sThis paper has been written under the auspices of the U.S. Government and is therefore not subject to copyright in the United States of America.

* Correspondence to: Richard G. Gann, Fire Science Division, Building and Fire Research Laboratory, National Institute of Standards and

Technology, Gaithersburg, MD 20899, USA.

FIRE AND MATERIALS, VOL. 21, 259—264 (1997)

Fabrics for Testing the Ignition Propensity

of Cigarettess

Keith R. Eberhardt1, Mark S. Levenson1 and Richard G. Gann*2

1 Statistical Engineering Division, Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg,

MD 20899, U.S.A.

2Fire Science Division, Building and Fire Research Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899,

U.S.A.

This paper reports an analysis of data from a study conducted by the cigarette industry to determine whether the

fabrics used in a measurement method for cigarette ignition propensity reasonably represent the ignition behaviour of

actual upholstery fabrics. A ‘consistency score’ is defined to evaluate objectively the relative agreement of ignition test

results on various test fabrics compared with the cotton duck fabrics used in the measurement method. Particular

attention is paid to those cases where the cigarettes show statistically significant differences by the chi-squared test.

This analysis finds that the aggregated set of 79 industry fabrics ranks the four test cigarettes in the same order as do

the three cotton duck fabrics in the measurement method. Thus, to the extent that the industry set is representative of

those fabrics used in upholstery, it would be proper to use the three test fabrics as surrogates for the purpose of

determining the relative ignition propensity of a cigarette. The analysis does identify six to ten fabrics that would be

expected to show persistent reversals compared to the aggregate ordering; however, three-fourths of the fabrics rank

the cigarettes consistently with the cotton duck fabrics. ( 1997 John Wiley & Sons, Ltd.

Fire Mater., Vol. 21, 259—264 (1997)

INTRODUCTION

Cigarette ignition of soft furnishings (upholstered furniture and bedding) has long been the leading cause of fire

deaths in the United States.1 In the 1970s, extensive effort

was directed at increasing the resistance of mattresses

and upholstered furniture to cigarette ignition, resulting

in test methods and regulations for those products. Later,

Federal legislation in 1984 and 1990 directed research

efforts to determine whether the potency of the cigarette

as an ignition source could be moderated. In the final

report to the Congress under the Cigarette Safety Act of

1984,2 the investigators reported that it was possible to

make cigarettes with reduced ignition propensity and

identified several cigarette characteristics whose adjustment could have a significant effect. They also found that

ignition results from bench-scale mock-up testing agreed

very well with corresponding data from experiments with

full-size chairs made of the same fabrics and padding

materials. However, they identified a need for a standard

test method for cigarette performance that was not subject to the high variability in the fabrics and paddings

used in those mockups.

Under the Fire Safe Cigarette Act of 1990, two

methods for measuring cigarette ignition propensity were

developed:3,4

f The Mock-up Ignition 1est Method uses three types of

simulated upholstery cushions, each with a different

cigarette ignition susceptibility. Each assembly (substrate) consists of a top layer of one of three weights of

cotton duck fabric; a cushion of a polyurethane foam,

and, in the least susceptible substrate, a thin layer of

thermoplastic film in between. The performance

measure is whether or not the mock-up is ignited by

the cigarette placed on it.

f The Cigarette Extinction 1est Method replaces the

more complex substrate with 3, 10 or 15 layers of

standard cellulosic filter paper. The performance

measure is whether the cigarette extinguishes before

burning its full length, i.e. whether the substrate absorbs enough heat from the cigarette coal to extinguish

the cigarette.

Both of these test methods were subjected to interlaboratory evaluation by nine participating organizations. The

results demonstrated that both methods had values of

(intralaboratory) repeatability and (interlaboratory) reproducibility comparable or superior to other standard

fire tests.3

Subsequently, the Mock-up Ignition Method has been

criticized for its use of test fabrics (cotton ducks) considered to be unrepresentative of fabrics used in the

manufacture of upholstered furniture.5 A joint venture of

cigarette industry firms purchased approximately 500

upholstery fabrics and tested them using a mock-up test

apparatus and procedure different form the Mock-up

Ignition Method.6 They concluded that most of the fabrics ranked cigarettes differently from the cotton duck

fabrics used in the mock-up ignition test method.

