PhD oral final examination presentations

製品開発の構想段階における
意思決定法

Md. Mamunur Rashid

北見工業大学院
博士後期課程
生産基盤工学専攻
平成 25 年 2 月 8 日

© Md. Mamunur Rashid, Kitami Institute of Technology, 2013 1

Title of the Doctoral Thesis:
Decisionmaking in Conceptual Phase of Product
Development

Md. Mamunur Rashid

Manufacturing Engineering Graduate Program
Graduate School of Kitami Institute of Technology
February 08, 2013

Personal Details
Name Md. Mamunur Rashid
Date of Birth 1 November,1970
Place of Birth Dinajpur, Bangladesh
Citizen Bangladesh

Management Counselor
Present Position Bangladesh Institute of Management
Dhaka, Bangladesh

Present Address:
Hokkaido, Kitami-shi, Toryo-cho 111-2-10-16


Degrees Obtained
November 1993
Bachelor of Science in Mechanical Engineering
Bangladesh Institute of Technology
Rajshahi, Bangladesh

December 1996
Master of Science in Mechanical Engineering
Bangladesh University of Engineering and Technology
Dhaka, Bangladesh


Work Experiences
Period
from up to Post Organization Place
Assistant
Jamuna Fertilizer
May-1997 Feb-2004 Mechanical Bangladesh
Company
Engineer
Bangladesh
Management
Feb-2004 Present Institute of Bangladesh
Counselor
Management


Publications of the Doctor’s Work

Technical Papers in Refereed Journals:
•Md. Mamunur Rashid, A.M.M. Sharif Ullah, Junichi Tamaki,
and Akihiko Kubo. (2011). Evaluation of Hard Materials using
Eco-Attribute, Advanced Materials Research, Volume 325, Pages
693-698 [ Trans Tech Publications, Switzerland]
[http://dx.doi.org/10.4028/www.scientific.net/AMR.325.693].

•A.M.M. Sharif Ullah, Md. Mamunur Rashid and Junichi Tamaki.
(2012). On Some Unique Features of C-K Theory of Design,
CIRP Journal of Manufacturing Science and Technology, Volume
5 Number 1, Pages 55-66. [Elsevier, The Netherlands]
[http://dx.doi.org/10.1016/j.cirpj.2011.09.001].


Publications of the Doctor’s Work
Full-length Paper in International Conference
•Md. Mamunur Rashid, A.M.M. Sharif Ullah, M.A. Rashid Sarker,
Junichi Tamaki, and Akihiko Kubo. (2012). Logical Aggregation of
Customer Needs Assessment, Proceedings of the Fifth International
Symposium on Computational Intelligence and Industrial
Applications, Sapporo, Japan, August 20-26, 2012.

Paper in National Conference:
•Md. Mamunur Rashid, Junichi Tamaki, A. M.M. Sharif Ullah and
Akihiko Kubo. (2010). A Virtual Customer Needs System for Product
Development, Proceedings of the 2010 Annual Meeting of Japan
Society for Precision Engineering, Sapporo, Hokkaido Branch,
Japan, September 04, 2010, Pages 53-54.

Decisionmaking in Conceptual Phase of Product Development

Agenda:
1.General Background
2.Customer Needs Assessment
3.Sustainability Assessment
4.Creativity Assessment
5.Discussion and Concluding Remarks



General Background



What is Product Development?

Product Development is the study of
activities of a product life-cycle in a
concurrent manner.



External Customers Internal Customers
(Real Customers) (Product Development Team)

Creativity
Customer needs Conceptual Phase
(Key Solutions)

Use
(Satisfaction) Detailed Design

Materialization
Primary Materials
Manufacturing
Production

Disposal Sustainability
(Recycle, Downcycle, Landfill)


(Recall the Previous Slide Figure)
Issues of the Study: External Customers
(Real Customers)
Internal Customers
(Product Development Team)

How to differentiate a Customer needs Conceptual Phase
Creativity

creative key solution from (Key Solutions)

a non-creative key Use

Materialization
solution? Primary Materials

How to deal with the
Manufacturing
Production

sustainability assessment in Disposal
Sustainability

key solution determination
process?
What is the appropriate customer need model?
How to deal with the unknown customer needs?
How to classify the key solutions based on customer
responses?


