-Industrial Product Interface: A Case Study of Car Electronic Control Unit
Key wordsKT method, Analytic Hierarchy Process, Product interface, Car Electronic
Name of InstituteGraduate School of Management Sciences, Aletheia University
Graduate DateJan, 2009 Degree ConferredMaster Degree
Name of StudentJia-Hau Ke AdvisorRui-Yang Chen Ph. D.
Abstract
In opposition to the micro profit situation of electronic information industry intense competition, the car electronic industry combined the advantage of electronic information with car product components to make it more intelligent in information function. Furthermore, the combination extend a new business of application field in the electronic information industry. In the cross-industry product integration process, the problems of individual product components interface may influence the quality and usefulness of the whole electronic components product. Besides, in the process of interface integration, it may occur the conflicts between the two diffirent industrial products and increase the difficulties of integration. The integration connected to the safety and application of car electronic products. The key point of cross-industry integration is how to avoid conflicts and make product interface integration effectively.
This study takes the car electronic control unit for example. The main purpose of this study is to discuss the probable problems of cross-industry product interface integration. We use the KT method to do the substantial evidence analysis for cross-industry product interface integration problems. Furthermore, we combined the results of Analytic Hierarchy Process(AHP) and experts questionnaire to construct the solution oriented of cross-industry product interface integration problems.
I
IV
V
1
........................................................................................ 1
........................................................................................ 4
........................................................................................ 5
........................................................................................ 7
........................................................................................ 8
10
KT............................................................................................. 10
.............................................................................. 11
.............................................................................. 13
.............................................................................. 15
...................................................................................... 16
.............................................................................. 19
.................................................................................. 21
AHP ......................................................................... 22
I
29
...................................................................................... 29
KT ........................................... 31
AHP .................................. 45
.............................................................................. 48
50
.............................................................................. 50
.............................................................................. 52
.............................................................................. 54
Fuzzy KT ..................................................... 58
AHP ..................................................................... 67
75
.............................................................................................. 75
...................................................................................... 77
.......................................................... 77
79
...................................................................................................... 79
...................................................................................................... 80
II
III
...................................................................................................... 82
84
1-1 9
2-1 KT 11
2-2 12
2-3 15
2-4 AHP 28
3-1 30
3-2 32
3-3 KT 37
3-4 38
3-5 39
3-6 40
3-7 AHP 47
4-1 Expert Choice 2000 AHP () 73
IV
2-1 AHP 25
2-2 27
3-1 36
3-2 KT 37
3-3 42
3-4 44
3-5 44
4-1 A 51
4-2 ECU 54
4-3 58
4-4 KT159
4-5 161
4-6 262
4-7 KT263
4-8 65
4-9 KT365
4-10 66
4-11 AHP 67
V
4-12 68
4-13 69
4-14 69
4-15 70
4-16 AHP 72
VI
1
70%
2005
2
Mercedes
-Benz Carl
2005
2004
3
2005
2005
ComputerCommunication
Consumption 3C C Car
Electronic
( 2006 )
4
2005
Strategy Analysis 2004
358 2013 608 2004 2013
GAGR 7.3 3.8
25 40
2007
IT
2007
5
6
2004
KT
7
KT AHP
8
1-1
KT
AHP
9
1-1
KT
AHP
10
KT
KT KT Charles H. Kepner
Benjamin B. Tregoe 1950 RAND
KT Spitzer and Evans1999
KTC.H.KEPNERB TREGOR
2-1
1Situation Analysis-S.A
2Problem Analysis-P.A
3Potential Problem Analysis P.P.A
11
4Decision Analysis-D.A
2-1 KT
12
1
2006
2-2
(2006) (2006)
/
a. /
b. /
a. ( )
(
)
b.
/
a. /
b. /
13
2004 87.22% 2005
2006
37 49 1948-1960
50 59 1961-1970
60 69 1971-1980
14
70 79 1981-1990
IC 80 1991
89 2000
e
2001
IC
2005 9,879 2005
IC 1 1,131 2006 1 2,259
IC IC
TFT-LCD
CDT LCD
2006
15
2-3 %
IEK/
.../
ABS ...
......