The following statistical analysis of the data from Reference 5 was undertaken to investigate the strength of

this conclusion. We approached this analysis with some

CCC 0308—0501/97/060259—06$17.50 Received 30 May 1997

( 1997 John Wiley & Sons, Ltd. Accepted 29 September 1997
uneasiness because there are many things about the conduct of the industry experiments that are not known. In

particular, the conclusions from the statistical analysis

are sensitive to whether or not the tests were run in

a balanced design with respect to significant test conditions. For example, the interlaboratory evaluation conducted under the Fire Safe Cigarette Act of 1990 showed

some evidence of ignition effects due to operator and to

time-of-day (morning versus afternoon). If the experimental design for the present data were unbalanced, then

some factors such as differences between operators, or

between test chambers, or due to time-of-day, or to

position within the test chamber or to other environmental factors would be confounded with cigarette

and/or fabric differences. Such confounding would cause

unresolvable ambiguity in interpreting the results. In the

absence of complete information on the experiment design, our analysis in effect rests on the implicit assumption that the test conditions were completely uniform

throughout, and therefore that observed differences in

the results can be interpreted solely in terms of the fabric

and cigarette types, plus (binomial) random variation.

INDUSTRY DATA

Aspects of the industry study are reported in References

5 and 6. Samples of 500 fabrics were obtained from shops

in the Greensboro, NC, area with the goal of surveying

upholstery fabrics that are in wide use and representative

of materials commonly found in residences. Each fabric

was tested for ignitability with an experimental cigarette

of high ignition propensity. All of the ignitable fabrics

were either 100%, or nearly 100%, cellulosic in fibre

content. In Reference 6, it is stated that 145 of the 500

fabrics were ignitable by the test cigarette, and of these,

127 were 100% cellulosic. A copy of these data (Set 1) was

provided to the Consumer Product Safety Commission

in 1993. Reference 5 states that, among the 500 fabrics

tested, there were 113 cellulosic fabrics that gave ignitions with the same test cigarette. A copy of these data

(Set 2) was provided to the National Institute of Standards and Technology in 1994 by an official in the cigarette industry.7

The industry group then selected four different experimental cigarettes and tested each on the ignitable cellulosic fabrics. The test apparatus and procedure are

described in Reference 6. Six replicate tests were performed for each of the four cigarettes on each of the 113

fabrics. For some fabrics, all four cigarettes either ignited

the substrates all of the time or none of the time. Table 1

summarizes the two industry reports of their ignition

data. The source of the second set of data has stated that

Set 2 should be used for further analyses. Our comparison of the two data sets indicates that the fabrics in Set

2 comprise a subset of those in Set 1.

The authors of Reference 5 assigned each of the 113

ignitable fabrics to one of three groupings—‘Duck-Like’,

‘Duck-Unlike’, or ‘Balance’— based on the fabric weight,

porosity and content of sodium and potassium ions. The

‘Duck-Like’ grouping consisted of 21 fabrics that contained high levels of alkali metal ions, coupled with high

weight and below average porosity. The ‘Duck-Unlike’

Table 1. Summary of the two industry data sets

Data set 1 Data set 2

Total number of fabrics

represented 145 113

Number of fabrics with at

least one ignition and one

non-ignition for test cigarettes 101 79

grouping included those 24 fabrics containing relatively

low levels of alkali metal ions and having a low weight

and no restrictions on porosity. The ‘Balance’ group

contained the remaining 68 fabrics.

The industry data show that the ‘Duck-Like’ fabrics

ranked the ignition propensities of the four test cigarettes

in the same order as did the cotton ducks. By contrast,

the larger set of ‘Duck-Unlike’ fabrics, in aggregate,

ranked the same four cigarettes quite differently. The

authors concluded that the mock-up ignition test method

‘provides a measure of cigarette propensities that is not

representative of those found on commercial fabrics’ and

‘its adoption as a definitive test for ranking cigarettes can

lead to erroneous conclusions.’ (Reference 5, pp. 81, 82)

The physical interpretation of this result is uncertain.

