Volume 10 Issue 9 - October 2, 2009 PDF
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Product design evaluation model of child car seat using gray relational analysis
Hsin-Hsi Lai1,*, Chien-Hsu Chen1, Yu-Cheng Chen1, Jo-Wei Yeh1 and Cheng Fang Lai2

1Department of Industrial Design, College of Planning & Design, National Cheng Kung University
2Department of Textile and Clothing, Fu-Jen University
hsinhsi@mail.ncku.edu.tw

Advanced Engineering Informatics, Volume 23(2),2009,165–173

 
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The purpose of this study aims to search for the comfort relations of child car seats by performing an experiment of physiological measures, and applying a scientific effective algorithm to build the product design evaluation model for designing optimal child car seats. The fundamental theory of the new product design evaluation (abbreviated as PDE ) model is based on an artificial intelligent technique, which is the analysis method of gray relation. The gray relational analysis (abbreviated as GRA ) is one kind of measuring method to analyze the relations among discrete arrays in the theory of gray system. It depends upon the geometric shape of serial curve to judge whether they are extensively related or not.

The new PDE model is developed through two stages. The first stage is to perform an ergonomic experiment to find out the relations between the comfort and the interface pressures on the child subjects. The second stage is to construct a PDE model by applying the method of gray relational analysis with programming languages.

The construction of the PDE model is based on the GRA of gray systemic theory. The model applies the GRA to analyze the pressure parameters of child car seats, and to make the relative evaluation of user’s comfort to each car seat. The program languages used to construct the new PDE model can be Visual Basic or C++.In this study, we adopted the Visual Basic. The building process is described as follows:

A. Build the relation table between seat variables and seat pressure parameters: Through seat pressure experiment and pressure data calculation, the pressure parameters of each sample can be obtained. The mean of each sample is further derived to construct a seat’s variables and seat’s pressure parameters relationship table (see Table 1) as the basis of the gray relational analysis.

Table 1. Relationships between seat’s variables and seat’s pressure parameters.
Seat no.
Seat angle
Soft mat
BCP
BPP
BCA
CCP
CPP
CCA
No. 1
20°
Non
1.3861
0.1569
44.10
16.4009
0.4689
267.95
No. 2
20°
KR
1.4746
0.0932
63.33
13.9042
0.1896
320.43
No. 3
20°
KQ
1.5094
0.1172
57.71
12.7967
0.2247
306.24
No. 4
20°
HD
1.8857
0.0961
50.71
13.8502
0.2066
299.19
No. 5
30°
Non
2.7709
0.1695
85.19
12.9149
0.3586
276.48
No. 6
30°
KR
3.2473
0.1161
118.67
9.5665
0.1630
306.86
No. 7
30°
KQ
3.1535
0.1168
123.14
10.1308
0.1687
306.67
No. 8
30°
HD
2.3438
0.1071
99.24
9.4686
0.1709
294.86
No. 9
40°
Non
2.9875
0.1917
95.43
11.5937
0.2927
255.91
No. 10
40°
KR
3.3883
0.1057
134.48
7.9544
0.1495
283.10
No. 11
40°
KQ
2.7513
0.1443
141.19
7.2699
0.2248
284.05
No. 12
40°
HD
3.1536
0.1342
115.43
7.9237
0.2141
277.24
Note: Back Contact Pressure = BCP; Back Peak Pressure = BPP; Back Contact Area = BCA; Cushion Contact Pressure = CCP; Cushion Peak Pressure = CPP and Cushion Contact Area = CCA

B. Proceed the gray relational analysis: Utilize the table 1 to process the gray relational analysis. Use Visual Basic to complete the evaluation model.

According to this evaluation model, product designer or related design develop personnel (the main model users) can proceed product design and development as well as product assessment and comparisons. It can provide an objectively scientific comfort-evaluating method to eliminate subjectively personal errors in the design process. In addition, it can effectively offer the design criteria of child’s comfort for car safety seats.

Results of the experiment and the gray relational evaluation can be summed up and discussed as the following:
  1. From the Results of total gray relational evaluation, while arranging KR and HD soft mat into pairs and adjusting the angle of back-resting support at 30°, the child’s comfort level is the optimal.
  2. A larger angle of seats can share the pressure load of buttocks, but if not adding soft mat, on the contrary, it will increase the peak value of back pressure and lead to reduce child’s comfortability. Thus, while desiring to increase angles of seat, the choice of soft mats should be emphasized in order to spread the peak values of pressures.
  3. In the aspects of soft mat textures, there is an obvious difference between non-soft mat and other three soft mats. In other words, the total values and peak value of back and buttock pressures, as well as the utility value of contact area for seat without soft mat are less than those of other three soft mats. While proceeding with the total evaluations by applying GRA, the gray relational intensities of the three soft mats are obviously higher than those of non-soft mat. Thus, adding these three soft mats will obviously enhance the child’s comfortability.
  4. In the aspects of comparisons of three soft mats, for the softest one, KQ with hardness 100.78 N, although the utility values of back and seat contact areas are higher, the total values and peak value of pressures are less than KR and HD soft mats, with hardness 116.46 N and 135.38 N, respectively. While performing the total evaluations in gray relational analysis, the KQ soft mat is not better than KR mat. The reason maybe is the same as the study of Sprigle and Chung who indicated that softer mats may cause becoming deformed too much and cannot spread contact pressures effectively. Thus, the child’s comfort will be lower due to larger contact pressures and higher peak value of pressures.
  5. Results of the relations among pressure parameters show that the percentage of the peak value of seat’s back pressure occurred in the scapulas or the lumbar vertebras is 81%, and 60% in the ischium tubercles or the thighs. Although the relations of experimental parameters and the occurred areas are not very sure. Results shown in Fig. 1 also indicate that the most frequently occurred areas of the peak value for seat’s back pressure are on the scapulas or the lumbar vertebras while for seat’s pressure are on the ischium tubercles or the thighs. Therefore, in the design of child car seats, designers should design a profile chair, which fits child’s anthropometrical profiles to avoid producing peak values of back-supporting and buttock-supporting pressure.
Fig, 1. The areas of peak values of back-support pressure and peak values of buttock-support pressure.

To summarize the above results, we know that the choice of soft mats will affect the pressure parameters. Choosing an adequate soft mat can effectively reduce peak value of pressures and increase child’s comfortability. In addition, different angles of back-resting support can also affect pressure parameters. While increasing the angles of seats, designers should make use of soft mat design to reduce the peak value of pressures and simultaneously utilize profile chair or mat design to avoid producing new pressure loads. Results of this study by applying GRA are consistent with results of experimental statistics. Hence, the effect of this PDE model by applying GRA is right. This PDE model can also applied to different chair parameters, such as evaluating the relations between different chair’s contours and child’s comforts, the pressure affections of adding different accessories of chairs, and so on. Therefore, the construction of the evaluation system will be helpful to the design decisions.
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