IC CPU
MCU
/IC
OEAfter Market
1980
16
2006
NISSAN
IC
IC
IC IC
Handerson & Clark, 1990
17
Stone 2000
Dhebar, 1995Sengupta, 1998:
Muffatto1999
2004
18
Narver & Slater, 1990Kohli and
Jaworski1990
Customer FocusDay1994
Gatignon & Xuereb
1997
19
Song, 1997, 2000Souder, 1997Sethi
DanielPark, 2001
Gatignon & Xuereb,
1997Application Enginning
Zadeh 1965
Crisp Set
20
0 1
0 1
0 1
0 1 Membership Function
Wang & Mendel, 1992
U U x
( )UAA 0 1 x A
A ( )xA ( ) 10 xA ( )xA
1 A
21
Technology ParadigmDosi, 1982
Teece, 1996Teece, 1997
Tushman1986
Competence EnhancingCompetence-Destroyimg
1997Fleming & Koppeman1997
Dougherty1990
22
Fleming & Koppeman, 1997
1997Allen & Hamilton1982Kuczmarski
19921
234
AHP
AHP
AHP MultiobjectiveMulticriteria
T.L.Saaty, 1977
23
AHP
2005
AHP
AHP
Ratio ScalesNorminal Scales
2-4 AHP
5W1HWhatWhyWhereWho
WhenHow
24
Brainstorming
Delphi method KJ
Criteria
Sub-criteria
AHP
1989
1.
2.
3. Saaty
4.
5.
n nn-1/2
25
AHP
1 9
Saaty1990 2-1 AHP
2-1 AHP
1 ( Equal Importance )
3
( Moderate Importance )
5
( Essential Importance )
7
( Very Strong Importance )
9 ( Extreme Importance )
2,4,6,8
( Intermediate Values )
Saaty, 1990
Eigen value
Eigen vectorPriority vector
26
NGM Normalization of the Geometric
Mean of the Rows
= ==
=
=
n
i
nn
jij
nn
jiji n1,2.....,ji, AAW
1
1
1
1
1
++
=
=
=
n
nmax
n
2
1
n
2
1
n
n
nn
WW
WW
n
W
WW
W
WW
AA
....A
A
A
A
L
MMM
L
K
MM
1
1
2
1
2
12
1
12
111
1
1
11
AHP C.R.
Consistency Index , C.I.Consistency Ratio , C.R.
Saaty C.R. 0.1
1=
nn.I.C max
C.I.
27
Random Index , R.I.
1989 N R.I. 2-2 1
11 R.I. 500 12 15 R.I.
100 Saaty, 1990
2-2
N 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
R.I 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49 1.51 1.48 1.56 1.57 1.59
( Satty, 1990 )
C.I. R.I.C.R.
C.R. = C.I. / R.I. C.R. 0.1
C.I.HC.R.H
C.I.HR.I.H
( ) ( ) .I.CH.I.C =
( ) ( ) .I.RH.R.C = H.I.R/H.I.CH.R.C =
10.H.R.C
28
2-4 AHP
1989
C.R.0.1
29
KT AHP
3-1
Fuzzy KT
AHP
30
3-1
Fuzzy KT
Fuzzy set
KT
AHP
KT
31
KT
KT
3-2
Fuzzy KT 1Situation Analysis-S.A
2Problem Analysis-P.A
3Potential Problem Analysis P.P.A
4Decision
Analysis-D.A
a.
b.
c.
d.
e.
3-2
32
3-2
33
34
35
Fuzzy KT
3-3
3-1 3-2
36
Fuzzy
KT
3-4
1
X ( )x
3-1
Fuzzy sets
37
3-3 KT
3-2 KT
Yes No
1
Yes
38
3-2 KT
2
Yes
3
Yes
3-4
( )( )( )( )
39
3-5
Should
Actual
3-6
3-5
Actual
40
3-6
Should
Actual
41
3-3
42
3-3
WHAT? WHERE? WHEN? HOW
MUCH?
1~5
1~5
1
43
State the action
3-4
44
3-4
Fuzzy sets
()
AHP
3-5
3-5
= = =
45
AHP
KT
46
KT
AHP
Fuzzy KT
AHP 3-7
47
3-7 AHP
19
48
NGMNormalization of the Geometric
Mean of the Rows
AHP
1.
2.
