CHAPTER 8 RESULTS AND DISCUSSION -...

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CHAPTER 8

RESULTS AND DISCUSSION

8.1 THROUGHPUT TIME COMPARISON

In the existing batch production system,the throughput time for all

the selected products line is too high .On an averagethe throughput time for

men’s T-shirt(product-1) is 6 hours,men’s shirt(Product-2) is 1.5 days,

Knitted men’s bottom (Product-3) is 3 hours and knitted underwear

(Product-4) is 1.5 hours. In the existing layout operators took bundles of cut

panels from cuttingdepartment and stared producing garment parts. The

problem comes when the preparatory sections producesunequal amount of

parts .Due to this reason there is a huge Work In Progress (WIP) in the

product line. But the full finished endproduct quantity is less as compared

with the WIP. In batch production, if everything goeswell, there are no

quality defects, there is no machine breakdown and the operator follows the

bundle sequence properly and it will take minimum 220 to 230minutes for

making the product-1. (Approximately 90 minutes in preparatory and 130

minutes in assembling). Whereas this time is less than an hour in case of

single pieceflow principle as recommended by this study.

On the other hand, strict follow up of ticketing numbers is another

issue in garmentindustry because the garment parts of different ticketing

numbers can be mixed together. In some cases even if allpreparatory sections

(collar, cuff, front and sleeve) produces equal number of parts intheir

respective area but they cannot be used in assembly if they hadn’t followed

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properticketing number.In some cases, the problem appears due to quality

issues or reworks. For example, the operator worksin bundle system and one

bundle consists of approximately 20 to 30 pieces. While checkingthese

bundles if quality checker finds defects even in a single piece, then the

wholebundle will be returned to the concerned operator for correction. This

will lead to unbalanced WIP.

In PBS production system, if there are different styles running in

preparatory and assembly and the quality checker finds some defects after

assembly, then to correct that defect is very difficult task, which increases

cost of quality. During theproduction cycle operators start producing the parts

with their fullefficiency irrespective of the requirement of succeeding

operation. Due to this practice,huge WIP will be created between the

processes, whichindirectly lead to sewing defects. In the production cycle,

identifying the sewing defects are easier if the WIP level is lesser. When

sewing defects minimizes, ultimately the cost of quality will be

minimized.Whereas in the revised lean system follows lesser WIP.

In earlier days the production order quantity per style per color was

high. So mass production system was effective. In present days there are lot

of changes in the production order. For example the SKU levels are keep on

increasing without changing the total order quantity.So frequent product

changeover is unavoidable.But with the support of current production process,

it is very difficult to manage these kinds of requirements .For overcoming

these kinds of issues lean layout is implemented essentially which will

minimize the WIP level.

The snap study is conducted at ABC Ltd.on daily basis for

measuring the throughput time in the current PBS production layout of

product-1, product -2, product- 3, and product- 4 for 10 days .The same

procedure is repeated in the implemented lean layout (Cellular layout) for the

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mentioned product lines.The product wise comparison charts are shown in

Figures 8.1 to 8.4.

Figure 8.1 Comparison of Avg. throughput time between current

layout to lean layout in product -1



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From the above graphs, it is understood that significant amount of

throughput timedifference exists betweenall the garment products from the

PBS production layout to Lean layout.The average throughput time for the

PBS production layout for product-1 is 207minutes, product-2 is 512 minutes,

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product-3 is176 minutes, and product-4 is 82 minutes. But the average

throughput time for the implementedlean layout for product-1 is 10 minutes,

product-2 is 20 minutes, product-3 is15 minutes, and product-4 is

12 minutes.It seems a drastic amount of time difference exists between these

two layouts.So this lean layout production system helps the manufactures to

produce the small order quantity with minimal throughput time.

8.2 COMPARISON OF STANDARD MINUTES VALUE (SMV)

A focused research is done on analyzing Standard minutes value

(SMV) on each productbetween two different layouts.As compared with

current production system the SMV in thelean layout is reduced significantly.