Decisionmaking in General:

1. Rational Decision Making
(utility based decision making approaches)

2. Naturalistic Decision Making (traditional setting
of game theory)


Two-dimensional Decision Measure
1
Solution 2

0.75
Solution 1
The Degree of
0.5
Fulfillment E
R
e

f
0.25
g h

0
0 0.25 0.5 0.75 1
CE
The degree of Certainty of
Knowledge


Customer Needs Assessment


(Recall Slide No.11)

What is the appropriate External Customers
(Real Customers)
Internal Customers
(Product Development Team)
customer need model?
Creativity
How to deal with the (Key Solutions)

unknown customer needs?
Use

How to classify the key Materialization
solutions based on Manufacturing
Primary Materials
Production
customer responses?
… Disposal Sustainability


Roadmap of Customer Needs Assessment
Step 1: Collection of customer needs Step 8: Making final decision
data using Kano model

Step 7: Determination of coherency
Step 2: Selection of reliable answers measures of product feature status

Step 3: Monte Carlo simulation of Step 6: Determination of information
unknown answers content of product feature status

Step 4: Determination of truth value of Step 5: Determination of truth value of
product feature Kano evaluation product feature status



Step 1: Customer Needs Data Collection



Dhaka
Bangladesh


100 respondents from different section of the society. Some Sample
feature of 38 parameter of small passenger vehicles, as follows:
No Feature
1 I bought a new vehicle
2 I bought a pre-owned vehicle
… …
21 My vehicle is a Sedan type vehicle
22 My vehicle is a SUV type vehicle
23 My vehicle is a Van (microbus) type vehicle
… …
30 My vehicle is made in Japan
… …
38 My vehicles runs on Petrol

Step 1: Questionnaires according to Kano Model (Example)

Functional answer Dysfunctional answer

Like 　 Like 　

Must-be ☑ Must-be 　

My car is Sedan Neutral 　 My car is not Neutral ☑
Sedan
Live-with 　 Live-with 　

Dislike 　 Dislike 　


Step 1: Kano Evaluation
Dysfunctional answer
Live-
Like Must-be Neutral Dislike
with
Like Q A A A O

Must-be R I I I M
Functional
Neutral R I I I M
answer
Live-with R I I I M

Dislike R R R R Q
Attractive (A), Indifferent (I), Must-be (M), One-dimensional(O), Questionable
(Q), or Reverse (R).

Step1: Meaning of Kano Evaluation


Step1: Kano Evaluation

Kano evaluation
Vehicle Type
A O M I R Q

SUV 14 10 17 41 16 2

Sedan 20 10 12 37 17 4

Van 15 8 11 21 43 2



Step 2: Selection of Reliable Answers


Step 2: Functional Answer ( According to Kano Model)

Functional Answer
Question
Like Must-be Neutral Live-with Dislike

My car is SUV 26 19 34 9 12

My car is Sedan 31 16 30 8 15

My car is Van 24 7 17 11 41


Step 2: Dysfunctional Answer (According to Kano Model)

Dysfunctional Answer
Question
Like Must-be Neutral Live-with Dislike

My car is not SUV 11 9 37 16 27

My car is not Sedan 11 9 31 24 25

My car is not Van 26 12 31 11 20


Step 2: Kano Evaluation based on the Answers of Acceptable
Respondents

Kano evaluation
Number of acceptable
Vehicle Type
A O M I R Q respondents

SUV 6 10 9 9 9 2 45

Sedan 10 10 6 8 15 4 53

Van 6 8 6 5 34 2 61



Step 3: Monte Carlo Simulation of
Unknown Answer



Step 3: Monte Carlo Simulation for Case 1 for
SUV
Case 1
Feature ev(i) fr(i)
LL(i) E(i) Pr(i) CPr(i)
A 0.133 qu 0.1 0.750 0.079
O 0.222 su 0.267 2.003 0.289
M 0.200 su 0.267 2.003 0.500
SUV
I 0.200 su 0.267 2.003 0.711
R 0.200 su 0.267 2.003 0.921
Q 0.044 qu 0.1 0.750 1.000


Linguistic Likelihood (Imprecise Probability) (LL): Case-1

1
mu
mu pu pu ns
ns pl
pl ml
ml
)
,

0.75
D
B
o

0.5
µ A

0.25

0
0 0.2 0.4 0.6 0.8 1
D
B
o
g
e
(
f
r
i
l

Relative Frequency, fr

mu- most unlikely; pu- perhaps unlikely; ns- not sure
pl-perhaps likely; ml-most likely

mu ququ
mu su su ns
ns slsl ql
ql ml
ml
1
)
,

0.75
D
B
o

0.5
µ A

0.25

0
D
B
o
g
e

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
(
f
r
i
l

mu- most unlikely; qu- quite unlikely; su-some unlikely;
ns- not sure; sl-some likely; ql-quite likely; ml-most likely

eu mu qu su ns sl ql ml el
1

0.75
µ ( .) ( x )