AHP
1 9
n nn-1/2
49
Content ValidityPredictive Validity
Construct Validity
AHP
50
KT
AHP
ITA
A19731.5267
A
A
A
20022007
2005
4-1A
51
4-1 A
06 06 IS 06 06 UNIX 06 Windows 06 06
06 06 /06 06 06 06
06 06
06
06 06
A
LIN/CANFlexRayIDB-1394
1985
LANLANLAN
A
IDB-1394LINCAN Flexray
A
A
A
52
100
Electronic Control Unit,
ECU
Electronic Fuel Injection, EFI
ECU
ECU
53
ECU ECU
ECU
ECU
ECU
ECU
ECU
ECU
MPU
4-2
54
4-2 ECU
ECU
ECU
ECUMAP-EGRECU
ECUEST-
ECU
MPU MPU
ECUECU
OBD
ECU-MPU
2005/10
ECU ECU
1V
55
1
0.1V 0.3V
ECU
ECU
ECU
56
ECU
ECU
ECU
ECU
EMI
10 4.5
EMI
EMI
EMI
EMI EMI
ECU EMI
57
ECU
EMI
ECU
ECU
ECU
58
Fuzzy KT
Fuzzy KT
4-3
ECU
ECU
4-3
EMI
Fuzzy sets
1. 1000
2. 6km/l
59
4-3
1.
2.
1.
2.
4-4
YES
4-4 KT1
1000/6km/l
Yes No
1
Yes
60
4-4 KT1
2
Yes
3
Yes
4-5 4-6
ECU
61
4-5 1
WHAT? WHERE? WHEN? HOW MUCH?
(1~5)
700~800
1000
10km/h
15km/h
ECU
1~10
1
1.
2. ECU
6 3 9 4 10 4 5 8 10 5 8 5
62
4-6 2
WHAT? WHERE? WHEN? HOW MUCH?
(1~5)
7~10km/l
6km/l
4~5
1~10
2
1.
2. ECU
6 3 9 4 10 4 5 8 10 5 8 5
63
ECUECU
ECU
KT
4-7
4-7 KT2
1000/6km/l
Yes No
1
Yes
64
4-7 KT2
2
Yes
3
Yes
A10nF
EMI
LAN
FMEMI
30dBA
EMIEMI
EMIEMI
EMI4-8
65
4-8
=0.211 =0.246 =0.543
3 1 3 2.508
3 5 3 3.492
3 3 1 1.914
5 3 3 3.422
4-9
4-9 KT3
1000/6km/l
Yes No
1
Yes
66
4-9 KT3
2
Yes
3
Yes
ECU
4-10
(Fuzzy sets)
()
67
AHP
AHP
AHP Expert Choice 2000
www.my3q.com 20 6
14 20 3
17 4-11
4-11 AHP
20 14 6
20 17 3 31
4-12 77.4%
25~34 45.2%
38.7% 32.3%
/ 71.0%
http://www.my3q.com/68
4-12
%
1.
2.
24
7
77.4
22.6
1. 20~24
2. 25~34
3. 35~44
4. 45
4
14
8
5
12.9
45.2
25.8
16.1
1.
2.
3.
4.
5.
3
10
12
2
4
9.7
32.3
38.7
6.5
12.8
1. ()
2. /
3.
4
22
5
12.9
71.0
16.1
AHP
C.I.C.R. max
Expert Choice 2000 AHP
00.0.. =IC 00.0
00.000.0
R.I.C.I... ===RC
4-13
69
4-13
1 2.24294 0.692 0.692
0.44584 1 0.308 0.308
=max 2.00C.I.=0.00C.R.=0.00
:
692.0692.01 =
083.0083.01 =
C.R.=0.00C.I.=0.00 0.1 Saaty
C.I.C.R. max
Expert Choice 2000 AHP 80.0.. =IC
890.090.0
80.0R.I.C.I... ===RC
4.24max = n 4-14
4-14
=max 4.24C.I.=0.08C.R.=0.089
1 3.81916 6.07159 2.14175 0.182 0.126 2
0.26183 1 6.33682 2.55696 0.061 0.042 4
0.16470 0.15781 1 4.90923 0.642 0.444 1
0.44691 0.39109 0.20369 1 0.116 0.080 3
70
:
0.1260.182692.0 =
042.0061.0692.0 =
444.0642.0692.0 =
080.0116.0692.0 =
C.I.C.R. max
Expert Choice 2000 AHP 70.0.. =IC
780.090.070.0
R.I.C.I... ===RC
4.21max = n 4-15
4-15
=max 4.21C.I.=0.07C.R.=0.078
:
0.0170.0.054308.0 =
0.0370.120308.0 =
0.0810.263308.0 =
1 3.51943 5.10233 6.58694 0.054 0.017 4
0.28414 1 3.18147 5.15938 0.120 0.037 3
0.19599 0.31432 1 3.13030 0.263 0.081 2
0.15182 0.19382 0.31946 1 0.564 0.174 1
71
0.1740.564308.0 =
4-144-15
C.R. 0.0890.078
0.1 Saaty
C.I.C.R. max 4-16
4-16
0.6920.308
4-16
(0.444)0.1740.126
0.0810.080.0420.037
0.017
72
4-16 AHP
0.182 0.126 2 3
0.061 0.042 4 6
0.642 0.444 1 1
=max 4.24 C.I.=0.08 C.R.=0.089 =0.692
0.116 0.080 3 5
0.054 0.017 4 8
0.120 0.037 3 7
0.263 0.081 2 4
=max 4.21 C.I.=0.07 C.R.=0.078 =0.308
0.564 0.174 1 2
Expert Choice 2000 AHP
4-1
0.543
0.2460.211
73
4-1 Expert Choice 2000 AHP
0.4440.174:
1.
