why we need matrices in qfd · when qfd was born, the house of quality (hoq), as a tool was an...

17th

International QFD Symposium, ISQFD 2011 - Stuttgart

1

© 2011 QFD Institut Deutschland e.V. © Thiess, Streckfuß, Jahn

Why we need matrices in QFD

Monika Thiess

Gaggenau Industrie S.A.S.

Lipsheim/Strassbourg

Gerd Streckfuß

Institut für Qualitätsmanagement

Dr. F.Weigang und Partner (IQM)

Dr.Walter Jahn (†)

SPQ

Leipzig

ABSTRACT

In this paper, we describe the need of using special matrices in QFD to achieve sustainability. These matrices inside of the

House of Quality (HoQ) were always criticized regarding the time consuming effort and the minimum of benefit in regard of

the results. But in the last decade, there is a revival of the QFD matrices. This paper will present the specific reasons for this

future trend and the prerequisites to handle the matrices inside QFD and discuss the results of several, selected projects.

KEYWORDS

QFD, House of Quality, Special Matrices, Optimization Direction, Conflicts and Contradictions, QFD and TRIZ, Mahalanobis-

Distance

1. INTRODUCTION When QFD was born, the House of Quality (HoQ), as a tool was an important integral part of using QFD. The HoQ was

derived from the “fish-bone” diagram, which was one of the most important “new 7 tools” to identify all potential factors

causing one effect. 1

Sometimes, the meaning of QFD was identical to the HoQ and reverse.

The negative impacts in using the House of Quality were discussed ever since it was published in the QFD Literature (Mazur

et.al). 2

Main items refer to:

The enormous time needed to handle large matrices

Wrong input in regard to Customer Requirements gives wrong output:

Garbage in = expensive garbage out

The results as outcome of the calculations with the relationship-figures were nontransparent, sometimes obscure.

The results did not get any acceptance in the R&D Departments. Engineering was more interested in getting valid

Customer Requirements (if there was already a customer orientation) and no technical solutions “produced by QFD”.

But talking to practiced customers, who are using QFD since more than a decade and our own experience, there is now a

revival in using Matrices and in the calculation of the results. New needs and requirements in a global development world are

reasons for this approach.

2. The Impact of using matrices.

2.1 Time consuming? Using QFD for a product with 5 Customer Requirements (CR) and 5 Technical Requirements (CTQ) gives a feasible Matrix

5 x 5 = 25. But there is no need to use QFD for this simple product.

17th


2


E.g. in areas of high-end home appliances or medical healthcare equipments, these products have several hundred of

requirements and technical features. It is, of course, impossible to handle these large matrices. It was the impact of the Kano-

Chart, which allows an effective filter, to reduce the number of requirements, and in connection the number of CTQ’s. The

filter is very simple and easy to use:

Only these Requirements are listed for QFD:

They are: They are not:

1. New and 1. Already implemented

2. Important for Customers and 2. Basic requirements

3. Difficult for R&D 3. R&D says: “Easy…”

In most cases, it reduces the number of items between 30 to 80.

This gives still large matrices and would likely kill the QFD session. The solution is in separating the global group into “sub-

groups” of 3 people, each of the subgroup is handling a part of the matrix. Only the outcome will be discussed at the end

within the total group. (“Reading the Matrix, Sanity check”). E.g. given 50 CR and 25 CTQ’s and the total group of 15 People,

gives 250 relationship numbers for one subgroup.

The main reasons for extensive discussions in this timeframe are caused by the unanswered meanings and understandings

regarding customer requirements, which was skipped at the beginning of the QFD. And remember: It takes us 3 to 5 years to

develop these products, we should be able to find 2 – 4 days in this period….

2.2 The “positive” and “negative” relationships

In the past, we asked only, if there is any

relationship between a specific customer

Requirement and a Technical Feature. If yes, we

tried to rate, how much, with values 9, 3, 1.

The value of this information for the R&D was

too simply, because it was not a new expert

knowledge.

Adding the figures or calculating the product of a

matrix by a scalar was an misleading result.

The new approach (which was not a total new

one) was the appearance of TQM (Total Quality

Management) with the request, to add the

Improvement Direction (or: Optimization

direction)

Figure 1: Simplified relations

17th


3


Figure 2: Relations with optimization direction

There are now three questions to evaluate the relationship values:

1. Are there any relationship between a specific customer Requirement and a Technical Feature?

2. If yes, how much (1,3,9)?

3. If we improve the technical requirement because of customer request:

a. Will it be a benefit for the customer (positive)?

b. Or will it be a conflict in the view of the customer (negative)?

Remark: The summary of the technical Feature (e.g. scalar product, Tensor) must be separated in a positive and negative

result. To combine both together (e.g. positive = 50, negative = -50, Result = 0) is useless and misleading.

2.3 The correlation-Matrix (“Roof of the House of Quality”)

Technical features are always more or less strong correlated among one another. The analysis gives two interesting results:

1. This one Technical feature has influence to all other Technical Features; measured by the correlation matrix.

2. All technical Features together have influence to this one Technical Feature; measured by the multiple correlation

coefficients

It is obvious, the optimization direction has an important influence within the correlation matrix.

Considering the optimization direction together in the relation-matrix and the correlation-matrix, it gives a total new picture

and is difficult to evaluate. But it answers the question: what happens, if we improve a product in the view of the customers’

requests.

17th


4


Figure 3: House of Quality with optimization direction

2.4 The House of Quality with optimization direction To solve the negative influences is not an easy task:

To leave just one strong negative relation, this could become a “killing item”, which prevents the customer to buy or

to recommend the whole product.

To change the optimization direction only moves the conflict from one relation to the other(s)

To compromise is always a way out to prevent new solutions.

To skip the Customer Requirement, which “causes” the conflict, means, we just “skip” the customer. Nevertheless, it

is one of the most misappropriated solutions. (Motto: The customer is always the central point in our business, that

the reason, why he always stands in our way….)

In all the QFD Sessions, we run in the last years, there was none one without negative relations in the matrix. Changing

Parameters have always a positive and negative impact. This is also valid for changing parameters in the direction of

improvement.

In the meantime, R&D (not the Marketing or Sales teams) is looking more than ever to find these conflicts from the very first as

to look after the positive numbers. But these dependencies could only be detected, analyzed and justified by using a matrix. A

single, linear deployment of just one Customer Requirement will not ensure the faultfinding’s.

