5W1H, GRA and GSM in the Evaluation and Identify on ... JCIT Vol6 No12.pdf · 5W1H, GRA and GSM in the Evaluation and Identify on Optimal Design of Bike Lamps 1Jung-Chin Liang, 2Tian-Wei

5W1H, GRA and GSM in the Evaluation and Identify on Optimal Design of Bike Lamps

1Jung-Chin Liang, 2Tian-Wei Sheu, 3Jian-Wei Tzeng, 4Bor-tyng Wang, 5Nagai Masatake

1-5, First Author Graduate Institute of Educational Measurement and Statistics National Taichung University of Education, Taichung, Taiwan,

[email protected] *1, Corresponding Author Graduate Institute of Educational Measurement and Statistics

National Taichung University of Education/, Department of Technological Product Design, Ling Tung University, Taichung, Taiwan,

[email protected] 4Foreign Language Center, Feng Chia University, Taichung, Taiwan,

[email protected]

Abstract This paper presents the best way to design a new product from screening the design vocabulary of

the bike lamps as an example. This research aims to the optimal design of assessment, data mining based on the experience of experts, and it is hoped to contribute the technical education application on teaching the product design. For this purpose, the paper mentions about the methods of 5W1H and GRA (Grey Relational Analysis) with finding the analysis results of the design vocabulary, and get the best design vocabulary sets. Therefore, we can point out the optimal design factor of the bike lamps, and the order of the importance. The paper not only analyzes the optimal relation diagram for producing the best bike lamps, but also presents the Grey Structure Model (GSM) for an example of making the best design education.

Keywords: Bike lamp, Optimal design, Evaluation, 5W1H, GRA, GSM

1. Introduction

When it comes to bike lamp function for safety consideration, brightness is the basic needs. Moreover, shape, color, material are also important. Above all, they belong to design field of product shape [1-2]. About can be changed colors and brightness effect of the lights and save power, easy use, etc. It belongs to the quality of the product design function [3]. Optimal bike lamp design combines outer beauty which is called structure design, and inner one which is called quality function. Finding the optimal design factor to meet the completeness of design can make best product come true. Therefore, new product can be easily implemented by improving product quality, meeting the requirements of customers, and making fewer mistakes [4-5]. The key points of the innovation design are functionality, quality, technology, vision, economy, art, society, psychology, etc [6]. Based on the design principles above, this study proposes a new design strategy to analyze and process the design. Therefore, the best design for the bicycle lamp conditions, the importance of the assessment, and to identify the optimal design principles into the design of educational applications and manufacturing design basis can be found. This proposal combines 5W1H, GRA and GSM method to identify the key factor of bike lamp. Sorting optimal design factor is the best criterion to develop new product.

2. Methods 2.1 Optimal design principles

A new product can be developed successfully by using optimal design method. Product innovation

is a process which transfers a new ideal to a product. Combining with new science, knowledge, material and technology can realize creation a new product [7]. Product design includes creativity and improvement. Moreover, the final result of design is accomplished by analyzing optimal design factors.

5W1H, GRA and GSM in the Evaluation and Identify on Optimal Design of Bike Lamps Jung-Chin Liang, Tian-Wei Sheu, Jian-Wei Tzeng, Bor-tyng Wang, Nagai Masatake

Journal of Convergence Information Technology(JCIT) Volume6, Number12, December 2011 doi:10.4156/jcit.vol6.issue12.33

266

The definition of optimal design is creating new ideal or process. Optimal design should include creativity of product, process, and technology [8]. This paper is based on analytical method of 5W1H, expert’s opinions; design factors of bike lamp are structure appearance and quality function. 2.2 Nagai methods (5W1H)