Both groupings of fabrics were predominantly cellulosic;

thus the fuel chemistry is similar. Most of the oxygen

needed for ignition is available from the air above the

fabric;8 an industry analysis of the permeability of the

fabric weave to air has shown it to be of secondary effect

on the ignition process.9

The following analysis of the industry 500 fabric study

is not based on any groupings of the fabrics, but focuses

directly on the ignition propensity results. This analysis

was undertaken to obtain an independent evaluation of

the extent to which fabrics show inconsistent ignition

behaviour in these data.

THIS STUDY

The purpose of this analysis was to investigate the relationships among the reported ignition propensities of

four selected cigarette types (designated as 528, 525, 508,

and 506) as measured across the wide variety of fabrics in

the industry 500 fabric study. In particular, the relative

ignition propensities were measured in terms of the number of ignitions out of six trials of each cigarette type on

each fabric. The industry data set contains results for 113

different fabrics. Of these, the results for 34 fabrics did not

produce cigarette rankings because in these cases all four

cigarettes either ignited the fabric 100% of the time (23

fabrics) or 0% of the time (11 fabrics). Thus, we consider

a reduced data set consisting of the outcomes (number of

ignitions in 6 trials) from 316 tests (4 cigarettes on each of

the remaining 79 fabrics). This reduced data set is shown

in Table 2.

Testing for between-cigarette differences

To avoid trying to interpret differences in ignitions that

are not statistically significant, we computed, for each

260 K. R. EBERHARDT, M. S. LEVENSON AND R. G. GANN

( 1997 John Wiley & Sons, Ltd. Fire Mater., Vol. 21, 259—264 (1997)
* A simple test for interaction was conducted by using analysis of variance (ANOVA) on the ignition counts in Table 2, after first transforming the raw

counts by the Freeman—Tukey version of the angular transformation.10 In the resulting two-way table with one observation per cell, the test for

interaction was performed using Tukey’s one-degree-of-freedom test for additivity.11

fabric, the chi-squared (s2) statistic appropriate for testing the hypothesis that the ignition propensities of the

four cigarettes are equal. Since the experiments were

based on a small number of tests (6 for each cigarette and

fabric combination), the differences in the observed ignitions were not statistically significant for about half of the

fabrics. However, the s2 test did indicate a significant

difference between cigarettes (at the 5% level) for 41 of

the 79 fabrics. The results shown in Table 2 are listed in

decreasing order of the s2 statistic, so that fabrics showing the nost significant differences between the four cigarettes appear near the top of the table. Fabrics for which

the cigarettes differ significantly at the 5% level of significance (i.e. s2'7.81) are marked with a single asterisk (*).

Those which also detect differences at the 1% level of

significance (i.e. s2'11.34) have a double asterisk (**).

If there were no real differences in ignition propensity

among the four test cigarettes, one could expect that

purely random variation would cause the s2 test to

produce ‘false positive’ conclusions (that significant differences exist at the 5% level of significance) for about

5% of the 79 fabrics (i.e. four fabrics). The fact that 41

such cases were observed implies that real differences do

exist among the cigarettes, and that this conclusion is not

compromised by statistical considerations related to

multiple comparisons or multiple testing. Similar conclusions follow from the results of the s2 test at the 1%

level of significance. Under the null hypothesis that these

four test cigarettes are truly equal, only one fabric (i.e. 1%

of 79) would be expected to yield s2'11.34, compared

with 28 which were observed. Thus, it is reasonable to

proceed with the data analysis on the assumption that

these four test cigarettes are showing real differences in

ignition propensity and not just random variation.

Testing for statistical interaction

Interaction is present in a statistical model whenever the

difference (in some metric) in the ignitability of two

cigarettes changes depending on the fabric used. Two

major types of interactions are possible. In the first, the

rank ordering of the cigarettes’ ignition propensities is

the same on all fabrics, but the magnitude of the differences varies. An example of this would occur if cigarette

type A is more likely than cigarette type B to ignite all

fabrics, but type A is twice as likely as type B to ignite

fabric X and 3 times as likely to ignite fabric Y. The

second type of interaction involves ‘reversals’. A reversal

would be indicated if, for example, cigarettes of type

A consistently showed higher ignitability than type B on

some fabrics, but that order was reversed, with type

A lower than type B, on other fabrics. For purposes of

this investigation, we will consider that an interaction is

important only if it affects the direction, and not just the

magnitude, of a difference in ignitability.

