Razor Technical Report

Components:

Albert Lopes

Andre Rufino

David Ferreira

Eric Araujo

Mohammed Woyeso

Thomas Caiado

Vytor Almeida

December 2010

Summary

1) Introduction: ......................................................................................................................... 3

2) House of Quality: ................................................................................................................... 4

2.1) Customer requirements ......................................................................................................... 4

2.2) Technical characteristics ........................................................................................................ 5

2.3) Relationship matrix ................................................................................................................ 5

2.4) Expected quality deployment ................................................................................................ 6

2.5) Technical comparison ............................................................................................................ 7

2.6) Correlation among technical characteristics ......................................................................... 7

3) Lyman Normalization: ........................................................................................................... 8

4) AHP method: ......................................................................................................................... 9

5) The Q-bench Algorithm: ........................................................................................................ 9

6) Fmeca: ................................................................................................................................. 10

7) Conclusion: .......................................................................................................................... 12

8) References: .......................................................................................................................... 12

Attachement 1............................................................................................................................. 14

Attachement 2............................................................................................................................. 16

Attachement 3............................................................................................................................. 17

1) Introduction:

In this technical report will be analyzed the Razor for a targeted market

segment. There are different types of Razor available on the market such as

the straight blade, 2 blade razor, 3 blade razor, electric razor, etc.

In this project report, it was focused on the Electric Razor. It was identified

some of the criteria that the customers require from a Electric Razor, and then

due to those needs it was described the technical characteristics to satisfy

those requirements. After that the house of quality can be started.

The report is divided in six steps:

1. House of Quality

2. Lyman method

3. AHP Method

4. Q-bench Algorithm

5. Fmeca

6. Attachments

2) House of Quality:

2.1) Customer requirements

In the construction of the house of quality, firstly it should be identified the

customer requirements by making a questionnaire.

The followings are the results obtained from the administering questionnaire:

It should have long cycle life

It should have good appearance

It should be safe

It should be easy to handle

It should be have a design project for faces

It should shave fast

It should not irritate the skin

It should shave close to the skin

It should have a good accuracy when is shaving

The battery should have a good durability

It should not have a loudly noise

Secondly these requirements were ordered as is written below:

Life time of the Blade

Aesthetics

Risk of nicks and cuts

Ergonomics

Facial Adaptability

Shaving Time

Skin Irritation

Close Shaving

Precision

Battery Efficiency

Noise

2.2) Technical characteristics

Thirdly it was developed the following technical characteristics to meet these

requirements; here is the list of the technical characteristics:

Edge straightness tolerance

Blade Edge thickness

Blade tensile strength

Blade Vickers hardness

Weight

Battery Duration

Recharge time

No. Of colors

Length

Body coefficient of friction

Sound intensity level

Rotational Speed

No. Of Blades

Blade range of move

2.3) Relationship matrix

Then the degree of importance was obtained from the questionnaires, and the

relative importance can be easily calculated: just by dividing each degree of

importance by the sum of all the degrees.

In the next level the relationship matrix should be done, which shows how the

technical characteristics are related to the customer requirements (Figure-1)

Figure-1: house of quality with customer requirements and technical characteristics and the relation ship

matrix in which = 9 (strong correlation),O = 3 (medium relationship),Δ = 3 (weak relationship)

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A B C D E F G H I J K L M N

1 Life time of the Blade 2 5,7%

2 Aesthetics 1 2,9%

3 Risk of nicks and cuts 5 14,3%

4 Ergonomics 3 8,6%

5 Facial Adaptability 4 11,4%

6 Shaving Time 3 8,6% r

7 Skin Irritation 4 11,4% r

8 Close Shaving 5 14,3% r

9 Precision 3 8,6% r

10 Battery Efficiency 2 5,7% r

11 Noise 3 8,6%

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2.4) Expected quality deployment

A benchmarking was done to understand the customer quality perceived. It was

asked about how the quality of current model and the competitors’ model is,

according to the result, the target was defined.