17th


5


2.5 Detecting “Killing Items” We all know the exemplary cases, where single faults cause extreme cost and reputation. E.g. the product recalls in the

automotive industry. In practice, there are few negative relations, especially if only enhancements of a product are requested.

But it needs the QFD-House of Quality to detect these single ”killing items”, showcased in the picture below.

Case 1: It is apparently a negative relationship; the increase of speed of the shutter will cause an increasing noise. In practice,

very often these basic contradictions are overseen. But to know these contradictions at the beginning of the product

development is essential, because in most cases technical solutions could be found at this stage.

Case 2: More difficult are hidden contradictions. The Customer requires the turn down of the shutter, not only if a bright

sunshine is detected, also if a high temperature is measured. But in this case, also a fire inside of a house will close the shutter

and prevent the fire fighters to enter the rooms. This single feature - “killing item” -would definitely produce a recall or stop the

sales.

Also in products, which are well known in all aspects of development, simple changes causes contradictions, even though the

quantity is in general not high. Also Teams, adept very well in QFD, need the QFD Matrices to detect them. It is the human

behavior, that you will get after the detection of killing items comments like: “….if anybody has asked me before…”

(C)

G. S

TR

EC

KF

US

S 1

.99

V

97/9

8 (

1)

Ku

nd

en

seg

me

nt:

Ku

nd

en

stim

me

/-n

utz

en

(M

asl

ow

):

QFD

House of Quality I

V4.0

Mitb

ew

erb

B

1

- 5

All

g.

Ge

wic

htu

ng

1-1

0

He

uti

ge

r S

tatu

s

1 -

5

Mitb

ew

erb

A

1

- 5

Mitb

ew

erb

C

1

- 5

an

ge

stre

bte

r S

tatu

s 1

-5

Ve

rbe

sse

run

gsf

akt

or

F/B

Ve

rk.a

rgu

me

nt

1,

1.2

, 1

.5

Ge

wic

htu

ng

A*G

*H

Re

l. G

ew

ich

t (%

)

RE

L.G

EW

ICH

T (

%)

PA

RE

TO

Qu

ali

tity

Fe

atu

re

Pro

gra

mm

ieru

ng

s-m

ög

lic

hk

eit

en

+

da

ue

rha

fte

Sp

eic

he

run

g +

He

llig

ke

it +

/-

un

ive

rse

ll e

ins

etz

ba

r +

ze

itu

na

bh

än

gig

+

Ra

um

tem

era

tur

-

Fe

rtig

un

gs

teil

e -

Um

we

ltfr

eu

nd

lic

h +

Gu

rtw

ick

lerk

ap

az

itä

t +

Ze

it -

Grö

ße

-

We

rks

toff

+

Mo

tork

raft

+

leic

hte

Be

die

nu

ng

+

Bra

nd

sc

hu

tz +

Ge

wic

ht

-

Sp

an

nu

ng

-

Au

fla

de

ze

it -

Sp

eic

he

rka

pa

zit

ät

+

Ge

räu

sc

h -

Re

cy

cli

ng

+

Wa

rtu

ng

-

Le

istu

ng

+

se

lbs

terk

läre

nd

+

Ha

ltb

ark

eit

+

Fo

rm +

Kin

de

rsc

hu

tz +

Ein

kle

mm

sc

hu

tz +

Re

inig

un

gs

ze

it -

Ob

erf

läc

he

+

Re

ibu

ng

-

un

ge

wo

llte

Be

die

nu

ng

-

Wa

ss

erd

ich

t +

Zu

gä

ng

lic

hk

eit

+

Dre

hm

om

en

t +

Au

ss

pe

rre

n -

6 K1 K2 A B C D E F G H I J K + + +/- + + - - + + - - + + + + - - - + - + - + + + + + + - + - - + + + - # 40

7 G undbedürf nissProj.: symp11 167 139 133 115 115 110 86 75 73 71 70 65 63 62 59 59 56 55 55 54 53 53 50 42 39 38 32 30 22 16 11 6 3 3 0 0

8 S icherheitKunde: Benutzer 100,00 8 7 6 6 6 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 1 1 1 1 0 0 0 0 0

9 K KommunikationGruppe: -129 104 52 54 87 58 50 59 41 43 53 40 50 47 67 29 34 26 26 33 3 29 40 37 41 30 17 22 21 10 5 10 11 1 2 0 17 0 0 0 ENDE

10 P restigeModerator: 0 5 3 3 4 3 2 3 2 2 3 2 2 2 3 1 2 1 1 2 0 1 2 2 2 1 1 1 1 0 0 0 1 0 0 0 1 0 0 0

11 SW elbsverwirklichungDatum: nur heute schwacher Erfüllungsgrad 104 52 54 87 58 50 59 41 43 53 40 50 47 78 118 34 26 26 33 32 29 40 37 41 30 17 22 21 10 5 10 11 1 2 0 17 0 0 0

12 R eklamationVersion 1 0 0 0 0 0 0 0 0 0 0 0 0 0 -11 -89 0 0 0 0 -29 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

13

14

15 Mittelwerte: 2 6,9 # # # # 1,7 1,1 13,9 2,9 3

16 Nr. Customer needs M.C.GewHeuM.BM.RM.S Pla 303,5 62 100 einzelne 9, d.h. nur dieses Q-Merkmal als Einfluss-Faktor.Schwache Reihen=keine Q-Merkmale?schache, siguläre Spaltn=schwache Q-Merkmale aus Kundensicht (Kosten!)

