Fabric Defects Cotton Mix

8/3/2019 Fabric Defects Cotton Mix

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A Fabric Defect is any abnormality in the Fabricthat hinders its acceptability by the consumer

A Fabric that exhibits a consistentPerformance

Within the boundaries of human use & humanview

A Fabric that exhibits a consistent AppearanceWithin the human sight boundaries

What is a Fabric Defect?

What is a Defect-Free Fabric?

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Machine-Related Factors:

Failure of spinning preparation to eliminate or minimize shortand long-term variation

Failure of opening and cleaning machines to completelyeliminate contaminants and trash particles

Failure of the mixing machinery to provide a homogenous blend Excessive machine stops particularly during spinning Excessive ends piecing during spinning preparation Poor maintenance and housekeeping

Weaving-related defects Knitting-related defects Dyeing and Finishing-related defects

What are the Factors that could lead to

Fabric Defects?

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Material-Related Factors:

Fiber contaminants Excessive neps and seedcoat fragments Excessive short fiber content Excessive trash content High variabil ity between and w ithin-mix Clusters of unfavorable fiber characteristics Weight variation Tw ist variation

Excessive Hairiness

What are the Factors that could lead to

Fabric Defects?

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At Auburn University Testing Laboratory, we have a very sound

sample analysis program in which we perform systematic Fabric& Yarn defect-diagnostic analysis and provide complete reports.

Our laboratory has state-of-the-art Testing and Diagnosticsystems including optical and scanning M icroscopic systems,and all advanced physical & chemical testing techniques offibers, yarns, and fabrics.

Since 1989, we have handled over 3000 disputes for over 28

companies with a feedback rate down to few hours dependingon the case in hand.

Now , we have a Diagnostic-Expert Software program which assist

in speeding up diagnostic fabric defects analysis using a largeimage-base & an image-recognition & comparison system.

Examples from the image-base bank we have are shown below

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Fabric Barr

Material or machine related

Mixing is often a prime suspect

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Fabric Barr

Raw-Material

Excessive Between-Mix Variatio

in Fiber Fineness

Excessive Within-Mix Variationin Fiber Fineness

Excessive Between-Mix Variation

in Color +b or Rd

Excessive Within-Mix Variation

in Color +b or Rd

Yarn

High CountVariation

High Twist

Variation

High Hairiness

Variation

Mixing Fresh

with Stored YarnsHigh Yarn

Irregularity

& Imperfection

Knitting

ImproperStitch Length

Improper

Feed Tension (knitting)

Variation in Fabric

Take-up from loose

to tight

Excessive Lint

Build-Up

Worn*Needles

Double-Feed

End

Weaving

Uneven Warp

Tension

Uneven Let-Off or

Take-up Motion

Uneven Filling

Tension

Different Causes of Fabric Barre

[ * usually produce length direction streaks]

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Shade Variation

Material or machine related

Dyeing & Finishing

Mixing is often a suspect

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Synthetic Fiber Contaminant

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White Specs

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Small Bits of contaminants Spun into the Yarn

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Fill ing Streaks &Slubs of Varying

Lengths

Weak Spots(Over-bleaching)

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8 cm

d~2d

Short Thick Places

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>> 40 cm (16 inch)

d

~40% to 100% of d

Long Thick P laces

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Spun-in or knit-inContaminant?

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Modeling Fabric Defects: The Problem-Theory

Fabric Defect =f (macroscopic parameters, microscopic parameters, noise parameters)

Fabric Defect = f (MaPs, M iP s, Noise)

MaP =f (visual illusion, physical reflection, gross parameters)

MiP =

f(w ithin-yarn variation, clustering effects, colorbreakdown failure)

Noise =

f (Unknown Parameters, informat ion resolution loss)

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The Textile Process Does not Eliminate Variability.Indeed, it is quite the opposite. As materials flow from one stageof processing to another, components of variability are added and

the final product involves a cumulative variability that is muchhigher than the variability of the input fibers.

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The Textile Product is Positively Deceiving.The main reason, the consumer does not realize the largemagnitude of variability in the final product (fabric or garment)

is that the different components of variability have beensmoothed during processing to produce a product that exhibitsa pattern of Consistent Variability at the naked-eye visual

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Poor Cotton Mixing is a Sure Defect-CausingFactor & Good Mixing alone Does not AlwaysGuarantee a Defect-Free Fabric

Machine-Related Factors cannot be emphasized enough

99% of Fabric-Defects can be diagnosed withminimum or no testing if every involved personnel

from the fiber to the fabric sector is willing to honestlytells his/her side of the story.Fabric-defect diagnostic work has become more of detective

work because of missing facts

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When business is good, fabric defects arenormally at their lowest rate Coincident!!

In the absence of a well-established problem

theory, in which backward projection of fabricquality is the foundation, fabric defects of thesame type will always re-occur.

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Current yarn testing techniques reveal minimumor no information about potential causes of

Fabric defects.It is truly disturbing that high cost yarn testing equipments available todayreveal minimum or no prediction of potential fabric defects. Indeed, thereis a significant gap between yarn quality as tested in the yarn raw formand corresponding yarn quality as it exists in the fabric. For instance, the50 cm yarn length used to test yarn strength often proves no correlationwith fabric strength or weaving performance. The capacitive mass variationmeasures often prove meaningless with respect to fabric weight variation.

