Characteristics of fabrics in automated handling systems

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Parameters affecting the low-force frictional characteristics of fabrics in
automated handling systems
P. M. Taylor, R. Bicker, P. J. Abbott and D. M. Pollet
Transactions of the Institute of Measurement and Control 2002 24: 15
DOI: 10.1191/0142331202tm044oa

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Transactions of the Institute of Measurement and Control 24,1 (2002) pp. 15–31

Parameters affecting the low-force
frictional characteristics of fabrics in
automated handling systems
P.M. Taylor1 , R. Bicker1 , P.J. Abbott1 and
D.M. Pollet2
1
Department of Mechanical, Materials and Manufacturing Engineering, University
of Newcastle upon Tyne, Newcastle upon Tyne NE1 7RU, UK
2
European Patent Of ce, Munich, Germany

Much research has been carried out on the automation of garment assembly but, in practice,
many of the techniques suffer from unreliability. In order to investigate why this is so, it is
necessary to determine the critical mechanical properties on the fabrics under the conditions
that will be found in the handling equipment. This paper concentrates on the frictional proper-
ties of fabrics against engineering materials with particular emphasis on these properties under
zero applied normal loads, i.e., self-weight. Several tests are described and the main results
given. These highlight the importance of humidity and the strong in uence of the fabric struc-
ture and the supporting surface on the frictional characteristics. It is concluded that either the
assembly must be carried out using well de ned fabrics and a degree of climate control or
that these effects must be carefully considered in the design of handling systems.

Key words: automation; environmental effects; fabric properties; fabric testing; test equipment.

1. Introduction

During the 1980s and early 1990s there was an upsurge in research on the auto-
mation of garment and shoe manufacture. In Japan the TRAAS programme

Address for correspondence: Prof. P.M. Taylor, Department of Mechanical, Materials and Manufac-
turing Engineering, Stephenson Building, University of Newcastle upon Tyne, Newcastle upon Tyne
NE1 7RU, UK. E-mail: p.m.taylorKncl.ac.uk

Ó 2002 The Institute of Measurement tim.sagepub.com by guest on September 8, 2012
Downloaded from and Control 10.1191/0142331202tm044oa

16 Frictional characteristics of fabrics

(Iguchi, 1990) focused on jacket production, in the USA part of the AMTEX project
(Black, 1993) was targeted at the garment industry and in Europe (European Com-
mission, 1991) there were a number of initiatives sponsored by the European
Union under its BRITE and ESPRIT programmes, complemented by various
national and in-company schemes. Although many ingenious mechanisms and
machines were invented, relatively little has been developed for use in production.
Not only is advanced machinery often dif cult to justify on cost grounds but it
must also be very reliable. In the experience of the authors, this reliability is often
dif cult to achieve in practice. In particular, slight changes in fabrics and environ-
mental conditions can cause an operation to fail catastrophically. Figure 1 shows
the result of a faulty pick-up-and-place of a rectangular fabric panel by a four-
element pinch gripper. This is an extreme case but even small errors in positioning
or alignment of fabric panels can lead to mis-sized garments with faulty seams
such as that shown in Figure 2.
It has been observed (Taylor et al., 1998) that changes in humidity can have
signi cant effects on fabric properties and hence on the performance of automated
gripping. Large, hourly changes in humidity are not untoward, with changes
within a day of 20–30% relative humidity being common throughout the world
and through many seasons. For example, consider Asheville, North Carolina. At
07.30 h in January the average (over 1880 to 1949) relative humidity (r.h.) is 82%,
at noon it is 61% (Air Ministry Met. Of ce, 1958). In Mexico City the change is
even more abrupt. From 07.00 to 13.30 h the corresponding average drops from
79% to 34%. There are similar variations when moving from one location to