Nagai method is a semantic structural compositions analysis method. It has been proposed in 1989

by Professor Masatake Nagai. This method combines 5W1H methods to make semantic comparison and structural composition analysis. By using the mathematical methods of finding the maximum (strong) values and the minimum (weak) values for screening these semantics, it simply compares a competitive product and the new target product. In the recent years, there are many successful researches [9-10]. The steps are as follows [11-13]. (1) Strong and weak analysis chart of 5W1H: It evaluates the properties of the new product and also the old product. Using 5W1H to make a thorough consideration and discover the characteristics of a new product. By comparing with the competitive product, extract the strong and weak values to determine the items of features. (2) The calculation of ISM: Using extract features from 5W1H to construct a relationship matrix. Compare all the possible relationships between these features. Use ISM analysis method to calculate the adjacency matrix and to get the reachable matrix. (3)Explore the decision route chart of ISM: Form the structure of this reachable matrix and determine the route of design strategies. 2.3 Grey relational analysis (GRA)

Professor Deng (1989) proposed the Grey System Theory [14], and the grey relational analysis

(GRA) can be used to manage the uncertain, multi-dimentional, discrete, and incomplete data. The main function of GRA is to calculate the discrete data and quantify the factors. Through the ordinal process, the information can be translated and there are many successful researches [15-21]. The paper aims to analysis the bike lamp design elements as for a new product design criteria. 2.3.1 Establishing the raw data analysis

For setting up the GRA, there must be reference vector and comparative vector, and they are shown

as follows. mkmxkxxxx ,...,2,1));(,),(,),2(),1(( 00000 == LL (1)

nimxkxxxx

mxkxxxx

mxkxxxxmxkxxxx

nnnnn

iiiii

,...,2,1))(,),(,),2(),1((

))(,),(,),2(),1((

))(,),(,),2(),1(())(,),(,),2(),1((

22222

11111

==

=

==

LL

M

LL

M

LL

LL

(2)

2.3.2 Generations of grey relation During the GRA process, researchers need to extract the available data by satisfying three rules, and

they are: non-dimension, scaling and polarization. There are three methods to generate and standardize the data, and they are: larger-the-better, smaller-the-better, and nominal-the-better. They are shown as follows. Larger-the-better

)(min)(max

)(min)()(

kxkx

kxkxkx

iiii

iiii -

-* ＝ (3)


267

Where )(max kxii

means the maximum number in j and )(min kxii means the minimum number

in j . Smaller-the-better: when we expect the target to be as small as possible.

)(min)(max

)()(max)(

kxkx

kxkxkx

iiii

iiji

i -

-* ＝ (4)

Nominal-the-better: when we expect the target to be between the largest and the smallest data.

OB

xOBe

ee

eex ik

ikikiik

i

ikiki

ik-

=-

-* ,

}{min}{max

}{max＝ (5)

Where 0¹OB and the target goal is zero, Nagai Masatake’s equation of smaller-the-better will be

used, that is, ijiOBjiji

xxx minmax ³³ .

2.3.3 Calculations of Grey Relational

Based on Nagai’s equation [13-14], the grey relation can be calculated in this paper when

partial grey relation’s reference vector is 0X and comparative vector is jX . When i0G is close

to 1, it means that 0x and jx are highly related to each other. The equation of the partial grey relation is shown as follows.

minmax

0max0 ))(),((

D-D

D-D=G=G i

ioi kxkx , where rrr

1

1000 ))]([(å

=

D==Dn

kiii kx (6)

Where maxD represents the maximum and minD represents the minimum When m,,2,1 L³r , it means Minkowski’s grey relation; when 2=r , it means Euclidean grey

relation. The overall grey relation is as follows.

max

j 1),(DD

-=G=G ijjii xx , where 2

1

1

2 ))]([(å=

D=Dn

kijij k (7)

2.3.4 Grey relation cardinal The grey relation i0G is compared in the decision-making process and the more important factor has

larger i0G number, and this rule is applied to be the ordinal principle of the system. 2.4 GSM structural analysis

According to the evaluation data, the GRA and grey relational ordinal can be calculated. Then the value of i0G is compared based on GRA. When the value of i0G is greater on one side, it is recognised as the more important item and becomes the guidelines lines for the system structure ordinal. This paper uses Nagai’s GSM theory to make matrix ordinal [22], and then Matlab is used for calculation. Finally, provides the information of weighting and structure. The equation of GSM is shown as follows. Make Γ denote a grey relational matrix, which is the result of a globalized GRA as follows [22].