171

tro tz Stromaus fa l l funk tions tüc htig

1 10 1 4 1 5 5,0 1,5 75,0 15,4 106 1 9 3 9 3 3 1 28

18 2 bei Däm m erung früher / s päter abs enk en / ö ffnen

1 8 1 3 2 5 5,0 1,5 60,0 12,3 119 2 3 9 3 1 16

19 3 bei hoher Innentem peratur Abs enk ung des Rol l ladens

1 8 1 1 1 5 5,0 1,2 48,0 9,9 131 3 3 3 9 -9 6

20 4 k le ine Abm aße

2 8 2 1 1 7 3,5 1,0 28,0 5,8 141 4 9 1 9 9 3 9 9 3 3 55

21 5 m ehrere Program m ierungs m ögl ic hk ei ten

2 5 1 3 3 3 3,0 1,2 18,0 3,7 146 5 9 3 9 -3 9 27

22 6 s ol l gewic hts unabhängig, bes tändig und g le ic hm äßig funk tion ieren

3 8 2 3 3 4 2,0 1,0 16,0 3,3 150 6 9 1 9 1 3 3 26

23 7 in k urz er Zei t Öffnen, Sc hl ießen

4 6 2 3 4 5 2,5 1,0 15,0 3,1 153 7 1 1 9 3 -9 3 8

24 8 z uv erläs s iger Betrieb

4 10 4 4 4 5 1,3 1,0 12,5 2,6 156 8 1 3 3 1 9 17

25 9 Zuv erläs s iger Kundendiens t

1 10 5 3 4 5 1,0 1,2 12,0 2,5 158 9 3 3

26 10 einfac he Ins ta l la tion

1 9 4 2 1 5 1,3 1,0 11,3 2,3 161 10 1 9 1 3 3 1 18

27 11 geringer Strom v erbrauc h

2 9 4 3 1 4 1,0 1,2 10,8 2,2 163 11 9 9 3 3 3 9 1 37

28 12 m ehrere Geräte m i t e inem Bediente i l

1 7 5 1 1 5 1,0 1,5 10,5 2,2 165 12 3 1 1 3 1 9

29 13 Gerät s o l l le is e s e in be i Betrieb

2 10 4 1 1 4 1,0 1,0 10,0 2,1 167 13 1 3 1 9 3 17

30 14 bei s tark er Sonneneins trah lung abs enk ung des Rol l ladens

1 8 4 5 3 5 1,3 1,0 10,0 2,1 169 14 3 9 3 9 24

31 15 s elbs terk lärend

3 8 4 2 3 5 1,3 1,0 10,0 2,1 171 15 1 9 9 19

32 16 einfac he Program m ierung

3 10 5 1 2 5 1,0 1,0 10,0 2,1 173 16 9 3 1 9 22

33 17 geeignet für a l le gängigen Gurtbre i ten

5 10 4 5 5 4 1,0 1,0 10,0 2,1 175 17 9 3 3 15

34 18 Wartungs arm

5 10 5 5 5 5 1,0 1,0 10,0 2,1 177 18 3 1 9 9 9 1 32

35 19 Bi l l ig in der Ans c haffung

4 8 5 1 2 5 1,0 1,2 9,6 2,0 179 19 3 9 3 15

36 20 öffnen / s c h l ießen durc h Handz ug s o l l noc h m ögl ic h s e in

1 4 2 1 1 4 2,0 1,2 9,6 2,0 181 leer! 20 0

37 21 Aus s perrs ic herung

1 6 3 5 1 4 1,3 1,2 9,6 2,0 183 21 9 9 18

38 22 orts unabhängige Bedienung, Steuerung

1 6 4 1 1 4 1,0 1,5 9,0 1,9 185 22 3 1 3 9 16

39 23 einfac he Bedienung

4 9 5 4 4 5 1,0 1,0 9,0 1,9 187 23 3 3 1 9 1 17

40 24 v ers tändl ic her Aufbau

2 9 4 2 2 4 1,0 1,0 9,0 1,9 189 24 1 1 2

41 25 Kinders ic her

1 8 4 4 1 3 0,8 1,5 9,0 1,9 190 25 3 3 9 9 3 1 28

42 26 einac heTec hnik

3 6 3 2 3 4 1,3 1,0 8,0 1,6 192 26 1 1 1 1 3 7

43 27 Gerät s o l l unabhängig v on der Gurtlänge funk tion ieren

1 8 5 1 1 3 0,6 1,5 7,2 1,5 193 27 9 9 3 21

44 28 Eink lem m s c hutz

2 8 4 4 1 3 0,8 1,2 7,2 1,5 195 28 3 9 9 21

45 29 s ol l große Gewic hte bewegen k önnen

3 6 4 3 3 4 1,0 1,0 6,0 1,2 196 29 9 1 3 9 -1 9 3 33

46 30s c höne Form 1 4 4 3 3 4 1,0 1,2 4,8 1,0 197 30 3 1 9 1 9 23

47 31 unauffä l l iges Aus s ehen

1 2 2 2 3 4 2,0 1,0 4,0 0,8 198 31 3 9 3 15

48 32 große Speic herk apaz i tä t

1 1 1 4 2 2 2,0 1,2 2,4 0,5 199 32 9 3 3 3 9 27

49 33 le ic ht z u re in igen

4 2 5 2 3 5 1,0 1,0 2,0 0,4 199 33 3 1 1 3 3 9 9 3 1 33

50 34 s ol l optis c h in d ie Wohnung pas s en

1 1 3 3 3 5 1,7 1,2 2,0 0,4 199 34 1 1 9 3 14

51 35Längere Betriebs z ei ten m ögl ic h 2 1 3 1 3 3 1,0 1,0 1,0 0,2 200 35 1 9 3 13

- 9

- 9

Fire control access (Case 2)

Low noise required (Case 1)

Actin

g o

n h

igh

tem

pe

ratu

re

(

2)

+

Sp

ee

d

(1

)

+

Open and close in minimum time (Case 1) +9

Figure 4: Single “killing items” (shutter)

17th


6


Figure 5: “Only” six contradictions in a product improvement, but likely killing the product.

To find out the various relationships between Customer Requirements and Features respectively Functions and the correlations

between the Features (Quality Features, CTQ’s) are important on new, innovated products. In an extreme situation, the result of

a QFD could lead to a stop of these developments. The following charts are demonstrating the various QFD results of an new

inventive product development, which was after the QFD sessions reappraised as too difficult to continue without making

major changes.