Figure 1 Failed pick and place of a rectangular fabric panel


Taylor et al. 17

Figure 2 The results on a completed garment of an alignment
error at an earlier stage of the production

another in the world. Note that most fabrics are affected; indeed their ability to
absorb water is one of the reasons for their comfort.
Humidity is just one possible cause of unreliability; in order to determine why
automated handling systems are not as reliable as they need to be, a programme
of research was initiated at the University of Hull and transferred in 1996 to the
University of Newcastle upon Tyne. This activity comprises two parts, rstly the
determination of key fabric properties as required in automated systems and the
effect on these of environmental changes. The second aspect is an analysis of the
automated handling processes, using the above properties to predict the behaviour
of equipment and to use the new knowledge of the processes and materials to
design more reliable second-generation machines.
Key fabric properties are the tensile and compressive characteristics, the bend-
ing behaviour and the frictional characteristics against engineering surfaces for a
range of applied normal forces going down to zero. Most studies on fabric friction
are concerned with subjective fabric handle (the ‘feel’ of a fabric) or have studied
friction between pairs of fabrics (Thorndike and Varley, 1961; Wilson, 1963; Carr
et al., 1988). Little work has been reported on friction between fabrics and non-
brous materials, and most of this has been carried out under medium
(Nishimatsu and Sawaki, 1984a, b; Yoon et al., 1984; Ajayi, 1992) to high normal
forces (Virto and Naik, 1997). None of this can be applied with con dence for the
case of very low or zero applied normal load, such as occurs when fabric is slid
over a surface. Such sliding occurs in aligning devices and vibratory feeders. It



is, however, applicable much more widely than this; fabrics are often only gripped
locally, with the bulk of the material left to trail across the working area. This
latter material will usually slide or be distorted by the local gripping and manipu-
lation task. Consequently, the zero-load frictional data is relevant to many manual
and automatic operations such as gripping, moving and sewing. Recent work by
the authors (Pollet, 1998; Taylor and Pollet, 2000a, b) describes tests which were
used to determine the low load frictional characteristics of a range of fabrics over
three surfaces. The emphasis of these papers is on the textile technology and in
determining models for the behaviours and relating them to the earlier work
described above. The aims of this paper are to describe the test procedures in
detail and to summarize the key results with a view to establishing those para-
meters of the fabrics, the handling surfaces and the environment which will affect
the frictional forces from an engineering viewpoint. Conclusions are then drawn
regarding the implications of these results for designers of automated equipment.

2. The fabric samples and surfaces

Six types of fabric were chosen to represent the wide range of fabrics used in the
apparel industry. They cover cotton, wool, acrylic and polyester bres and two
main types of construction: woven and knitted. Their surface nishes are
unknown, being as supplied by the producers. The main technical details of the
fabrics are given in Table 1. The setts were counted under a conventional micro-
scope and the results con rmed from the laser scans described below.
A laser sensor (LD1605–4 by m e Ò ) was used to characterize the surface pro le
of the fabrics. The 300-m m diameter beam of light of wavelength 675 nm was
pointed downwards onto the fabric measurement surface. The sensor uses triangu-
lation to convert the re ected beam into a distance. A 12-bit analogue-to-digital
(A/D) converter (PC30AT-card) was used for these measurements giving a 5-mV
resolution corresponding to 1 m m displacement. The fabric sample was moved
under the sensor using an x–y table in order to get the surface pro le made up
from six scan lines 1 cm in length and 1 mm apart. For each of the six chosen

Table 1 Fabric descriptions (Courtesy of the Textile Institute)

Fabric Fibre Fabric Sett (threads/cm) Mass Thickness
code content structure (g/m2) at
Warp/wale Weft/course 0.5 cN/cm2
(P) (T) (mm)

C1 Cotton Twill weave 19 17 517 1.034
P1 Polyester Plain weave 46 39 105 0.190
W1 Wool Twill weave 12 13 352 3.095
KC1 Cotton Fleece knit 16 11 257 1.428
KC11 Cotton Double knit 14 15 183 1.030
KA11 Acrylic Double knit 15 10 264 1.230


Taylor et al. 19

fabric types, six sample pieces were used for the warp/wale tests and six separate
sample pieces for the weft/course tests. Six line pro les, each 1 cm in length and
0.1 mm apart, are scanned at 1 mm/s on every sample. The surface roughness,
SMD, of the fabrics is, in accordance with the KES-FB4 test (Kawabata, 1980),
calculated from their height pro le, hi, obtained by the laser sensor at s different
points and is de ned as follows:

O
s
¯
(hi 2 h )
1
SMD = (1)
s
¯
h represents the mean value of the heights. Large-scale, low-frequency undulations
of the fabric can occur, so, taking the approach of Ramgulam et al. (1993), two
mean heights and the local roughness based on them are calculated for 4-mm
subdivisions, SMD1 being calculated between 2 and 6 mm and SMD2 between 6
and 10 mm. The lled area in Figure 3 between the mean value and the actual
surface height of the second subdivision represents the numerator of Equation
(1). The results are used later in the section dealing with the dependency of friction
on the surface properties of the fabric.
Three representative engineering materials were chosen for the test surface: alu-
minium as a metallic, lightweight construction material, rubber as a surface used
in grippers and conveyors, and Formica as a typical tabletop material. Details
regarding the roughness of the surfaces can be found in Table 2. Each surface is
in the form of a plate which can be clamped to the moving table described below.