Dividing the target by degree of importance, it was found the improvement

ratio. The strength column is to identify the product’s potential strength for an

improvement, 1.5 very important strength, 1.2 possible strength, 1.0 not

considered as strength.

Then the absolute weight is calculated by multiplying the degree of importance

and improvement ratio and strength (Figure-2).

Figure-2: Expected quality deployment

3 5 3 4 1,33 1,00 3 5%

3 4 3 4 1,33 1,00 1 3%

4 3 4 4 1,00 1,20 6 11%

3 4 2 3 1,00 1,00 3 6%

2 4 3 3 1,50 1,20 7 14%

3 3 4 4 1,33 1,00 4 8%

4 3 3 4 1,00 1,50 6 11%

4 5 4 5 1,25 1,50 9 18%

4 3 4 5 1,25 1,20 5 9%

3 4 3 4 1,33 1,50 4 8%

2 2 3 3 1,50 1,00 5 9%

53 100%

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2.5) Technical comparison

In this part, for each technical characteristic it is multiply the relationship value

by the relative importance of the correspond customer requirement then it is

sum up the results for each column this number will show the technical

importance which says how important is the technical characteristic due to

customer satisfaction.

The Absolute weight can be found by doing the same calculation but instead of

relative importance, it is used the relative weight column. This shows the

absolute weight of each technical characteristic.

At the end the technical characteristics of the current mode should be simply

compared with other competitors’ model to find its level of competitiveness.

(Figure-3)

Figure-3: Technical comparison

2.6) Correlation among technical characteristics

It was build the roof of the house of quality. At first the vector for each

technical characteristic was found. Analyzing the relationship matrix if exist any

relation the number 1 is sign, otherwise number 0, this process should be

repeat for all of the technical characteristics. Then formulas are applied with

the vectors value found:

A: (a1, a2, a3... a14)

B: (b1, b2, b3... b14)

Cosα = A.B [0: 1]

|A| |B|

Then if Cosα > 0.66, they are correlated, then it is check logically if the result found is right if no, the word NO is sign, otherwise it is check between those two technical characteristics that are correlated if one increase the other one

will increase too (positive correlation) it is sign with “+”, if they have negative correlation it is sign with “-“. (Attachment_1) As showed on the attachment_1 the result shows that:

- Blade Edge thickness & Blade Vickers hardness are positively correlated;

- Weight & Length are positively correlated;

- Battery Duration & Recharge time are positively correlated;

- Edge straightness tolerance & Blade tensile strength are negatively

correlated;

- The other correlations are irrelevant.

3) Lyman Normalization: In Lyman normalization method, the Absolute weight of technical

characteristics can be founded by normalized relationship values.

It means that first should normalize the relationship values due to each

customer requirements then this number is used instead of exact relationship

value for calculating the absolute weight.

As noticed in Figure 4 and Figure 5, the results are a bit different but not so

much.

Figure-4: Comparison of technical characteristics importance with and without Lyman

Normalization

Figure-5: Graphic comparison of technical characteristics importance with and without Lyman

Normalization

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1 2 3 4 5 6 7 8 9 10 11 12 13 14Techn. Char.

RANKING Comparison no LYMAN

with LYMAN

In Lyman method, it is also taken in to account the proportion in the

contribution of the requisites; it will give a better ranking for technical

characteristics.

4) AHP method:

Due to comparison evaluation of the customer requirements the matrix which

is symmetrical matrix is can be created (Attachment_2)

Then it will be needed to find λmax, the software Matlab was used, due the

calculation would be quit complicated.

After getting these results it is able to find CR and CI with fallowing formulas

(according to CI it was found RI, as showed in the attachment_2) if CR>0.1 then

it is not acceptable otherwise the result is acceptable. According the result on

attachment_2 CR is smaller than 0.1, so it has a consistency acceptable.

CI= (λmax-n)/(n-1)

CR= CI/RI

As noticed on the comparison graph in attachment_2 it exist differences in

some points but on other points there are not so much differences, because of

the small difference it is possible to accept the result.