It is a straightforward matter to conduct a statistical

test for general interaction between fabric type and cigarette type based on the data in Table 2. The result of

performing such a test* is that the null hypothesis of zero

interaction is strongly rejected (p(0.001). Thus, we conclude some type of interaction between fabric type and

cigarette type is clearly indicated by the data in Table 2.

Identifying ‘reversals’

Given the conclusion that some type of interaction exists

between cigarette type and fabric type, the next issue is to

distinguish whether the cigarettes and fabrics indicate

a reversal phenomenon. While there is no standard statistical approach to address this specific type of question,

we have used a simple and practical approach that seems

adequate for present purposes.

To identify easily and objectively which fabrics show

evidence of a reversal in the behaviour of the four cigarettes, we found it convenient to define a numerical

criterion called the ‘consistency’ score for each fabric.

This consistency score is defined so that it takes positive

values when the numbers of ignitions for the four test

cigarettes are generally in the same order as the total

ignitions for all tests, which was 525'528'508'506.

For brevity, we refer to this ordering as the ‘aggregate

ordering’. The consistency score takes negative values

when the results tend to be reversed, compared to the

aggregate ordering. For each fabric, the value of the score

is calculated as follows: select two cigarettes from the four

tested, and compute the difference in the number of

ignitions, carrying out the subtraction according to the

aggregate ordering. Then sum these differences over all

such pairs. The result is as follows:

Consistency"(X525!X528)#(X525!X508)

#(X525!X506)#(X528!X508)

#(X528!X506)#(X508!X506)

where, e.g. X525 is the number of ignitions for cigarette

525 on a given fabric. This definition of a consistency

score coincides with the linear component of the trend in

the ignitions which would be estimated using orthogonal

polynomials.12 This means that if the four cigarettes are

assigned ranks in the order (525, 528, 508, 506), and if

numbers of ignitions are fit by regression as a linear

function of the ranks, then the slope of that function is the

consistency score.

‘Reversals’ and statistical significance

Study of the results in Table 2 yields the following summary of the relation between the consistency scores and

the s2 values.

Table 3 shows that 77% of the fabrics (61 out of 79)

indicate general agreement with the aggregate ordering

shown at the bottom of Table 2, which is

525'528'508'506

In the aggregate ordering, the total ignitions for cigarettes 525 and 528 were nearly equal (292 and 319 out of

474, or 62 and 67%). This outcome is quite similar to the

ordering of these same cigarettes tested on the cotton

IGNITION PROPENSITY OF CIGARETTES 261

( 1997 John Wiley & Sons, Ltd. Fire Mater., Vol. 21, 259—264 (1997)
Table 2. Summary of results for 79 fabrics yielding at least one ignition and one non-ignition with test