Figure 3 First pro le scan of KC11 along the wale direction
(courtesy of the Textile Institute)



Table 2 Speci cations of the engineering surfaces (Courtesy of the Textile Institute)

Aluminium Formica Rubber

Material 99% pure Natural grade B
Thickness 0.15 mm 0.9 mm
Characteristics Half hard Antistatic
Roughness,a Ra ( m m) 0.243 0.959 0.600
a
The roughness test is performed on a Form Talysurf Series with a diamond-tipped stylus (tip
radius 1.5–2.5 m m) spring-loaded onto the material with a force of 70–100 mgf.

3. Equipment

The apparatus is based on Dreby’s principle (Dreby, 1943) and is shown in
Figure 4. A 10-cm square sample of fabric is placed on a test surface. The sample
is constrained by two light threads connecting it to a static ring whilst the surface
is slid in a controlled manner beneath it. The spring steel ring is of diameter
150 mm and has four single-axis semiconductor strain gauges bonded to it at the
mid-length of the ring. These are connected in a bridge network to a high-gain

Figure 4 Friction-testing equipment


Taylor et al. 21

ampli er mounted immediately below the ring such that a full-scale de ection of
5 g will give an output voltage of 10 V. This signal is connected to a PC via a
12 bit A/D converter, thereby giving a resolution of 1.22 mgf. The computer logs
the data and provides the control signals to the motors moving the test surface.
In these particular experiments the test surface is clamped onto an x–y table with
only the x-axis energized.
The equipment is housed in a room where the temperature can be controlled
to 6 1°C and the humidity to 6 4% r.h. Many of the tests are carried out under
‘standard conditions’. In this paper this means 20 6 1°C and 65 6 4% r.h. Note
that true ‘standard conditions’ as de ned by ASTM, 20 6 2°C and 65 6 2% r.h.
(ASTM D1776–85), require the relative humidity to be more closely controlled. It
is not possible to achieve this tight speci cation in our laboratory but it is found,
in practice, that repeatabilities are very good and experimental curves are smooth
so that this imprecision is deemed acceptable for the tests carried out here. During
the friction tests, the air is ionized with a portable ionizer close to the table to
prevent the fabric samples from becoming electrically charged.
4. Test procedures
In general, every test is carried out six times, each time with a different piece of
fabric cut from adjacent sections of a roll. All fabric samples are preconditioned
by leaving them, technical face upwards, in the controlled environment for at least
1 day. This conditioning period was determined experimentally as described
below in the rst section of results. After conditioning, the mass of the sample
was measured using an electronic balance (Mettler Toledo PB302) having a resol-
ution of 0.01 g. This mass is entered into the computer program along with the
test parameters: table velocity, distance of travel and sampling frequency (75 Hz).
The fabric sample was then connected to the measurement ring with a ne
polyester thread and temporarily rested, measurement face upwards, on the cover
of the ring and its ampli er. Following a command to return the table to its home
position, the fabric sample was placed measurement face down onto the test sur-
face. A short measurement was taken to calibrate the zero level and offset the
weight of the bre attachment, followed by a dwell time of 30 s in accordance
with ASTM D3334–80.
Figure 5 shows a typical friction trace where the ‘friction coef cient’ m i at a given
time is taken as the instantaneous force measured by the ring, divided by the normal
force exerted by the self-weight of the sample. The static friction coef cient, m s, is
taken as the highest peak at the start of the motion and the mean of the peaks and
troughs is taken as an estimation of the dynamic (kinetic) friction coef cient m d.
The discrimination, however, between the static and dynamic friction for low-
pressure tests is not always very clear, especially at higher velocities. The dynamic
friction coef cient is indicated in Figure 5 by the horizontal line through the pulses
of the friction trace and calculated as follows:

O
s

m i
1
m d = (2)
s
where s is the number of samples m i, starting from the static friction reading.