úúúúú

û

ù

êêêêê

ë

é

=G

mmmm

m

m

ggg

gggggg

L

MOMM

L

L

21

22221

11211

mji ,...3,2,1, = (8)


268

z

zgjiji

jiij

xx

xx

-""

--=

maxmax1 (9)

2.4.1 Setting Hierarchal Structure

Due to the localized GRA, the GSM procedure sorts some classes. A hierarchy of each class is

shown as follows [21-23]. (1) Let C indicate a set of elements and it is shown as follows:

}{ q£= ijji eXC (10)

Where ;,...,3,2,1, mji = q is a class coefficient given as 10 ££q ; and

úúúú

û

ù

êêêê

ë

é

=

mmmm

m

m

eee

eeeeee

E

L

MOMM

L

L

21

22221

11211

(11)

Is the error matrix as joiije 0gg -= , 10 ££ ije and 0=iie .

(2) The ettC arg in this paper ( iC ) are placed in the digraph when the following conditions are satisfied. 1. Card iiC "= min}{ ; 2. ji CC Ë for all j , ji ¹ . 2.4.2 Setting Paths

Based on Nagai’s equation [21], the GSM procedure needs to place a directive path among several

pairs of elements and it can be shown as follows. },),{( ojoiijji xxP ggyg p³= (12) Where y is a path coefficient as 10 ££y . Next, establish a direct path for all pairs ),( ji xx of P from ix to jx

3. The research survey 3.1 Collection and selection of design elements

This study the design vocabulary information from books, magazines and multimedia, those are

prior to quality of bike lamp. Especially, the vocabulary related to shape and quality is the necessary requirements. In the first stage, sixty design vocabulary are collected, and then remove non-related phrases from research topic by using KJ and 5W1H methods. Using 5W1H method to extract design vocabulary in the second stage, and get forty items in the end. The method chooses characteristic of phrases and selects the creative design phrases by comparing optimal design phrases of bike lamp with normal case. Table 1 and Table 2 are arranged from the opinions of three experts by the design rule of structure appearance and quality function. Design elements are made by 5W1H method according to their priorities those are extracted from table 1 and 2.

3.2 Selection and coding of best element design


269

The study based on Table 1 and Table 2 of the optimal design elements, as bike lamp assessment optimized key vocabulary. Encoding these design elements into two groups, E (1) ~ E (10) and F (1) ~ F (10), and they are shown in Table 3. 3.3 The selection of experts

Ten assessors named from S (1) to S (10) are selected from design experts of Bike Lamp Company,

sales, bicycle contestants, and people who are interested in bicycle industry, and their backgrounds are shown in Table 4.

Table 4. Data of subject

3.4 The evaluation of subject

First, structure appearance and quality function are the design points for experts. Besides, optimal

design is made according to Table 3 and Table 4. The graded method of this thesis are divided into 11 levels, those are 0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, and 1. The most important design element is shown 1 while the least important is shown 0. Table 5 is the LGRA-E table (local grey relational matrix from outer structure criteria) and Table 6 is the LGRA-K table (local grey relational matrix from quality function) those are arranged from the assessment result. Moreover, put larger-the-better factor from each Y-axis of Table 5 and Table 6 into Nagai’s equation [21-23], and then get the result of recombination design phrases of Table 7 and Table 8 by using the partial grey relational equation and definition of larger-the-better from Matlab, respectively. Table 5. Appearance structure of LGRA-E Table 6. Quality function of LGRA-F