0.5

0.25

0
0 0.125 0.25 0.375 0.5 0.625 0.75 0.875 1
eu-extremely unlikely; mu- most unlikely; qu- quite unlikely; su-some unlikely;
ns- not sure; sl-some likely; ql-quite likely; ml-most likely; el-extremely likely

Summary of Linguistic Likelihoods (LLs) : Expected Value

Linguistic Likelihoods (LLs)
Cases
eu mu qu su ns sl gl ml el
1 - - 0.1 0.267 0.5 0.733 0.9 - -
2 - 0.033 0.133 0.3 0.5 0.7 0.867 0.967 -
3 0.042 0.125 0.25 0.375 0.5 0.625 0.75 0.875 0.958


Summary of Linguistic Likelihoods (LLs) : Alpha-cut at α=0.5
For determine the Range of fr

Linguistic Likelihoods (LLs)
Cases
eu mu qu su ns sl gl ml el
[0.15,0.4
1 - - [0,0.15]
]
[0.4,0.6] [0.6,0.85] [0.85,1] - -
[0.05, [0.8,0.9
2 - [0,0.05]
0.2]
[0.2,0.4] [0.4,0.6] [0.6,0.8]
5]
[0.95,1] -

[0,0.0 [0.0625, [0.1875, [0.3125, [0.4375, [0.5625, [0.6875, [0.8125, [0.937
3 625] 0.1875] 0.3125] 0.4375] 0.5625] 0.6875] 0.8125] 0.9375] 5, 1]



Step 4: Determination of Truth Values of
Product Feature Kano Evaluation


Step 4:Determination of Truth Values of Product Feature
Kano Evaluation
mf qf pf ns pt qt mt
)V
(T
µ (
)
.

fr(Xj)

TV
TV


Linguistic Truth-Value (TVs)

Linguistic TVs
Items
mf qf pf ns pt qt mt

Five 0.1 - 0.267 0.5 0.733 - 0.9
Expected
Value
Seven 0.033 0.133 0.3 0.3 0.7 0.867 0.967



Step 5: Determination of Truth Values of
Product Feature Status


Step 5: Determination of Truth Value of Product Feature
Status
Case 1
Kano
A O M I R Q Remarks
evaluation
After
fr 0.11 0.2 0.23 0.2 0.17 0.09
simulation
TV 0.133 0.3 0.3 0.3 0.133 0.133
must be should be could be
Status
included included included
TV 0.3 0.133 0.867

40
© Md. Mamunur Rashid, Kitami Institute of Technology, 2013

Step 5: Determination of Truth Value of Product Feature
Status
Fi must be included → ( Fi is O ) ∨ ( Fi is M )
TV ( Fi must be included ) = max ( TV ( Fi, O ) , TV ( Fi, M ) )
Fi should be included → Fi is A
TV ( Fi should be included ) = TV ( Fi, A)

Fi could be included → ( Fi is I ) ∨ ( Fi is ¬ R ) ∨ ( Fi is ¬ Q )
TV ( Fi could be included ) = max ( TV ( Fi, I ) ,1 − TV ( Fi, R ) ,1 − TV ( Fi, Q ) )



Step 6: Determination of Information
Content of Product Feature Status


Step 6: Determination of Information Content

Case 1

Status must be included should be included could be included

TV 0.3 0.133 0.867
Ic 0.6 0.266 0.266
CE 0.377
PR The feature is a must be included feature
RE 0.722

43

Decisionmaking using Two-dimensional Information Content
1
Solution 2
(Recall
Slide
0.75
Solution 1 No.14)

0.5
e
E
R

f
0.25
g h

0
0 0.25 0.5 0.75 1
CE

Epistemic Information Content
1 n

∑ I ( TV ( Pi ) )
c
0.75 CE = i
n
I ｃT ()
(V .

0.5

0.25

0
0 0.25 0.5 0.75 1
TV(.)