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Micronaire


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BalePopulation

Cotton Mixes

BaleLayd

own

xTime

Upper Control Limit

Center Line

Lower Control Limit

ProcessAverage

x

Out ofcontrol

MicronaireColor +b

Short Fibers

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Micronaire


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Cotton Mixes

BaleLayd

own

x

MicronaireColor +b

Short Fibers

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Between-Mix Pattern

Run

RunTrend

Trend

Trend

Between-Mix Runs or Trends58


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Bale


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Cotton Mixes

R

Tim

e

R1

R2

R3

R4

R5

BalePopulation

Rp

Time

P

rocessRang

e(R) Upper Control Limit

Center Line

Lower Control Limit

Micronaire

Short FibersColor

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Macro-SectionsMicro-Sections

>> FL

A fiber strand that has approx imately zero variabilitybetween consecutive macro-sections and a variabilityof micro-sections that perfectly reflects the naturalvariability in the constituent fibers of the input fiber

mix

Ideally-B lended Fiber Strand: Definition

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The Dimensional Allocationof Different Fiber Segments

w ithin the Structural Boundariesof the Fibrous Assembly

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i j M icro i j

i j M ac ro i j

R

R

P F F F L M ic ro S

P F F F L M a c ro S

=

=

{ / }&

{ / }

where Rij is the representation factor of a certain fineness/length combination in the

micro-section or macro-section of fiber strand.

The Representation Factor

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Th Cl t i Eff t


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n

C n q=

n = The standard deviation of the No. of fibers/ CsC = the average number of fiber ends per clusterP = 1-q = n/ nmax

The Clustering Effect

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3.5

4

4.5

5

Mic

0.95

11.05

1.11.15

FL

0.006

0.006

0.007

0.0070.008

0.008

0.009

0.009

0.01

0.01

0.011

0.011

0.012

0.012

0.013

0.013

0.014

0.014

P

(Macro)

P(Macro)

Relationship Between the Probability of Representation of Fibers ofMic/FL Combination in the Macro-Section of Yarn [Ne = 20s]

P(Macro) = 0.016014+ 0.0665027/Mic+ 0.0113814/FL

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0

0.05

0.1

0.15

0.2

0.25

C11

C12

C13

C21

C22

C23

C31

C32

C33

Cshort

Fineness/Length Category

P{Ffi/FLjITuft}

120%

Comparison Between Probabilities of Representation in Micro-Sections and

Macro-Sections of Fiber Strand [Yarn]

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A (Vi l) Bl di


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Appearance (Visual) Blending:

The Homogenization of Different

Fiber Colors in the Fiber Assembly

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ij M icro i

ij M ac ro i

R P b M icro S

R P b M acro S

= +

= +

{ ( ) }

&

{( ) }

1

1

The Representation FactorOf Color

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The Representation Factor


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Intimate

Blending

Draw

Blending

% Black Fibers

PercentageNo.in

YarnCross-Sections

PercentageNo.in

YarnCross-Sections

% Black Fibers

p

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Clusters of Similar Color

Fibers


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They Undergo Changes During Processing

They embed in the fiber bulk verycleverly and manage to survive

They cluster

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ference

Mic DifferenceSFCD

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Threshold Values of Betw een-Mix Variability

FS Difference

FE%Differen

ce

FLDiffe

r

+b Difference

Neps/g

Difference

VFM

Difference

1.2 2 3

1

2

3

0

.04

0.05

0.1

200 100 50

3

%2%

1%

0.1

0.2

0

.5

1

2

3

UV Range

3.0

2.0

1.0 2 5

6

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C.V% Mic

10

12

FL

Max.S


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Threshold Values of Within-M ix Variability

C.V% FS

C.V%FE

C.V%

FL

C.V% +b

Neps/g

VFM

SFCw

3 5 7 9 11 13

4

56

7

89

2

3

4

5

6

6.0

4.0

3.0

1.0

0.5

400 200 100

1412 10

8

6

4

2

4

6

8

10

12

UV Range

10 15

20

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Closing Remarks


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Every defect should not be treated only as a passing loss, but more importantlyas an opportunity to learn more about the root causes of the defect.

As many defects as we see on daily basis we often focus on the effect and

overlook the root causes

The traditional approach of dealing with quality problems passively unless asignificant cost is encountered should give way to more intelligent approaches

in which problem prevention in the first place is the key factor

Current yarn testing techniques are based on traditional thinking and they

reveal virtually no indication of potential fabric defects. New approaches toyarn testing based on fresh innovative thinking should be introduced

When the same type of defects reoccur once, it is perhaps because we failed to

discover the root causes the first time. When the same defect reoccurs

100 times, our intelligence becomes largely in question In the era of SIX SIGMA, you can either lead, follow closely or get out

out of the track Defects are not only about cost or loss, they are more

importantly about customer trust and confidence

Yehia El Mogahzy

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Fabric Defects Cotton Mix