270

Table 7. LGRA-E GRA ordinal Table 8. LGRA-F GRA ordinal

Design criteria of optimal bike lamp and opinions from assessment of experts are recombined from the design phrases of Table 7 and Table 8 according to the calculation result of Gamma value. 3.5 The ordinal of optimized design

Table 9 is the design application result from the recombination of design phrases of Table 3 based

on the assessment result of Table 7 and Table 8. 4. Formation of GSM 4.1 Formation and analysis of GSM

Optimal reference design figure can be got by understanding the difference of design phrases of

figure structure and quality function. Put the data of Table 5 and Table 6 into Nagai’s equation, and GSM structure figure can be got by using local grey relational equation and definition of large-the-better from Matlab calculation which are shown in Figure 1 and Figure 2.

Figure 1. The GSM of (E)


271

Figure 2. The GSM of (F)

GSM is formed according to vertical arrangement of Gamma value. Structure and relationship can

be identified easily through bottom-up structure. Structure figures of Figure 1 and Figure 2 are divided into four levels of cluster analysis. Design phrases which are vertical arranged mean that they have the order of structure organization. Phrases which are parallel arrangement mean that the important of them are equal and inter-related. Moreover, the importance of diagonal arrangement phrases is less than the parallel ones. Therefore, divide phrases into each group which are important in common and systematic organization makes bike lamp structure design more perfect. GSM is a regular organization which shown the key point of design structure of bike lamp clearly. Analyzing cluster of design phrases can understand of structure factors and relationship all levels. Figure 1 and Figure 2 optimal design vocabulary the ordinal, as shown in Table 9. 5. Conclusion

This study assessment result is clear by providing 5W1H method, combining Gray Relation Analysis (GRA), analyzing with LGRA method, considering the sequence, continuity, articulation, integration of research structure, building vertical organization. Then the assessment results of all testers can be easily conveyed by GSM diagram. Analytical method of this research is better than the traditional ones and it is a new design method in the educational research field.

This research combines both GRA and GSM methods to transmit the survey data completely. New research method is established precisely by using the simulation tool which is called Matlab to calculate the data and plot the figure. Besides, there are still some distributions as follows, 1. Identify design factors according to assessment result and this is also an objective research method. 2. Complete design data by the appearance structure and quality function of the results of assessment. 3. Correct method decreases the probability of error design by using the evaluation experience of experts. 4. Design factor, importance of phrases and sorting of bike lamp can be classified clearly. 5. GSM is the vertical structure, expression of GSM figure is better than other diagrams. 6. Reference [1] S. P. Huang, L. T. Ba, “Bicycle book,” Bird of Minerva publishing house, Taipei, 2008. [2] D. Fujii, “The first of the science analysis of bicycle,” San Yueh Publishing Company, Taipei,

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[5] J. C. Liang, Y. L. Lee & M. Nagai, “The Innovative evaluation of product design based on AHP, GRA and GSM,” The 6th International Conference on Planning and Design, pp. 34-43, 2011.

[6] B. Jiang, “Innovative product design,” Beijing University of Technology Press publishing, Beijing, 2009.


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[9] M. Nagai, “System Analysis Method and Design Methods Technique,” Kougaku Kenkyosya, Tokyo, 1989.

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[19] D. Yamaguchi, G. D. Li, M. Nagai, “New Grey Relational Analysis for Finding the Invariable Structure and Its Applications,” Journal of Grey System, vol. 8, no. 2, pp. 167-178, 2005.

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Table 1. Appearance design selection (5W1H)


273

Table 2. Quality design selection (5W1H)

Table 3. Design elements of the coding

Table 9. Design application result of ordinal


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5W1H, GRA and GSM in the Evaluation and Identify on ... JCIT Vol6 No12.pdf · 5W1H, GRA and GSM in the Evaluation and Identify on Optimal Design of Bike Lamps 1Jung-Chin Liang, 2Tian-Wei