2.5.1 Results of a relationship matrix

Positive and negative weight Quality Features

-100

-50

0

50

100

150

200

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48

Cu

sto

me

r V

alu

e

Ka

no

Ma

slo

w

So

ft F

ac

tor

Po

ssib

le Im

pro

ve

me

nt

QFD House of

Quality A1

QF to CR

se

e d

ocu

me

nt:"N

"

Imp

ort

an

ce

10

-1

Cu

rre

nt

Sta

tus

5

- 1

Co

mp

etio

n A

5 -

1

Co

mp

etitio

n B

10

- 1

Co

nsu

me

r R

ep

ort

(te

st)

5 -

1

Pla

nn

ed

Sta

tus

5 -

1

Imp

rove

me

nt

F/B

Sa

les P

oin

ts

1,

1.2

, 1

.5

Imp

ort

an

ce

We

igh

t

A

*G*H

Re

lati

ve

Im

ort

an

ce

We

igh

t (%

)

Re

l. W

eig

ht

(%)

Pa

reto

Qu

ality

Fe

atu

res

(Q

F),

CT

Q's

Ene

rgie

verb

rauc

h ("Ste

ckdo

se")

Ene

rgie

verb

rauc

h (L

abel

ing)

Bet

riebs

gerŠ

usch

Ger

uchs

verm

eidu

ng

Nut

zvol

umen

ZugŠ

nglic

hkei

t der

Lag

erbe

reiche

vers

tellb

are

Abl

agee

bene

nO

rdnu

ngss

yste

m

Hel

ligke

it (L

euch

tkra

ft)

Lich

tfarb

e

hom

ogen

e Aus

leuc

htun

g

Lage

rtem

pera

tur

Tem

pera

turs

tabi

litŠt

tem

pera

turv

aria

bler

Lag

erbe

reich

Sch

nellk

Ÿhl

ung

klei

ner W

aren

men

gen

auto

m. A

btau

ung

Feuc

hter

egul

ieru

ng

Abw

Šrm

enut

zung

TŸrs

chlie

sshi

lfe u

nd …

ffnun

gshi

lfeM

ater

ial

Hap

tik

Opt

ik

SpŸ

lmas

chin

enfe

st

War

nsys

tem

bei

Feh

lfunk

tion/

Stš

rung

en

Eis

wŸrfe

lber

eitu

ng

Get

rŠnk

e-W

iede

rver

schl

ie§b

arke

it

(Sel

bst-) R

eini

gung

Mul

timed

ia-B

ildsc

hirm

K2 A B C D E F G H I J K 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

Project: New Optim.direction: - + - + + + + + + + + + + + + + + + + + + + + + + + - + +Company: F fix (Target) Cost:

Team: 1829 -7 27 28 50 -27 113 95 84 92 127 179 63 39 130 72,8 -22 0 8,8 177 114 91 168 49 106 3,86845 40,205 26,8 0,1426 0

100 0 1 2 3 -1 6 5 5 5 7 10 3 2 7 4 -1 0 0 10 6 5 9 3 6 0 2 1 0 0Facilitator: G.Streckfuss/IQM 21 20 17 27 6 43 49 44 32 48 61 41 24 63 46 4 0 15 69 58 43 64 25 39 25 27 33 34 0

Date: -20 -7 -7 -4 -16 -4 -4 -6 -3 -1 0 -5 -6 -1 -11 -13 0 -3 -6 0 0 0 0 -1 -23 -20 -12 -37 0

Version: 4.0 (GS) Technical Difficulties (10-1)

Spezification: HOW MUCH

5,9 2,5 1,9 2,5 2,3 3,3 1,4 1,1 9,0 2,6

V K M WF Pot. Nr.

Customer Requirements and

Needs (CR)Gew Heu M.A M.B. Test Pla 54 42,2 350,7 100 Nr

1,9 3,2 2,1 12,7 3,3 No Environment 7 3 3 1,0 1,0 7,0 2,0 2 1

5 3 1 15 3 1

My appliance is not wasting energy, I save energy 8 4 2 4 5 5 1,3 1,2 12,0 3,4 5 2 9 9 -1 -3 -1 -1 -3 9 -1 -3 -3 -1 3 1 -9 -3 -9

2 3 1 6 2 2

I own a "green cooler" / "green freezer", I protect the environment , I save energy, I can

easily sell the product, I set myself apart from the "others", I am interesting, I save money, I

got a good feeling, my appliance matches to the kitchen5 3 2 3 2 3 1,0 1,0 5,0 1,4 7 3 9 9 -1 -1 1 1 3 1 -3 -3 3 1 3 3 1 -1 -1

4 4 1 16 1 3I may use the waste heat of my appliance, I save time, I save energy, I protect the

environment, I am able to concentrate on more important things, nothing is constraining me,

I'm a gourmet4 2 2 2 1 2 1,0 1,2 4,8 1,4 8 4 1 1 1 9

0 4 Comfort 7 3 3 0,0 1,0 0,0 0,0 8 5

1 3 3 9 4 5 My appliance is silent, I am not negatively experiencing my appliance 7 3 2 3 5 4 1,3 1,0 9,3 2,7 11 6 9 -1 -1 -3 -3 -3 -1 1 -1 -1 -1

1 4 3 12 2 6My appliance sounds valuable while opening or shutting, I like my kitchen, It's fun, my

kitchen is reliable , in my kitchen everything works the same way, I can easily sell this

product6 3 2 4 1 4 1,3 1,0 8,0 2,3 13 7 1 9 1

1 4 4 16 4 7My appliance seems to be quite valuable while using, I got a good feeling, I am not

negatively experiencing my kitchen, everything is running smoothly , there are no stops in

the workflow, I got optimal ergonomics6 2 2 3 1 3 1,5 1,2 10,8 3,1 16 8 3 3 1 3 3 3 3 9 9 9 9 9 3 1 3 3 1

3 3 2 18 2 8

My appliance is abacterial, my live is convenient, I save time, cleaning activities will be

decreased , I feel good in my kitchen 1 3 3 1 5 3 1,0 1,2 1,2 0,3 17 9 3 3 9 3 -9 9

3 4 1 12 4 9

Easy to clean (Selfcleaning) 7 3 3 2 5 4 1,3 1,0 9,3 2,7 19 10 1 -1 -3 -3 -1 3 9 3 9 3 -3 -9 9 -3

1 4 4 16 10 My appliance seems to be very valuable, everything is running smoothly 6 2 3 3 1 3 1,5 1,2 10,8 3,1 22 11 3 3 1 3 3 3 3 9 9 9 9 9 9 3 3