cigarettes

Fabric Number of ignitions in 6 trials7 Consistency s2 test of Fabric

number score significance grouping7

Cig. 528 Cig. 525 Cig. 508 Cig. 506

140 6 6 0 0 !24 24.0** Duck-Like

147 6 6 0 0 24 24.0** Duck-Like

148 6 6 5 0 19 20.0** Balance

24 0 6 1 0 17 20.0** Balance

68 6 6 2 0 22 18.5** Duck-Like

155 6 6 4 0 20 18.0** Balance

283 6 6 4 0 20 18.0** Duck-Like

64 0 0 6 2 !12 18.0** Balance

34 6 6 3 0 21 17.6** Balance

42 6 6 3 0 21 17.6** Duck-Like

6 1065 !20 17.3** Duck-Unlike

40 6 5 1 0 20 17.3** Duck-Like

66 6 6 5 1 16 15.1** Duck-Like

26 1 5 6 6 !8 15.1** Balance

37 6 6 2 1 19 14.8** Duck-Like

57 6 2 1 0 11 14.8** Balance

38 3 6 0 1 18 14.4** Balance

19 6 6 6 2 12 14.4** Balance

414 0 0 0 4 !12 14.4** Balance

1 6 6 4 1 17 13.5** Duck-Like

78 6 6 4 1 17 13.5** Balance

150 2 5 0 0 17 13.5** Balance

70 6 6 3 1 18 13.5** Duck-Like

407 3 2 0 6 !9 12.6** Duck-Unlike

74 6 6 2 2 16 12.0** Duck-Like

239 6 6 2 2 16 12.0** Balance

264 1 0 5 1 !7 11.9** Duck-Unlike

7 4 5 0 1 16 11.7** Balance

349 0 4 0 1 9 10.9* Balance

399 1 0 5 2 [10 10.5* Duck-Unlike

287 0 1 5 2 [8 10.5* Duck-Unlike

131 3 5 0 1 15 10.5* Duck-Like

105 6 6 3 2 15 10.3* Duck-Like

46 6 6 6 3 9 10.3* Duck-Like

87 6 6 6 3 9 10.3* Duck-Like

107 6 6 6 3 9 10.3* Duck-Unlike

103 3 0 0 0 3 10.3* Balance

77 0 0 4 2 [10 9.8* Duck-Unlike

135 1 6 3 3 7 8.6* Duck-Unlike

302 1 4 1 0 12 8.0* Duck-Like

401 0 1 4 1 [4 8.0* Duck-Unlike

49 1 5 2 1 11 7.6 Duck-Unlike

234 2 4 6 2 2 7.5 Duck-Unlike

276 4 4 3 0 13 7.2 Balance

499 6 6 5 3 10 7.2 Duck-Unlike

447 2 1 4 5 [14 6.7 Duck-Unlike

136 6 6 6 4 6 6.5 Duck-Unlike

286 0 0 0 2 [6 6.5 Balance

445 6 6 6 4 6 6.5 Balance

146 2 0 0 0 2 6.5 Duck-Like

110 2 5 1 2 10 6.2 Duck-Unlike

151 4 2 2 0 8 6.0 Balance

120 3 5 4 1 11 5.9 Duck-Like

289 3 3 6 5 [9 5.4 Duck-Unlike

67 5 5 3 2 11 4.8 Duck-Like

356 2 0 0 2 [4 4.8 Balance

65 0 1 3 1 [3 4.8 Balance

86 6 6 5 4 7 4.2 Duck-Like

247 4 3 4 6 [9 3.8 Balance

108 3 4 2 1 10 3.4 Balance

389 4 3 3 1 7 3.2 Balance

9 6 6 6 5 3 3.1 Balance

83 6 6 6 5 3 3.1 Balance

262 K. R. EBERHARDT, M. S. LEVENSON AND R. G. GANN

( 1997 John Wiley & Sons, Ltd. Fire Mater., Vol. 21, 259—264 (1997)
Table 2. Continued

Fabric Number of ignitions in 6 trials7 Consistency s2 test of Fabric

number score significance grouping7

Cig. 528 Cig. 525 Cig. 508 Cig. 506

85 6 6 6 5 3 3.1 Balance

90 6 6 6 5 3 3.1 Balance

127 6 6 6 5 3 3.1 Balance

129 6 6 6 5 3 3.1 Duck-Like

238 6 6 6 5 3 3.1 Balance

295 6 6 6 5 3 3.1 Balance

341 6 6 6 5 3 3.1 Balance

426 0 1 0 0 3 3.1 Balance

260 0 0 1 0 [1 3.1 Balance

293 4 5 6 4 1 2.8 Duck-Unlike

252 6 5 5 4 4 2.4 Balance

44 1 2 3 1 1 2.2 Duck-Unlike

391 1 0 1 0 0 2.2 Balance

50 1 0 1 1 [3 1.1 Duck-Unlike

169 1 2 1 1 3 0.8 Balance

4 3 4 4 3 2 0.7 Duck-Unlike

Totals 292 319 259 165

* Denotes values of s2 that are statistically significant at the 5% level of significance.