Figure 5 Friction trace for KC11 fabric (wale direction) against
the aluminium surface (courtesy of the Textile Institute). Standard
conditions, velocity = 0.5 mm/s, mass sample = 1.78 g, area of the
sample = 1 dm2, static friction coef cient m s = 0.341, dynamic
friction coef cient m d = 0.339

5. Experimental results

An extensive set of experiments was then carried out to determine the effects on
friction of a number of key parameters: roughness and direction of the fabric, the
morphology of the table on which the fabric rests, the speed of the fabric relative
to the table, triboelectric charge, small applied loads (multiple thicknesses of
fabric) and humidity.

5.1 Effect of fabric surface roughness and direction

The results of Figure 6 show that the smoother the fabric’s surface the higher the
friction coef cient will be. In addition, note that all knitted samples have a higher
friction coef cient than the woven samples.
The linear regression ts (least squares) in Figure 6 indicate the trend between
the friction coef cient and the roughness for both woven and knitted structures.
The results indicate models of the form m d = aSMD + b with a = 2 1.34, b = 0.44
for knitted and a = 2 0.34, b = 0.28 for woven ( SMD = mean roughness). Figure 6


Taylor et al. 23

Figure 6 Scatter plot of dynamic friction for unloaded samples
against aluminium as a function of roughness. Sliding velocity =
1 mm/s (courtesy of the Textile Institute)

also shows that for some fabrics, such as P1 and to a lesser extent KC1, the direc-
tion of movement with respect to the principal direction of the fabric is also sig-
ni cant, whereas for others, such as KC11, C1 and W1, the directionality effects
are negligible.

5.2 Effect of the table surface

Generally, the variation in friction coef cient between fabrics for a given surface
is less pronounced than between fabric–fabric, which can give a variation between
individual materials of up to 160% (Ajayi, 1992). He ascribes this to the smoother
solid surface, which cannot obstruct the movement compared to fabrics where the
yarn crown and ribs can t together when slid across each other. Here, as indicated
in Figure 7, three different sliding surfaces (aluminium, Formica and rubber) have
been used. It can be seen from Figure 7 that the friction for all fabrics in the weft
or course direction is lowest when slid across aluminium, highest against rubber
and intermediate for Formica. Similar results are found in the other fabric direction
(Pollet, 1998) and correspond with recent ndings by other researchers (Yoon
et al., 1984; Ajayi, 1992; Virto and Naik, 1997), who found the same classi cations
for loaded samples according to the sliding material. However, the morphology



Figure 7 Friction coef cients for set 1 fabrics in the weft (course)
direction against different surfaces. Standard conditions, velocity
= 1 mm/s, sample area = 1 dm2

of the sliding surface (see Table 2) does not seem to be directly responsible for
this friction increase.

5.3 Effect of table velocity

Experiments were undertaken to investigate the velocity dependency of dynamic
friction of the fabrics against the test surfaces. A group of six samples was used
for each principal direction. For each group, a velocity was chosen at random,
the tests carried out and a recovery period of 1 day allowed before testing at a
different velocity.
The friction, as displayed in Figure 8, initially decreases with increasing speed,
reaches a minimum, and eventually increases again with increasing speed towards
a constant value, following the distinctive form of the Stribeck curve. Similar
curves are obtained for brous materials (lubricated or clean yarn) and journal
bearings (Hansen and Tabor, 1957; Kalyanaraman, 1988a). Four regimes of lubri-
cation can be distinguished: static friction (velocity independent), boundary lubri-
cation, semi-boundary lubrication at the minimum friction and hydrodynamic
lubrication towards higher speeds.

5.4 Effect of triboelectric charge

Another factor which can in uence the handling behaviour of fabrics is the
presence of triboelectric charge. All the tests now described were carried out under


Taylor et al. 25

Figure 8 Velocity effect on the dynamic friction of KC11 (wale)
sliding against a rubber surface (courtesy of the Textile Institute)

fairly dry atmospheric conditions: 33% r.h. and 21°C. For test 1, all of the unloaded
fabric samples were left on a charged perspex plate for 30 min and then tested
on the aluminium plate as above. Table 3 shows the effect on the static and
dynamic friction coef cients. For Test 2, the samples are left charged for 1 day
before the friction coef cients were measured. Following this, for test 3, the fabrics
were each rubbed 10 times on the aluminium surface. The friction coef cients of
P1 (polyester ) are 0.28 at 33% r.h. when no charge is present so, from Table 3, it
can be seen that they are almost 10 times larger when an electrostatic charge is
present. Note that the electric charge on the fabric will be carried away by water
molecules when they evaporate (Onogi et al., 1996) and so an increase in humidity
will reduce the triboelectric effect.