2 5 4 40 4 11

I would like to have a "multimedia" kitchen, I don' t need to search things, everything is

running smoothly, nothing is constraining me, I may design my kitchen according to my

needs, I set myself apart from the "others", I may live in my kitchen , I may do different things

in my kitchen

5 1 1 1 1 3 3,0 1,5 22,5 6,4 29 12 -1 -1 -1 1 1 1 1 3 3 3 3 3 9

2 4 3 24 1 12I know what I need to buy, I love to be a perfect host, I save time, I am not negatively

experiencing my kitchen, I am always prepared , everything is running smoothly, I protect the

environment5 1 1 1 1 3 3,0 1,2 18,0 5,1 34 13 1 9 3 1 3 9 3 3

3 3 1 9 3 13My appliance has got enough space, space in the appliance is optimally used , my

appliance fits my requirements, I may store as much as I want, I am always prepared 7 4 2 4 5 4 1,0 1,0 7,0 2,0 36 14 -1 -1 -1 9 9 1 1 3 3 -1 -1

0 14 Cooling 6 3 3 1,0 1,0 6,0 1,7 38 15

1 1 1 1 2 15In my fridge there are various cool drinks all the time, I don' t need to search goods, I am

prepared, I save time, there are no stops in the workflow, I am a perfect host , I protect the

environment6 3 2 3 3 3 1,0 1,0 6,0 1,7 39 16 -1 1 1 3 -1 1 9 9 9 1 1 1 3 1

2 3 1 6 4 16I've got enough ice cubes any time, I am a perfect host , my love to visit me, I am always

prepared, I save time, I don't have negative experiences in my kitchen 5 2 2 2 1 3 1,5 1,0 7,5 2,1 41 17 -3 -3 -1 -1 -1 1 3 9 1 9 1

1 1 1 1 4 17It's not smelly when I open my appliance, I don' t have to expect something negative, I need

less cleaning my appliance, I cannot smell my appliance 6 2 2 2 1 3 1,5 1,0 9,0 2,6 44 18 9 -1 3 3 1 1 9

2 4 1 8 4 18I am able to store my bread for long times whithout freezing, I don't have to expect

something negative, I may optimize my shopping , nothing is constraining me, I protect the

environment7 2 1 2 1 3 1,5 1,0 10,5 3,0 47 19 -1 -1 -1 3 1 3 -3

2 3 1 6 2 19

My stored glass bottles are always cool, I am well prepared, I don't have negative

experiences, I love to be a perfect host , my friends love to visit me, I may concentrate on

more important tasks5 2 3 2 1 3 1,5 1,0 7,5 2,1 49 20 -9 -1 -1 -1 1 1 -3 3 9 3 3

4 1 1 4 3 20I may optimally cool my goods, I may optimally store my goods, I save time, I don't need to

search my goods , I'm well organized 6 4 3 4 5 4 1,0 1,0 6,0 1,7 51 21 -3 -1 -1 -1 -1 3 -1 9 9 9 9 1 9

2 3 1 6 1 21my drinks could be stored longer after opening, I am not experiencing my appliance

negatively, I may optimize my shopping 5 1 1 1 1 2 2,0 1,0 10,0 2,9 54 22 1 -1 9

0 22 Ergonomics 6 3 3 1,0 1,0 6,0 1,7 55 23

1 4 4 16 5 23I am able to easily pull out my interior elements, I like my kitchen, I am not experiencing my

appliance negatively, everything is running smoothly , there are no stops in the workflow, I

got optimal ergonomics6 4 2 4 3 4 1,0 1,2 7,2 2,1 57 24 -1 -1 9 -1 -1 3 9 -3 -1

2 4 5 40 4 24I may individually adapt my appliance, I am well prepared, I may optimize my shopping, my

goods are optimally stored, my fridge is variable 6 2 2 2 3 2 1,0 1,5 9,0 2,6 60 25 1 -1 3 9 9 1 3 9 1 1 -3

1 3 1 3 3 25It's easy to open bottles without any help, I don' t need to search things, my kitchen is tidy,

everything is running smoothly, I am not experiencing my appliance negatively, my

appliance supports me in daily live5 1 1 1 1 2 2,0 1,0 10,0 2,9 63 26 1 3 -3

2 3 1 6 4 26I may enlarge my compartments on if required, I am always prepared, my kitchen is tidy, I

may optimize my shopping, I am optimally using my appliance's space , I may buy what and

as much as I want6 2 2 2 5 3 1,5 1,0 9,0 2,6 65 27 1 1 3 9 9 1 -3

1 5 4 20 4 27I'm able to open my appliance's doors with little effort, it has optimal ergonomics , I like it

very comfortable , my appliance supports my daily life 7 2 2 2 3 4 2,0 1,2 16,8 4,8 70 28 -1 3 9 -1

1 4 4 16 5 28I'm able to close my appliance's doors with little effort, it has optimal ergonomics , I like it

very comfortable , my appliance supports my daily life 7 2 2 3 3 4 2,0 1,2 16,8 4,8 75 29 -1 9 9 -1

0 29 Light 5 3 3 1,0 1,0 5,0 1,4 76 30

1 4 3 12 5 30My fridge is enjoyably illuminated, I may show what's inside my fridge, I like my goods

looking nice, I love to open my fridge , I feel good in my kitchen 7 2 2 3 5 4 2,0 1,2 16,8 4,8 81 31 -1 1 9 9 9 9

1 4 4 16 1 31my fridge/freezer is a "Highlight" in the kitchen, my kitchen is transparent, the appliance

matches to my kitchen , I feel good in my kitchen, my kitchen astonishes my guests 5 3 1 4 1 4 1,3 1,2 8,0 2,3 84 32 1 1 1 3 1 9 9 9 3 3 3 1 9 3 9 3 3 3 3 1 9

0 32 Sales/Service 7 3 3 1,0 1,0 7,0 2,0 86 33

1 1 1 1 5 33

It's all BSH appliances , It fits to the other family 4 2 2 1 1 2 1,0 1,0 4,0 1,1 87 34 1 1 1 -1 1 3 3 3 9 3 3 3 3

4 3 1 12 3 34

I may easily mount the panel, Quick and easy installation , my installation team will be

happier, I can easily replace old products, it is simplifying my working life 7 3 2 3 1 4 1,3 1,0 9,3 2,7 89 35 -3 3 -9

4 3 1 12 4 35

All necessary fixing parts are already pre-mounted, I save time, I can save installation costs,

quick and easy installation , my installation team will be happier, I can easily sell this product,

I can easily replace old products, 7 2 1 2 1 4 2,0 1,0 14,0 4,0 93 36 -1 -1 -3 -3

1 1 2 2 4 36Door panel may be safely mounted, my appliance fits me, I have a nice kitchen , I feel good

in my kitchen, my installation team will be happier, I can easily sell this product 7 4 3 4 1 4 1,0 1,0 7,0 2,0 95 37