  TV − 0 1 − TV  
I c ( TV ( Pi ) ) = max 0, min
 , 
  0.5 − 0 1 − 0.5  



Determine Requirement Entropy (RE)
1

0.75

0.5
E
R

0.25

0
0 0.25 0.5 0.75 1
TV(PR)
  a − TV ( PR )  
RE = max 0, min1,
 
  a − b  
a = max( TV ( Pi ) | i = 1,, n ) b = min ( TV ( Pi ) | i = 1,, n )

Information Content For Systems Design
0.15

1
I ( FR ) = −log 
0.1
S S
)
)

sr
R
F
R
F
P
(
r
P
(
r

0.05
dr

0
15 20 25 FR 30 35 40
FR
47


Step 7: Determination of Coherency
Measures of Product Feature Status


Step 7: Variability in the Information Content of SUV
1.0

0.8

must be included
0.6
should be included
E
R

0.4
could be included
0.2

0.0
0.0 0.2 0.4 0.6 0.8 1.0
CE

Step 7: Variability in the Information Content of Sedan
1.0

0.8

must be included
0.6
should be included
R
E

0.4
could be included
0.2

0.0
0.0 0.2 0.4 0.6 0.8 1.0
CE


Step 7: Variability in the Information Content of Van
1.0

0.8

must be included
0.6
should be included
E
R

0.4
could be included
0.2

0.0
0.0 0.2 0.4 0.6 0.8 1.0
CE


Step 7: Coherency Measures (λ) of Product Feature

Status
Features must be should be could be
included included included

SUV 2.314 2.577 0.577
Sedan 2.578 2.578 0.755
Van 2.332 2.332 0.577



Step 8: Making Final Decision


1.0
Reduction in overall
0.8 information content for
could be included.
0.6
λ

0.4

0.2

0.0
Sedan SUV Van
Features
Injecting more and more SUV and Van into the market could
increase the level of satisfaction of car users in Bangladesh.

3.0
information content for should
2.5
be included.
2.0

1.5
λ

1.0

0.5

0.0
Sedan SUV Van
Features

SUV and Van are not that much unexpected surprises
to the car users in Bangladesh.

3.0

2.5
information content for
2.0
must be included.
1.5
λ

1.0

0.5

0.0
Sedan SUV Van
Features

SUV and Van must increase the level of satisfaction of car
users in Bangladesh but this conclusion possesses a great
deal of uncertainty.


Sustainability Assessment



External Customers Internal Customers How to deal
with the
Creativity sustainability
Customer needs Conceptual Phase assessment in
(Key Solutions)
key solution
Use
determination
(Satisfaction) Detailed Design process?

Primary Materials
Manufacturing
Production



Imprecision in Eco-attributes: CO2 footprint and Water Usage


Imprecision in Eco-attributes: NOx Vs SOx


Membership Functions :
When S=CO2 , footprint and xS=15
1
VLS LS MS HS VHS
0.75

0.5

0.25

0
0 3 6 9 12 15


Universe of Discourse (xs) for Two Cases

xs
Case CO2 Water NOX SOX
footprint usage emission emission

1 15 300 80 120

2 12 280 70 110


Decision Space for Sustainability Assessment

Less
sustainable
material
U I S( G )

Highly
sustainable
material

0
0 DIS(G)


Range Compliance of Numerical Range with respect to a
Fuzzy Number (R(L,A))

∫µ A ( x ) dx
R ( L, A ) = L
L′

L′

R( L = [10,30], A = Comfortable ) = 0.583

Evaluation of Alumina (AN)


Evaluation of Silicon Carbide(SC)


Evaluation of Boron Nitride (BN)


Evaluation of Boron Carbide (BC)


Evaluation of Zirconia (ZN)


Sustainability Assessment of Selected Hard
Materials for Abrasive Grains of Grinding Wheel
Categories Materials

Highly sustainable
Alumina based hard materials
materials

Moderately sustainable Zirconia/Silicon Carbide based hard
materials materials

Boron Nitride/Carbide based hard
Less sustainable material
materials



Creativity Assessment



External Customers Internal Customers
How to
Creativity
differentiate a
(Key Solutions) creative key
solution from
Use
(Satisfaction) Detailed Design a non-creative
Materialization key solution?
Primary Materials
Manufacturing
Production



C-K theory


State of Ordinary Concept (C1):
(Hydrocarbon+ O2 CO2 + Energy)

Linguistic Numerical Requirement
Propositions (PR) TV
TV TV
C1 is suitable for mostly
P11: 0.1 C1 should be
the perceived need false (mf)
suitable for
C1 is not suitable 0.1
perhaps perceived
P12: for the perceived 0.733 need
true (pt)
need
mostly
P13: C1 performs well 0.9
true (mt) C1 should
0.9
C1 does not mostly perform well
P14: 0.1
perform well false (mf)


Information Content of C1 (Existing/non Creative Engine):
(Hydrocarbon+ O2 CO2 + Energy)