**Denotes values of s2 that are statistically significant at the 1% level of significance.

Table 3. Relation of consistency scores and significant s2 values from Table 2

Consistency scores Consistency scores Total

that do not indicate that indicate fabrics

reversals reversals

Number Percent Number Percent

All fabrics 61 77% 18 23% 79

Fabrics with s2[7.81 (p\0.05) 31 76% 10 24% 41

Fabrics with s2[11.34 (p\0.01) 22 79% 6 21% 28

duck fabrics, which was reported in Reference 5 as

525"528'508'506

with cigarettes 525 and 528 tied. We refer to this as the

‘cotton duck ordering’ for brevity. In view of the tie in the

cotton duck ordering, the consistency score defined

above, which measures consistency of an individual fabric with the aggregate ordering, should be modified to

measure consistency with the cotton duck ordering. This

can be achieved by simply eliminating the difference

between cigarettes 525 and 528 from the original definition, yielding

Modified consistency score

"(X525!X508)#(X525!X506)#(X528!X508)

#(X528!X506)#(X508!X506)

For the data in Table 2, this modified consistency score

and original consistency score agree in that they both

produce negative values (indicating reversals) for exactly

the same subset of fabrics. That is, the two versions of the

consistency score both classify the fabrics in the same

way with respect to reversals and non-reversals. Therefore, the summary shown in Table 3 applies equally to

the aggregate ordering and to the cotton duck ordering.

Thus, about three-fourths of the fabrics showing differences in the cigarette industry 500 fabric study rank these

four cigarettes in general agreement with the ordering

obtained on cotton duck fabrics in the mock-up ignition

test method. Interestingly, as Table 3 shows, this fraction

holds quite consistently whether one considers all fabrics,

or only the subset of fabrics showing significant differences in ignitions at the 5% level of significance (those

with s2'7.81), or only those significant at the 1% level

(those with s2'11.34). The remaining fabrics, which

amount to about one-fourth of each of the groups in

Table 3, show evidence of reversal in the observed patterns of ignitions.

The degree of consistency or inconsistency with the

aggregate ordering is further examined in Fig. 1. The

figure displays a histogram of the positive consistency

scores (shown in the top portion of the plot) along with

a histogram of the negative scores. (shown inverted in the

bottom portion of the plot.) Recall that positive consistency scores indicate general agreement with the results

for cotton duck, and negative scores indicate reversals.

The 41 fabrics that significantly discriminate among the

four test cigarettes at the 5% level of significance are

represented by filled squares.

Three notable patterns in the figure are (1) there are

substantially more fabrics with positive consistency

IGNITION PROPENSITY OF CIGARETTES 263

( 1997 John Wiley & Sons, Ltd. Fire Mater., Vol. 21, 259—264 (1997)
Figure 1. Consistency scores for the 79 fabrics in Table 2.

scores than negative scores; (2) the positive scores tend to

be larger in magnitude than the negative ones; and (3)

considering only the fabrics that significantly discriminate among the test cigarettes, the first two patterns are

still evident.

CONCLUSIONS

As mentioned at the end of the Introduction, meaningful

conclusions from this data analysis depend implicitly on

details about the statistical design of the industry study

that are not known to us. However, on the assumption

that those unknowns do not affect the results of this

analysis, we can summarize the results as follows:

f These four cigarettes differ in ignition propensity.

Therefore, these test cigarettes constitute a set that can

reasonably be used to evaluate the equivalency of

fabrics.

f The aggregated set of 79 fabrics ranked the four cigarettes in the same order as did the cotton duck fabrics.

Thus, to the extent that this set of fabrics is representative of those used in soft furnishings, it would be

proper to use the cotton ducks as surrogates for the

purpose of determining the relative ignition propensity

of a cigarette type. A recent, complementary analysis

by Hirschler13 arrives at the same conclusion.

f About three-fourths (61) of the 79 fabrics in Table

2 yield rankings of the test cigarettes that are consistent with the rankings observed using cotton duck

fabrics.

f About 6—10 of the 79 fabrics in this study would be

predicted to show persistent reversals, compared to the

aggregate ordering, if extended testing of ignition behaviour were conducted. These are the fabrics showing

statistically significant differences in ignition behaviour as well as negative consistency scores.

Acknowledgement

The first re-analysis of the cigarette industry data was performed by Ms.

Beatrice Harwood, now retired from the U.S. Consumer Product Safety

Commission. It was her observation, based on a preliminary data set

from the cigarette industry, that led to this analysis.

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264 K. R. EBERHARDT, M. S. LEVENSON AND R. G. GANN

( 1997 John Wiley & Sons, Ltd. Fire Mater., Vol. 21, 259—264 (1997)