1 3 1 3 2 37The doors (thickness=25mm) may be openend without problems, my appliance fits me, I

like my kitchen, my installation team will be happier , I can easily sell this product 6 2 2 2 1 3 1,5 1,0 9,0 2,6 98 38 1 -3

1 3 1 3 5 38 Heavy front panel (30 kg) could be adapted 5 2 1 2 1 3 1,5 1,0 7,5 2,1 100 39 -3

0 39 40

41

42

Su

m:

Weight

Rel. weight (%)

Positive weight

Negativ e weight

Considerable number of negative relationships, also on important customer requirements.

negative

positive

Positive and negative weight: Quality-features from customer view

17th


7


Figures 6: Results of the relationship matrix (new innovative product)

2.5.2 Results of the correlation matrix (“roof”)

Figure 7: Results of the “roof” of the House of Quality (new innovative product):

negative

The change (Optimization) of one Quality Feature influences all other Quality

Features

-30

-20

-10

0

10

20

30

40

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

positive

e.g. Many Quality features with less customer importance but extreme technical difficulties. This causes a cost problem. Customer pays for "importance", not for technical difficulties.

negative

It is an advantage, that the most important Quality Features

(customer view) have many positive correlations to the other

Quality Features, except “increasing speed”

(except one (the increasing speed))

There are many conflicts between the Quality Features. It shows

the need of additional, inventive solutions. negative

17th


8


2.6 QFD Matrices in concept selections

2.7 QFD and TRIZ

QFD was originally not qualified to generate inventive solutions; the focus was on the deployment of customer requirements.

TRIZ on the other hand concentrates on finding new ideas to solve contradictions.

Concept_1 Concept_2 Concept_3 Concept_4 Concept_5 Concept_6

QFD House

of Quality III

V6.0 XLM

Interpretation

Concepts

Cu

sto

me

r F

ee

lin

gs

Imp

ort

an

ce

10

-1

Cu

rre

nt

Sta

tus

1

- 5

V

5 -

1

E

5 -

1

Pla

nn

ed

Sta

tus

1 -

5

Imp

rove

me

nt

E/B

Sa

les P

oin

ts

1,

1.2

, 1

.5

Imp

ort

an

ce

We

igh

t

A*F

*G

Re

lati

ve

We

igh

t (%

)

Re

l. W

eig

htt

(%

) P

are

to

Typ

e o

f M

otio

ns

Patie

nt p

ositi

on

ing

Siz

e/S

hap

e/ F

orm

Typ

e o

f M

otio

ns

Patie

nt p

ositi

on

ing

Siz

e/S

hap

e/ F

orm

Typ

e o

f M

otio

ns

Patie

nt p

ositi

on

ing

Siz

e/S

hap

e/ F

orm

Typ

e o

f M

otio

ns

Patie

nt p

ositi

on

ing

Siz

e/S

hap

e/ F

orm

Typ

e o

f M

otio

ns

Patie

nt p

ositi

on

ing

Siz

e/S

hap

e/ F

orm

Typ

e o

f M

otio

ns

Patie

nt p

ositi

on

ing

Siz

e/S

hap

e/ F

orm

A B C D E F G H I JProj.: Table Optim.Direction

Cust: Cost $Weight QF 0 4084 370 238 353 215 292 288 328 225 290 -29 -20 1 241 250 142 292 403 205 0

Team: Rel. Weight(%): 84 8 5 7 4 6 6 7 5 6 -1 0 0 5 5 3 6 8 4 0

Moderator: G.Streckfuss (IQM) Positive Weight: 370 248 353 388 411 337 328 240 290 166 65 27 241 250 142 324 403 237 0

Date: Negative Weight: 0 -11 0 -173 -118 -49 0 -16 0 -195 -85 -26 0 0 0 -32 0 -32 0

Version 1 Technical Difficulties(10-1)Techn.Spezification:HOW MUCH

Average 6,0 2,3 3,3 2,5 3,8 2,4 1,0 17,5 7,7

Maslo

w

Customer Requirements (CR) W

eig

ht

today

Varian

Ele

kta

Pla

nned S

tatu

s 5

-1

Impro

v.

SP

227,4

100

Re

latio

ns

1 1 1 1,0

1,0

1,0

0,4 0 1

1 Relative Patient Positioning (Isocenter Management) 12 8 1 1 1 5 5,0 1,1 44,0 19,3 20 1 10 1 3 9 9 3 3 9 9

1 Machine can support high patient load for lifetime of machine 2 9 1 4 4 4,0 1,2 43,2 19,0 39 1 55 3 9 3 1 1 3 1

4 Have a interchangable pallet for CT, ... And treatment 48 8 1 4 1 4 4,0 1,1 35,2 15,5 541 18 9 9 9 -9 -3 -3 9 9 9 -9 -1 -1 3 3 3 9 9 9

2 Collision avoidance 8 6 1 1 1 4 4,0 1,1 26,4 11,6 66 1 67 3 9 9 9 -1 1 3

3 Integrated controls 3 6 1 4 1 4 4,0 1,0 24,0 10,6 76 1 39 9 9 -1 9 1 1 9 9 -1 3 3 -3 -3

4 The table top should be radiotranslucent 36 8 2 4 4 2,0 1,1 17,6 7,7 841 21 3 9 -3 -9 1 3 -3 -9 3 3 9 9

1 Easy and fast mounting accessories must be possible 4 7 3 3 4? 4 1,3 1,0 9,3 4,1 88 1 43 1 -1 9 1 9 1 -3 3 -3 3 9 9 1 9

2 No workers comp 2 8 3 3 1,0 1,0 8,0 3,5 92 1 50 1 -1 9 1 3 9 3 -1 9 9 1 3 3 3 3

2 No obstruction to Pt transfer devices eg. Stretcher 2 5 3 2 3 4 1,3 1,0 6,7 2,9 95 1 28 1 -1 9 9 9 9 3 3 -3 3 1 3 9 9

1 Surface easy to clean 1 6 4 4 4 4 1,0 1,0 6,0 2,6 97 1 22 9 -1 1 1 3 9

1 High flexibility to position the table 4 5 5 5 5 5 1,0 1,0 5,0 2,2 100 1 9 3 9 9 -1 9 9 9 3 9 3 9 9

1 Avoid destruction of the table due to earthquarks 1 1 4 4 4 4 1,0 1,0 1,0 0,4 100 1 56 9 1 9 1 3 1

Conclusion

Only 6, but

important

requirements

(red) are the

major

differentiators to

concepts

Significant

differences Frame

Co

nc

ep

t-F

ea

ture

s

Concepts:

frame

-300

-200

-100

0

100

200

300

400

500

Concept_1 Concept_2 Concept_3 Concept_4 Concept_5 Concept_6

Solutions for killing items (-9):

Try to convert (move) the "+9"

solutions from other concepts to

solve "-9" conflicts. This will

assure the most clever product in

regard to customer requirements.