Compelling
reason
(suitableness)

Epistemic
challenge
(performance)


State of creative concept (C2) :
(Magnesium+ CO2 O2 + Energy)

Linguistic Numerical Requirement
Propositions (PR) TV
TV TV
C2 is suitable for
perhaps
P21: the perceived 0.733 C2 should be
true (pt)
need suitable for
0.733
C2 is not suitable perceived
perhaps need
P22: for the perceived 0.267
false (pf)
need
not sure
P23: C2 performs well 0.5
(ns) C2 should
0.5
C2 does not not sure perform well
P24: 0.5
perform well (ns)

Information Content of C2 (Creative Engine)
(Magnesium+ CO2 O2 + Energy)
Epistemic
challenge
(performance)

Compelling
reason
(suitableness)


The States of a Creative Concept
Lack of knowledge Rejection of concept
adopted

Motivation

Concept
conceived
Continuation of concept
λ adopted
Gain of knowledge

Concept adopted

Pursing a creative concept


Discussion and Concluding Remarks


Customer Needs Assessment
One of the ways to identify a key solution to develop a
product is to take opinions of customers regarding a set of
key solutions.
To deal with the intrinsic complexity of customer
responses, logical aggregation of customer opinions is a
better choice compared to frequency based analysis.
It has been found that a product feature needs to be
classified either into a must be included feature, or into a
should be included feature, and or into a could be included
feature. The link among these classifiers and Kano
evaluations has been established.

Customer Needs Assessment (Cont’d)
The multi-valued logic plays an important role in the
customer needs assessment. In particular, a two-
dimensional information content (in epistemic sense)
scheme has been found effective in logically computing
the degree of customer satisfaction of a given product
feature in terms of must be included, should be included,
and could be included.
To increase the degree of satisfaction of vehicle users in
Bangladesh, it is important to develop SUV- and Van-
type passenger vehicles replacing some of the Sedan-type
vehicles.

Sustainability Assessment
Sustainability of a product largely depends on the
materials used to manufacturing it. Therefore, the
material used to manufacture the product become one of
the key solutions.
To deal with the imprecision associated with the
material related sustainability parameters in the
conceptual phase of product development, an entity
called range compliance has been found effective. The
compliance of an sustainability parameter given by a
numerical range is determined by calculating its
compliance with five fuzzy numbers of the parameters
labeled very low, low, moderate, high, and very high.
82

Sustainability Assessment (Cont’d)
As an example, the imprecision associated with four
sustainability parameters namely, CO2 footprint, NOX
emission, SOX emission and water usage (i.e., resource
depletion) of five classes of hard materials (the materials
used to produce abrasive grains of grinding wheel or
other material removal tools) based on Alumina,
Zirconia, Silicon Carbide, Boron Nitride, and Boron
Carbide have been quantified by using the range
compliance.

83


Sustainability Assessment (Cont’d)
The sustainability parameter complying more with very
low or low less negative impact on the sustainability,
whereas the sustainability parameter complying more
with moderate, high, or very high has high negative
impact on sustainability.
It is found that Alumina based hard materials have low
negative impact followed by Zirconia and Silicon
Carbide based hard materials. Boron Nitride/Carbide
based materials have the highest negative impact.

84

Creativity Assessment
To identify a useful key solution in conceptual phase of
product development, the product development team
members needs to be creative.

To differentiate a creative concept from a non-creative
concept, Concept-Knowledge mapping as prescribed in
C-K theory can be employed.

Creative concept means a concept which is undecided
when it is being conceived.
Conceiving a creative concept is rather a motivation
driven process.

Creativity Assessment (Cont’d)
Information content of a creative concept is high
compared to that of a non-creative concept. The
information content means here the two-dimensional
information content in epistemic sense.
When a creative concept is pursued and new knowledge
becomes available, the information content should go
down significantly. Otherwise, the new knowledge does
not add any value to product development process.
A non-creative key solution does not exhibit the
abovementioned behavior of information content.


Creativity Assessment (Cont’d)
The effectiveness of the abovementioned approach has
been demonstrated by calculating the information contents
of two concepts Mg-CO2 based propulsion engine (a
creative concept) and fossil-fuel base propulsion engine
(an non-creative concept). It has been found that the Mg-
CO2 based propulsion engine exhibits high information
content compared to that of fossil-fuel base propulsion
engine for Mars exploration. The information content of
Mg-CO2 based propulsion engine have gone down
significantly under the presence of new knowledge.



Thanks for your attentions !


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