5) The Q-bench Algorithm:

First due to the current model and competitor’s model it has been done a

domain contraction, and this it is able to find the characteristic that has the

highest weight (technical relative importance) as is shown by yellow color in

attachment_3.

Then according to the signs inc or dec the target have been chosen. In this way

that the characteristic A which has the highest weight should get to its best

situation in the target and as it has inc sign so it should have the highest

number of the domain which is 13000, but others would be in their worst

cases, except the ones that do not have any sign they will stay in their previous

situation. It means that it has improved the characteristic with highest weight.

Then it was made a comparison between the target and the competitors’

technical characteristics, and fill the matrix with these formulas:

If both situations are satisfied, it is noticed that aOa’ which means a outranks

a’.

Then according to the matrix that is built it is able to draw the graph. Then

possible eliminate all the loops, then the one that outranks all, by doing this

able to find a preference sequence. In this case the target is that last preferred

so the process should be repeated all by improving the next characteristic with

highest weight.

The process has been repeated for 4 times till find a target which is preferred to

all the others. (attachment_3). By this result it has been notice that some

improvement should be in some points.

6) Fmeca:

Failure mode and effect analysis was performed on the prototype to determine

possible causes of failure and severity of the effects. It is important to

anticipate all of the ways a product could fail so that it will operate properly

after repeated use and cause no risk to the operator.

For each component, it was examined all of the possible ways in which the

razor enclosure could fail. The internal components were not considered in this

evaluation outside of their interactions with the enclosure because they will be

purchased. After identifying all of the possible failures, we rated them on

severity of the problem and probability of occurrence. The criteria for rating

can be found in Tables 1, 2 and 3.

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Table 1. Severity ratings of failure for FMECA

Rating Description

1 Minor

Functional failure of part of machine or process - no potential for

injury

2 Critical

Failure will probably occur without major damage to system or

serious injury

3 Major Major damage to system and/or potential serious injury to personnel

4 Catastrophic Damage causes complete system loss and/or potential for fatal injury

Table 2. Probability ratings of failure for FMECA

Rating Description

1 Frequent Likely to occur frequently

2 Probable Likely to occur several times in the life of the item

3 Occasional Likely to occur sometime in the life of the item

4 Remote Unlikely to occur but possible

5 Improbable So unlikely that occurrence may not be experienced

Table 3. Detection ratings of failure for FMECA

Rating Description

1 No uncertainty

2 Very low uncertainty

3 Low uncertainty

4 High uncertainty

5 Very High uncertainty

The results of the FMECA are presented in the Attachment 4.

7) Conclusion:

The product analyzed in this report was electric razor; the work had been

started with the structure of the house of quality, then the relative importance

of the technical characteristics and relative weight for customer requirements

were found and also the correlation between technical characteristics.

The work has been started by the structure of the house of quality, and then it

was found the relative importance of the technical characteristics and relative

weight of customer requirements, also it was found the correlation between

technical characteristics.

In next steps we found rankings for customer requirements by AHP method and

compare it to the results of the house of quality.

It was applied the same approach for the ranking of technical characteristics by

Lyman method.

Then it was found a target for technical characteristics by applying Q-bench

analysis.

And at end the potential failure mode were analyzes, showing what potential

failure mode the product may have, then also it was found out which failure is

more critical and risky than the other ones.