Concepts after using solutions from other concepts

-100

0

100

200

300

400

500

600

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

17th


9


Only new, innovative solutions can solve these contradictions. This was one of the reasons, why TRIZ was successful adapted

in the QFD community. TRIZ asks for an “input” of conflicts and contradictions and promises to support the findings of

inventive solutions by using a systematic workflow. QFD Matrices deliver this input.

2.7.1 Analyzing TRIZ results

TRIZ has 3 Levels of contradictions (Altshuller) . 4:

Level 1: Administrative, e.g. between needs and solutions

Level 2: Conflicts (“technical contradiction”), inverse correlation between technical features.

Level 3: Contradictions (“physical contradiction”), contradictory optimization direction of one requirement.

Altshuller has proven the fact, that Conflicts (Level 2) are derived from Contradictions (Level 3). This implies, that the

inventive solution is embedded in contradictions.

Considering these arguments, it demonstrates the contrary way of the common way of engineering: We try to solve the

conflicts between technical features first (Level 2), and than, we discuss the impact on customer needs.

But it is the customer(!), who gives us the level 3 contradictions! It is the customer, who requires inventive ideas.

2.7.2 TRIZ tools in the QFD process

The method TRIZ includes numerous tools, which are very different in regard of effort, knowledge and cases of application. If

conflicts between technical features are relevant to customer requirements, than the first step is using the conflict Matrix with

Figure 8: Various links between

QFD and TRIZ 3 4

17th


10


the attached inventive principles (Altshuller, Matrix 2003). Also, this matrix is debatable among the TRIZ-Guru’s, it is our

experience that the matrix is able to deliver on the spot the first signs of new ideas, which are worth to follow up.

To solve the contradiction of one technical feature (Customer request low weight because of… and high weight because of…)

is not an easy task. TRIZ recommends using the 4 (or 6) principles in separation (in time, in space, in parts/whole, in

conditions). Practical experience realized in these cases also the need for additional TRIZ tools to address inventive solutions.

Common tools are here the Function Analysis, the Su-Field Analysis and the Anticipating Fault Determination)

3. The QFD-Q-Plan and the Mahalanobis-Distance To manage customer requirements (CR) in the QFD Process is still a never-ending story. Also QFD is in charge to deploy CR

in the various R&D and Engineering processes, it still requires, to ensure the quality of CR. Wrong input in QFD guarantees

well structured and expensive, but still wrong output.

Based on the Q-Plan structure, published in Akaos QFD book (1988/1992), QFD teams used these templates to analyze CR.

The row “importance” was availed oneself of an opportunity to discuss the meaning and understanding of CR than for rating

issues. The row “Current Status ” is one of the aching tasks, because it is often the result of: “We already fulfill these

requirements”.

Today, nearly all companies using regularly QFD modified and improved the Q-Plan to address their specific needs. They

added additional rows, common are “Value for the customer”, “Kano” and “Needs based on Maslow’s Theory”. These

different rows allow us, to discuss and rate the CR under different perspectives.

Figure 9: Extended QFD Q-Plan Matrix

This gives us a picture of a matrix (pattern), which could be analyzed. The focus is more on identifying the discrepancy

between the different values and not to calculate detailed numbers. Our first Goal is to understand and accept the customer

requirements.

Va

lue

Ka

no

Ma

slo

w

WF

=V

+K

+M

Po

ten

tia

l "Sanity Check" of the QFD

Q-Plan Matrix (extract)1

0 t

o 1

5 to

1

5 to

1

5 to

1

5 to

1

5 to

1

Imp

rove

me

nt

Sa

les F

acto

r

We

igh

t

rel. W

eig

ht

Pa

reto

avr. 2,3 3,7 2,3Remark: the text and the figures are slightly modified compared to the

original input 6,6 2,2 2,0 2,6 2,8 3,6 1,9 1,1 13,1 4,1

V K M WF P Customer Requirements and Needs Imp.Cur.M.A M.B. Test Pla 13,3 157,5 50

2 5 4 11 4 I like to have a "multimedia" environment 4 1 1 1 1 3 3,0 1,5 18,0 5,7 6

2 4 3 9 1 I know what I need to buy 5 1 4 5 5 3 3,0 1,2 18,0 5,7 11

1,0 5 4 10 4

To open and closing the cover with little effort, it has

optimal ergonomics8 2 2 2 3 4 2,0 1,2 19,2 6,1 17

1,0 4 3 8 5 The enviroment is enjoyably illuminated 9 2 2 3 5 4 2,0 1,0 18,0 5,7 23

4 2 1 7 4 All necessary fixing parts are already set-up 7 2 1 2 1 4 2,0 1,0 14,0 4,4 28

5 3 1 9 3 The environment is not wasting energy, I save energy 8 4 2 4 5 5 1,3 1,2 12,0 3,8 31

1,0 4 4 9 The environment seems to be very valuable 7 2 3 3 1 3 1,5 1,2 12,6 4,0 35

2 4 1 7 4 To store my food for long times whithout freezing 6 2 1 2 1 3 1,5 1,0 9,0 2,8 38

2 3 1 6 1 The drinks could be stored longer after opening 5 1 1 1 1 2 2,0 1,0 10,0 3,2 41

1,0 3 3 7 4 The enviroment is s ilent, the sound is pleasant 9 3 2 3 5 4 1,3 1,0 12,0 3,8 45

3 4 1 8 4 I want to see a selfcleaning enviroment 7 3 3 2 5 4 1,3 1,0 9,3 2,9 48

4 3 1 8 3 I may easily mount the cover 4 3 2 3 1 4 1,3 1,0 5,3 1,7 50

5 = high, 1= low

no customer value, means: Customer will not spend any money for it. Question: why is this importance high rated, if Value is low?

