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DETERMINATION OF THE TECHNOLOGICAL VALUE OF COTTON FIBRE:  3

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Results and Discussion

The technological value of cotton fibre derived by various methods, as well as the rank correlation coefficient (Rs) between the technological value of cotton and yarn tenacity, are shown in Tables 8 and 9. It is observed that the RS ranges from a very low value of 0.098 to a very high value of 0.817. In general, the RS values were the lowest for the FQI model and highest for the PDI model. The proposed multiplicative AHP model, which can be considered as a variant of the traditional FQI model, demonstrates a reasonably good RS value of 0.738 and 0.716 for 22 Ne and 30 Ne respectively. The SCI model shows a moderate RS value of 0.401 and 0.459 for 22 Ne and 30 Ne respectively.

The traditional FQI model is basically a multiplicative model where all the criteria weights (Wj) are considered to be unity. However, in practice this assumption is totally void, as the influence of various fibre properties on yarn properties will not be identical. Therefore, in a multiplicative type model, proper emphasis must be given to the weights of different decision criteria. This modification is introduced here in the multiplicative AHP model resulting in enhanced RS values.

From Table 9, one may be tempted to conclude that in the given problem, the premium-discount index is the best method to determine the technological value of cotton. However, in the premium-discount index model, the decision maker receives a clear idea of the influence of fibre properties on yarn tenacity from the standardised ‘β’ coefficient values. The real accuracy of the premium-discount index model can be judged by subjecting it to some new test samples, which were not used for developing the regression equation relating the fibre properties and yarn tenacity. In case of the multiplicative AHP model, the relative weights of the cotton fibre properties are obtained from the pair-wise comparison matrix, where entries were made based on the past experience of the decision maker, without having any specific knowledge of the present case. Therefore, the multiplicative AHP is a very flexible tool, and can be used in any situation where the decision-maker has some prior knowledge of the problem.


Table 8. Cotton fibre properties and the technological values

Sample No

FS

FE

UHML

UI

SFC

FF

FQI

SCI

PDI

MIAHP

1

28.7

6.5

1.09

81

13.8

4.4

575.9

119.9

minus

47.5

2.998

2

28.5

6.6

1.15

80.2

11.9

3.5

751.0

125.7

-37.7

3.182

3

28.7

5.7

1.1

79.2

18.4

3.7

675.8

118.9

-80.1

2.915

4

30.8

6.4

1.13

82.6

9.8

4.3

668.6

133.6

28.8

3.261

5

26.5

5.8

1.09

81.5

8.4

3.8

619.5

120.6

-20.2

3.193

6

27.5

6.3

1.07

82.8

8.4

4.5

541.4

120.6

-5.6

3.167

7

29.2

5.3

0.98

80

16.6

4.5

508.7

109.2

-49.7

2.809

8

29

6.7

1.05

81.9

10.9

4.2

593.8

124.3

-7.7

3.102

9

30.3

6.7

1.1

83.2

8.7

4.4

630.2

134.3

33.7

3.278

10

28.1

6.3

1.01

80.7

15.5

3.8

602.7

117.5

-51.6

2.909

11

30.6

6.6

1.07

83.1

9

4.7

578.9

130.1

33.6

3.219

12

28.7

6.7

1.05

81

11.8

3.9

625.9

120.2

-23.5

3.078

13

28.3

6.5

0.97

81.5

13.1

3.8

588.8

118.3

-21.4

2.959

14

29

6.6

1.06

80.7

11.3

3.1

800.2

129.1

-5.1

3.191

15

27.7

5.5

1.05

81.5

11.7

4.7

504.3

110.5

-33.5

2.970

16

29.1

6.1

1.05

81.7

11.2

4

624.1

123.9

-0.8

3.097

17

28.6

5.7

1.04

82.4

10.8

4.2

583.5

125.0

4.1

3.069

18

28.8

5.5

1.05

82.6

9.2

4.1

609.2

126.2

23.2

3.161

19

28.1

6.7

1.03

81.7

7.2

4.5

525.5

116.8

-1.5

3.223

20

29

6

1.04

81.4

6.8

5

491.0

114.0

8.9

3.233

21

31.7

6.3

1.03

80.6

8.9

3.7

711.3

131.0

46.2

3.284

22

29.3

6

1.03

81.2

8.1

4.4

556.9

119.9

13.5

3.195

23

29.1

6.9

1.05

83.2

5.6

4.6

552.6

128.0

36.0

3.398

24

30.8

6.4

1.01

81.7

6.8

3.7

686.9

132.0

60.5

3.378

25

26.7

6.9

1.04

82.6

7.5

4.8

477.8

111.7

-22.4

3.155

26

30.2

6.7

1.06

82.3

5.6

4.3

612.7

128.9

48.5

3.457

27

28.7

6.2

1.02

80.7

8.7

3.8

621.7

120.1

3.9

3.188

28

29.5

6.4

1.02

81.9

7.2

4.8

513.4

116.3

20.6

3.228

29

27.5

6.9

1.01

81.7

9.7

4.5

504.3

110.9

-27.8

3.054

30

28.9

6

1.07

81.1

7.7

4.6

545.2

116.3

1.9

3.226

31

30.3

6.1

1.1

80.6

8.4

4.6

584.0

121.7

8.6

3.252

32

34

6.6

1.2

82.8

6.8

3.8

889.0

155.6

99.7

3.649

33

26.8

5.3

1

80.8

6.8

4.9

441.9

101.7

-18.3

3.117

 

Table 9. Rank correlation value between the technological value of cotton and yarn tenacity

Technological value
model

Yarn count

22 Ne

30 Ne

FQIHVI

0.098

0.129

SCI

0.401

0.459

PDI

0.817

0.809

M IAHP

0.738

0.716

 

Conclusions

A new multiplicative AHP model has been proposed to determine the technological value of cotton. The proposed method uses a variant of the traditional FQI formula, and enhances the rank correlation between the technological value of cotton and yarn tenacity. The incorporation of proper weights of cotton properties in the multiplicative formula is more logical than having the same weight for all the cotton properties. The past experience of the decision-maker plays a key role in determining the criteria weights in the proposed multiplicative AHP method. Of the four methods considered here, the premium-discount index method shows maximum rank correlation between the technological value of


cotton and yarn tenacity. The multiplicative AHP, SCI and FQI models are the remaining three methods, in the order of descending rank correlation. Similar studies could also be initiated using other MCDM methods.

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