8) References:

www.philips.com.br

www.panasonic.com

www.remingtonproducts.com

www.braun.com

badgerandblade.com

www.consumersearch.com/electric-shavers

shaverguide.com

Attachement 1

Correlation Matrix

A B C D E F G H I J K L M N

A 1.0 0.9 0.7 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.4 0.3

B 0.9 1.0 0.6 0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.6 0.5

C 0.7 0.6 1.0 0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.4

D 0.5 0.7 0.7 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.7 0.6

E 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0

F 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.5 0.0 0.0

G 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.5 0.0 0.0

H 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0

I 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0

J 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0

K 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.5 0.0 0.0

L 0.3 0.4 0.0 0.3 0.0 0.5 0.5 0.0 0.0 0.0 0.5 1.0 0.4 0.3

M 0.4 0.6 0.5 0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 1.0 0.8

N 0.3 0.5 0.4 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.8 1.0

A B C D E F G H I J K L M N

0 0 0 1 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 1 0 0 0 0 0 0

1 1 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 1 0 0 0 1 1 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 1

0 1 0 1 0 0 0 0 0 0 0 1 1 1

1 1 0 0 0 0 0 0 0 0 0 1 0 0

1 1 1 1 0 0 0 0 0 0 0 0 0 0

1 1 1 1 0 0 0 0 0 0 0 0 1 1

0 0 0 0 0 1 1 0 0 0 0 1 0 0

0 0 0 0 0 0 0 0 0 0 1 1 0 0

A B C D E F G H I J K L M N

0 0 0 0.5 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 1 0 0 0 0 0 0

0.5 0.447 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 1 0 0 0 1 1 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0.577

0 0.447 0 0.5 0 0 0 0 0 0 0 0.5 0.707 0.577

0.5 0.447 0 0 0 0 0 0 0 0 0 0.5 0 0

0.5 0.447 0.707 0.5 0 0 0 0 0 0 0 0 0 0

0.5 0.447 0.707 0.5 0 0 0 0 0 0 0 0 0.707 0.577

0 0 0 0 0 1 1 0 0 0 0 0.5 0 0

0 0 0 0 0 0 0 0 0 0 1 0.5 0 0

sum 1 1 1 1 1 1 1 1 1 1 1 1 1 1

Attachement 2

w relative w AHP

ranking Original Ranking

A Life time of the Blade -0.031 1.26% 11 9

B Aesthetics -0.051 2.07% 9 11

C Risk of nicks and cuts -0.505 20.72% 2 1

D Ergonomics -0.191 7.86% 5 5

E Facial Adaptability -0.137 5.61% 6 3

F Shaving Time -0.370 15.17% 3 5

G Skin Irritation -0.267 10.95% 4 3

H Close Shaving -0.680 27.94% 1 1

I Precision -0.098 4.01% 7 5

J Battery Efficiency -0.037 1.54% 10 9

K Noise -0.070 2.87% 8 5

Pairwise Comparison Matrix

A B C D E F G H I J K

A 1.00 0.33 0.11 0.14 0.17 0.11 0.13 0.11 0.20 0.50 0.25

B 3.00 1.00 0.13 0.20 0.25 0.14 0.17 0.11 0.33 2.00 0.50

C 9.00 8.00 1.00 4.00 5.00 2.00 3.00 0.50 6.00 9.00 7.00

D 7.00 5.00 0.25 1.00 2.00 0.33 0.50 0.20 3.00 6.00 4.00

E 6.00 4.00 0.20 0.50 1.00 0.25 0.33 0.17 2.00 5.00 3.00

F 9.00 7.00 0.50 3.00 4.00 1.00 2.00 0.33 5.00 8.00 6.00

G 8.00 6.00 0.33 2.00 3.00 0.50 1.00 0.25 4.00 7.00 5.00

H 9.00 9.00 2.00 5.00 6.00 3.00 4.00 1.00 7.00 10.00 8.00

I 5.00 3.00 0.17 0.33 0.50 0.20 0.25 0.14 1.00 4.00 2.00

J 2.00 0.50 0.11 0.17 0.20 0.13 0.14 0.10 0.25 1.00 0.33

K 4.00 2.00 0.14 0.25 0.33 0.17 0.20 0.13 0.50 3.00 1.00

largest eigenvalue = max = 11.74

max = 11.74 CI = 0.074

n = 11 RI (n>9) = 1.49

CR = 0.050 ≤ 0.1

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1011

A B C D E F G H I J K

customer reqs

RANKING Comparisoninterviews/questionnaires AHP

Attachement 3