Question: why is importance low rated, if WF is high?

High value, but no excitement, no prestige issue? and there is challenge for improvement

Question: why is this importance low rated,

if competition is high rated?

Question: hight rated, also current status OK?

17th


11


3.1 The Mahalanobis Distance But the research of various examples demonstrated very clear, that the pattern in the QFD-Q-Plan are NOT independent, there

are correlations between these values. We used the Mahalanobis Metric to verify the differences.

Figure 10: Different results using Linear Ratio, T-square and Mahalanobis

The chart above shows the different results, using QFD linear ratio, Statistic Hotellings (T-square) and the Mahalanobis

Distance. Mahalanobis and Hotelling are very close in regard to the results, but the QFD linear average values are considerable

different.

In statistics, Mahalanobis distance is a distance

measure introduced by P. C. Mahalanobis in

1936. It is based on correlations between

variables by which different patterns can be

identified and analyzed. It is a useful way of

determining similarity of an unknown sample set

to a known one. It differs from Euclidean

distance in that it takes into account the

correlations of the data set and is scale-

invariant. In other words, it is a multivariate

effect size….

Mahalanobis distance is widely used in cluster

analysis and classification techniques. It is

closely related to Hotelling's T-square

distribution used for multivariate statistical

testing and Fisher's Linear Discriminant

Analysis that is used for supervised

classification.

Source and more information’s in: Wikipedia.org

17th


12


The different results are caused by the fact, that the figures: “Value (V)”,

“Kano(K)”, “Maslow(M)” are NOT independent. The Correlation-Matrix shows,

that between “Kano” and “Maslow”, it exist a high rated positive correlation. But

“Value” has no correlation to “Kano” and even a negative correlation to

“Maslow”.

Pattern: Linear Ratio's to Mahalobis Distance

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50

Multiplication

Addition

Mahalanobis Distance

Figure 11: QFD-Q-Plan Pattern: Findings from the comparison

The addition of numbers is more close to the Mahalanobis distance compared to the multiplication.

The conclusion today is:

The patterns in the QFD-Q-Plan are not independent.

To multiply the numbers as a final result is critical.

But further research is required, to underline this predication and to understand the different results in practice.

4. Summary

1. Product development faces increasing demands on management and employees to fulfill different challenges:

Customers are today more critical in demanding fulfillment of their specific requirements.

Marketing must be positioned in a global world; product development is today a global task.

The number of CR’s and CTQ’s are growing because of the increasing complexity of products.

Very few faults and/or misunderstanding regarding customer needs could lead to unforeseeable major problems.

2. Product development is confronted with numerous multi-dependences.

It requires more multivariate methods, adapted to the needs of QFD.

Correlationmatrix V K M V 1.000 0.052 -0.208 K 0.052 1.000 0.467 M -0.208 0.467 1.000

17th


13


3. QFD has to address these challenges to remain sustainable:

We accept, it is the Customer who gives us the input in QFD as a human being and not as linear equation.

Therefore, it is more important to understand and accept the customer needs as to use intransparent math methods.

4. The House of Quality with the different tables, pattern and matrices is the link between understanding customer needs

and point out the various dependencies.

5. R&D is more looking to find conflicts and contradictions in the early stage of development. This saves time and

money.

In QFD, only the relationships and correlations in matrices are capable to do this.

6. Because of the increasing complexity of the today products, it is necessary to find ways to handle large matrices.

Matrices are images, illustrating the “Quality” of a product in the view of a customer. Therefore, we should more

read these images and as to calculate the figures.

7. Last, but not the least, Marketing and R&D are the customer of QFD. Therefore, QFD has to fulfill their requirements

(and not reverse) to guarantee its sustainable future.

5. REFERENCES [1] Akao, Yoyi (1992) QFD, Wie Japaner Kundenwünsche in Qualitätsprodukte umsetzen. Verlag Moderne Industrie.

[2] Mazur, Glenn (www.mazur.net), Modern Blitz QFD ® (no matrix).

[3] Saatweber, Jutta (2007), Kundenorientierung durch Quality Function Deployment, Symposium Publishing GmbH.

[4] Gundlach, Carsten, Nähler, Horst (Hrsg.) (2006) Innovationen mit TRIZ, Symposium Publishing GmbH

BIOGRAPHIES OF THE AUTHORS

Dipl.Ing. Monika Thiess

Monika Thiess is Senior Project Manager, responsible for global R&D projects at Gaggenau Industrie in Lipsheim near

Strasbourg/France. Since 1999, she is also responsible for the introduction of Quality methods in product development, process

optimization, standardization, R&D processes, also qualified as DGQ- and internal auditor. Since 2007, Monika Thiess is

certified as QFD Moderator and since 2009 Certified QFD Architect according to the QFD-Institute Germany e. V.

Gerd Streckfuß

Gerd Streckfuß is today Partner at the "Institut für Qualitätsmanagement, Dr.Weigang + Partner".. He had assignments at

Schlumberger Technologies, CAD/CAM Division as Technical Manager in Germany and Business Development Manager

Europe, responsible for the introduction of TQM in the European operations including QFD. He is also member at the QFD

Institute Deutschland e.V. and qualified as Certified QFD Architect conferred by the QFD-Institute Germany e. V.

Dr.rer. nat. Walter Jahn (†)

After his study of mathematics, Dr.Walter Jahn worked in the mathematical institute of the University Leipzig on the field’s

stochastic and mathematical statistics. His activity centers were aspects of multivariate statistical theory including their

application in the industry. He worked as an adviser for the industry.

Some of the books with applications are:

Jahn,W. und H. Vahle [1970]: Die Faktoranalyse und ihre Anwendungen Verlag „Die Wirtschaft“ Berlin

Jahn, W. u.a. [1972]: Analyse und statistische Prozessmodellierung für die Prozesssteuerung Verlag Technik Berlin

Jahn, W. und P. Langrock [1979]: Einführung in die Theorie der Markovschen Ketten und ihre Anwendungen, Teubner

Verlagsgesellschaft

Jahn, W. und L. Braun [2006]: Praxisleitfaden Qualität – Prozessoptimierung mit multivariater Statistik

in 150 Beispielen, Hanser Verlag München Wien.

http://www.mazur.net/

why we need matrices in qfd · when qfd was born, the house of quality (hoq), as a tool was an...

Documents