IBM
74
2.
OEM ODM
75
76
ECU
KT
AHP
ECUKT
AHP
77
KT
KT
78
KT
KT
79
1. 1997
75-121
2. 1997 IC
3. 2004-
4. 2006 5 486
5. 2006
6. 2005 134
3
7. 2005-
8. 2004-
80
9. 1989AHP
27p5-22
10. 1989AHP
27p1-20
11. 2004-
12. 2006Telematics
67
13. 2005
-
14. Kepner & Tregoe 1986The New Rational Manager
15. Kepner & Tregoe 2004The New Rational Manager
KT
16. Quinn Spitzer & Ron Evans1999HeadsYou Win
1. Booz, E., Allen, J and Hamilton, C., 1982. New Products Management for the 1980s, New York: Booz-Allen & Hamilton, Inc., pp.17.
81
2. Coles, S. and Rowley, J., 1995. Revisiting Decision Trees, Management Decision, 33, 8, pp.46-50.
3. Dhebar, Anirudh, 1995. Complementarity, Compatibility, and Product Change: Breaking with the Past?, Journal of Product Innovation Management, 12, pp.136-152.
4. Dosi, G., 1982. Technological Paradigms and Technological Trajectories, Research Policy, 11, 3, pp.147-162.
5. Dougherty, D., 1990. Understanding New Markets for New Products, Strategic Management Journal, 11, pp.59-78.
6. Fleming, Q. W. and Koppleman, J. M., 1997. Integrated Project Development Teams: another fad ... or a permanent change?, Project Management Journal, 28, 1, pp.4-11.
7. Gatignon, Xubert and Jean-Marc Xuereb, 1997. Strategic Orientation of the Firm and New product Performance, Journal of Marketing Research, 34, pp.77-90.
8. Henderson, R. and Clark, K.B., 1990. Architectural Innovation: The Reconfiguration of Existing Product Technologies and The Failure of Established Firms. Administrative Science Quarterly, 35:9-30.
9. Hillier, F. S., and Lieberman, G. J., 1995. Introduction to Operations Research, NY :McGraw-Hill, New York.
10. Kohli, A. K. and Jaworski, B. J., 1990. Market Orientation: The Construct, Research Propositions and Managerial Implications, Journal of Marketing, 54, 2, pp. 1-18.
11. Kuczmarski, T. D., 1992. Management New Product: The Power of Innovation, New York: Prentice-Hall, Englewood Cliffs, pp.61.
12. L.-X. Wang and J. M. Mendel, 1992. Generatiing Fuzzy Rules by Learning Form Examples, IEEE Trans. Syst., Man, and Cybern., 22, 6, Nov./Dec., pp. 1414-1427.
13. L. A. Zadeh, 1965. Fuzzy set, Information and control, 8, pp.338-353. 14. Muffatto, Moreno, 1999. Introducing a Platform Strategy in Product
Development, International Journal of Production Economics, 60-61, pp.145-153.
15. Narver, J. C. and Slater, S. F., 1990. The Effect of a Market Orientation on Business Profitability, Journal of Marketing, 54, 4, pp.20-35.
16. Saaty, T.L., 1990. The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation, 2nd Ed.,RWS Publications, Pittsburgh.