Table 3 Triboelectric effect on the friction coef cients (33% r.h., 21°C)

KC11 W1 P1

Friction coef cient

Static Dynamic Static Dynamic Static Dynamic

Test 1 0.39 0.34 0.35 0.31 3.60 3.10
Test 2 0.48 0.46 0.41 0.38 4.39 3.90
Test 3 0.52 0.47 0.37 0.34 2.47 2.00



5.5 Effect of fabric pressure

The normal pressure on the fabric samples was slightly increased by adding simi-
lar fabric samples at random on top of the samples under test. The results are
shown in Figure 9, which yields relationships of the form:
Fp = CNn (3)
where Fp is the frictional force, A the area, N the normal force (including self-
weight), and C and n coef cients. This is the same form as proposed by Wilson
(Wilson, 1963). The coef cient n is given by the slope of the characteristic in
Figure 9. The above experiment was repeated for all three sliding surfaces and
both directions. Three clusters can be seen in Figure 10 clearly showing the sur-
face dependency.

5.6 Effect of humidity

Before carrying out an extensive set of experiments for different conditions of
temperature and humidity, it is necessary to determine the length of time the
samples must be left undisturbed in the changed environment so that one can be
sure that they have reached close to steady-state conditions. Experiments were
carried out to determine this and simultaneously nd the time constants of change

Figure 9 Logarithmic relationship between the frictional force
per area (log F/A) and the normal pressure (log N/A) for fabrics
sliding across an aluminium surface. Standard conditions, velocity
= 1 mm/s, aluminium surface, weft or wale direction, sample area
= 1 dm2 (courtesy of the Textile Institute)


Taylor et al. 27

Figure 10 The in uence of the surface type on the Wilson model
coef cients n and C (all fabrics in both principal directions; cour-
tesy of the Textile Institute)

in frictional properties to a step change in humidity. This has practical implications
since it determines the importance of daily or faster changes in the environment.
The speci c test procedure was as follows; an oven-dried specimen at a near zero
humidity was brought into the standard conditioned laboratory, weighed and its
friction tested at time zero. The weighing and testing were then repeated six times
over a 90-min period.
A typical trace is shown in Figure 11 for fabric KC11 which exhibits an
exponential increase in the dynamic friction coef cient following a step increase
in humidity. All other samples show this characteristic, except for the polyester
sample, which is almost hydrophobic, and therefore neither the moisture content
nor the friction changes signi cantly over the 0–65% r.h. range used in this test.
In order to see the effects of humidity on friction, the humidity level in the
laboratory is changed and six samples are allowed to condition for at least 1 day
before the friction tests are carried out. Figure 12 shows the absorption curve for
KC11, tted to the points as the humidity is increased. The desorption points are
also indicated and these are quite close to the absorption points, showing that
there is little hysteresis in this case. The range bars show the maximum variation
across each set of six samples.



Figure 11 Variation of dynamic friction (1 mm/s) for KC11
caused by a sudden humidity change from 0% to 65% r.h.
(courtesy of the Textile Institute)

Figure 12 Dynamic friction of KC11 against an aluminium
surface, as a function of relative humidity


Taylor et al. 29

6. Evaluation

Every factor investigated above has been shown to have a signi cant effect on
the low-force frictional characteristics of fabric samples. Bearing in mind the rela-
tively few samples tested, preliminary evaluations are as follows.
The bre from which the fabric is made seems to have less in uence on the
friction than the type of construction. An example here is the friction coef cient
against an aluminium surface where the lowest coef cient is obtained from the
twill cotton samples, the highest from the double-knit cotton samples. However,
the type of bre becomes crucially important when tribolectric effects are con-
sidered. Here, a 10-fold increase in friction was observed for the polyester sample
in a dry atmosphere, the effect on other samples being much lower. Again, the
type of construction affects the surface pro le and in general the smoother the
surface of the fabric the higher will be the friction coef cient. Anisotropy was
generally not signi cant in the samples tested, apart from P1 and KC1.
Just as the surface pro le of the fabric is crucial, so is the nature of the surface
on which the sample is supported. For all samples, the aluminium surface gave
the lowest friction coef cients, Formica being the next highest and the rubber
surface giving the maximum values in the range of 50–100% higher than the
results for aluminium.
If we now consider handling variables, all fabrics exhibited Stribeck character-
istics of friction against velocity. Four regimes of lubrication can be distinguished:
static friction (velocity independent), boundary lubrication, semi-boundary lubri-
cation at the minimum friction and hydrodynamic lubrication towards higher
speeds. With reference to the velocity effect in yarn–metal friction, the following
hypothesis has been proposed (Kalyanaraman, 1988b). At low speed (boundary
lubrication), the brous materials are supported on their hairs. As the speed is
increased a ‘bristle effect’ lifts the brous material up and reduces the contact area
that in turn decreases the friction. With the speed increasing further, the projecting
surface hairs atten and the contacting surface area increases, contributing to a
rise in friction. In the case of man-made bres, the explanation has to be more
directed towards various lubricating effects. In addition to this hypothesis, air
entrapped between and underneath the bres probably plays an important role.
A typical characteristic showed a range of friction coef cients of 0.49–0.57 (KC11
against rubber). The above results are all for single-thickness samples with zero
normal force applied. When small normal forces are applied by multiplying the
thicknesses of the samples, as would occur in a partially constructed garment, it
is found that the friction force F against weight N characteristics are of the form
found by Wilson (1963) for larger loads, namely Fp = CNn. The coef cients C and
n are, unsurprisingly, also a function of the supporting surface.
Humidity is shown to have a large in uence. Firstly, the friction coef cients
respond exponentially to a step change in humidity, with time constants of 10 min
or so being typical. Not only does this mean that samples should be conditioned
before testing, but also that environmental variations will have a rapid effect on
the handling properties of the fabric. It is seen that a change in relative humidity
from 40% to 80% can double the friction coef cients. The characteristics are non-
linear so a 5% change in relative humidity has a bigger effect at 80% r.h. than



about 50% r.h. When fabrics acquire charge through rubbing in dry conditions,
the triboelectric effect can cause a dramatic 10-fold increase in the friction coef-
cients of the polyester material whereas other fabrics are almost unaffected. Sub-
sequent increases in humidity cause charge dissipation and hence a decrease in
friction for the polyester material. Consequently, the effect of humidity is inextri-
cably linked with the nature of the bres used in the fabric and itself affects the
effect of the fabric becoming electrically charged. Other work (Taylor et al., 1998)
has shown that humidity affects the bending stiffness of fabrics as well as their
frictional characteristics, so humidity is clearly a major factor in variations in hand-
ling properties.

7. Conclusions

One of the main advantages of human operators in a garment factory is their
inherent adaptability to changes in material properties. Humans can pick up and
place a wide variety of fabrics in a large range of environmental conditions, only
having real problems when the temperature is low and we lose the ‘feel’ in our
ngers.
Automated equipment is not so adaptable. From the above studies it is clear
that the ideal situation for the application of automated equipment is to have a
single, well de ned fabric made so that the variation in properties from roll to
roll and along and across the roll are all minimized. Furthermore, the rolls should
be handled carefully from fabric producer to manufacturer and during storage.
Garment production should be in reasonably constant conditions of humidity,
achieved either by judicious location of the factory or by use of air conditioning
equipment. In this way variations in fabric properties and environmental con-
ditions are minimized.
Such care is very much the exception rather than the rule, has associated costs
and is only suitable for those manufacturers with large-scale production of stan-
dard items. The vast majority of manufacturers require equipment to work in very
much less constrained conditions. This is only possible if the equipment is
designed, from the start, to tolerate the changes in process variables. The approach
taken here is to gain knowledge of the variations in the key parameters and
eventually combine these with analytical understanding of the handling. This
forms part of ongoing research. At the moment we are beginning to understand
why equipment fails. The next step will be to apply this knowledge to the design
of more reliable equipment.

Acknowledgement

The authors wish to acknowledge the support of the EPSRC for part of this
work.


Taylor et al. 31

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