17. Sengupta, S., 1998. Some Approach to Complementary Product Strategy, The Journal of Product Innovation Management, 15, pp.352-367.
82
18. Sethi, Rajesh, Daniel C. Smith and C Whan Park, 2001. Cross-Functional Product Development Teams, Creativity, and the Innovativeness of New Consumer Products, Journal of Marketing Research. Chicago, 38(1), pp.73-87.
19. Song, X. Michael, Neeley, Sabrina M, and Yuzhen Zhao, 1996. Managing R&D-Marketing Integration in the New Product Development Process, Industrial Marketing Management, New York: November, 25, 6, pp.545-554.
20. Song, X. Michael and Mark E. Parry, 1997. A Cross-National Comparative Study of New Product Development Processes: Japan and the United States, Journal of Marketing, 61, 2, pp.1-18.
21. Souder, William E., and Michael X. Song, 1997. Contingent Product Design and Marketing Strategies Influencing New Product Success and Failure in U.S. and Japanese Electronics Firms, Journal of Product Innovation Management, 14, 1, pp.21-34.
22. Stone, R. B., K. L. Wood and R. H. Crawford, 2000. Using Quantitative Functional Models to Develop Product Architecture, Design Study, 21, pp.239-260.
23. Teece, D. J., Pisano, G. & Amy, S., 1997. Dynamic Capability and Strategic Management, Strategic Management Journal, 18, 7, pp.509-533.
24. Tushman, M. L. and Anderson, P., 1986. Technological Discontinuities and Organizational Environments. Administrative Science Quarterly, 31 (3), PP.439-465.
1. 2006
http://www.itis.org.tw/rptDetail.screen?rptidno=A7CDBC1D3C2469464825715300376FF7
2.
http://www.teema.org.tw/introduce/default.asp
3.
http://www.ttvma.org.tw/cht/index.php
4. 2006
http://twbusiness.nat.gov.tw/asp/superior8.asp
http://www.itis.org.tw/rptDetail.screen?rptidno=A7CDBC1D3C2469464825715300376FF7http://www.itis.org.tw/rptDetail.screen?rptidno=A7CDBC1D3C2469464825715300376FF7http://www.teema.org.tw/introduce/default.asphttp://twbusiness.nat.gov.tw/asp/superior8.asp83
5. 2007
http://www.digitimes.com.tw/
6. 2007
http://www.itis.org.tw/index.jsp
http://www.digitimes.com.tw/http://www.itis.org.tw/index.jsp84
1. 2. 3.
E-mail Address
================================================================== 1. ()A
B1~B3C1~C9// 2. AHP
9:1 7:1 5:1 3:1 1:1 1:3 1:5 1:7 1:9
B A C
1. A 2. B 3. C
85
86
() 1. 2.
9:1 7:1 5:1 3:1 1:1 1:3 1:5 1:7 1:9
() 1. 2. 3. 4.
9:1 7:1 5:1 3:1 1:1 1:3 1:5 1:7 1:9
() 1. 2..3 4.
87
9:1 7:1 5:1 3:1 1:1 1:3 1:5 1:7 1:9
() 1. 2. 3.
9:1 7:1 5:1 3:1 1:1 1:3 1:5 1:7 1:9
() 1.2.3.
9:1 7:1 5:1 3:1 1:1 1:3 1:5 1:7 1:9
() 1.
88
2.3.
9:1 7:1 5:1 3:1 1:1 1:3 1:5 1:7 1:9
() 1.
2.3.
9:1 7:1 5:1 3:1 1:1 1:3 1:5 1:7 1:9
() 1.2.
3.
9:1 7:1 5:1 3:1 1:1 1:3 1:5 1:7 1:9
89
() 1.2.3.
9:1 7:1 5:1 3:1 1:1 1:3 1:5 1:7 1:9
() 1.2.
3.
9:1 7:1 5:1 3:1 1:1 1:3 1:5 1:7 1:9
() 1.2.
3.
9:1 7:1 5:1 3:1 1:1 1:3 1:5 1:7 1:9
90
1.
2. 20~29 30~39 40~49 50~59 60
3.
_______
4.
_______
5. /
/ID /
_______
6. / /
/ /
_______
E-mail Address
___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
--------
Jia-Hau Ke
70.10.25
95 9 ~98 1
89 9 ~94 6
:
2007/6/8
2007/6/8 AHP Fuzzy QFD 2352007
Graduate Student: Jia-Hau Ke