In the lean layout, the reduced SMV has been achieved by merging some of

the operation (as number of operations reduce the individual sewing

allowance for each operation will also be reduced)with other and removing

few of the non-value added activities from the current VSM.For example in

Product-1(Men’s T-Shirt)“front and back matching” and “shoulder joining”

operations are combined, “neck rib join” and “thread cut” are combined, like

wise “back neck elastic tape join” and “top stitch on back neck elastic” are

combined. “Shoulder cut mark” operation is completely removed from the

existing process.

In Product-2(Men’s shirt)the operations like “crease the collar”,

“trim the cuff”,“crease the patch piece”,“top stitch over the shoulder” are

combined with theirsubsequent operations and “crease the collar band” is

removed completely from the existing production system which reduces the

SMV level.

In Product -3(Men’sknitted trouser)“sew side seam panels” and

“top stitch” are merged,“top stitch on front fly”and“sew front and back rise”

are merged,“decorative top stitch making” and “attachment“ are merged,and

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“invert out” and “elastic join” are merged. Because of this merging of

operations, reduction in SMV level is achieved from the current VSM.

In Product -4(knitted under wear),operations like “loading”, “panel

matching” and “trimming” are removed completely from the existing

VSM.“preparation of size label” and “attachment of size label “ are merged,

“attachment of gusset” and “over locking on the gusset” are merged,“close the

right side seam” and “trimming of extra threads” are merged, and “main label

attachment” and “trimming of extra thread on the main label” are merged.

The following graph (Figure 8.5) indicates the level of reduction in

SMV between existing PBS layout to lean layout for all four products.

Figure 8.5 Comparison of SMV between existing layout to lean layout

The above graph shows that because of lean layout there would be

a reduction in SMV about 36.6% from the existing level for Product-1,

13.98% reduction from the existing level for Product-2, 8.9% reduction from

the existing level for Product-3 and 36.25% reduction from the existing level

for Product-4.The SMV reduction is achieved due to combining

fewoperations together, eliminating the non-value added operation,

elimination of bundle allowance and minimizing the personal fatigue

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allowance level from the current VSM. Due to continuous improvement

(Kaizen) in the process we can still minimize the product cycle time.

8.3 COMPARISON OF WIP LEVEL

A focused research is done on analyzing changes in WIP level

between current VSM to revised VSM for all the product line. The researcher

has collected average WIP data for 7 working days during the production. As

compared with current production system the WIP level in revised module is

reduced significantly. In revised system, this has been achieved by combining

the work stations, implementing single piece flow principle,implementing

cellular layout and introduction of multi skilled operators instead of regular

operator,removal of few of the non-value added activities in the revised value

stream mapping etc..The following graph (Figure 8.6) indicates the

comparison of WIP level between current VSM to revised VSM for all the

product line. For product-1 the average WIP level is 19 and 2.5,for product-2

the average WIP level is 19.5 and 3.8, for the product-3 the average WIP level

is 20.8 and 4.6 andfor product-4 the average WIP level is 18.5 and 5.

Figure 8.6 Comparison of Avg. WIP level between current VSM to

revised VSM

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This data shows that there would be higher level of reduction in

WIP from current VSM.This would support the manufacturer to minimize the

production cost particularly for short run orders.

8.4 COMPARISON OF NUMBER OF OPERATIONS

The number of operations required to complete a garment is

reduced in all the garment products from the current VSM to revised

VSM.Those operations which do not add any value to the garment are

eliminated and some of the operationsare combined together in such a way so

as to minimize the SMV level. The following graph (Figure 8.7) shows the

number of operationsin existing layout and revised layout.

Figure 8.7 Comparison of number of operation between existing layout

to lean layout

From the above graphs it is understood that there would be a

significant level of reduction in number of operations involved in the

production process between the current VSM to revised VSM.In current VSM

the number of operations of Product-1, product-2, product-3 and product-4 are

29, 41, 21, 16 respectively.In revised VSM the number of operations of product-

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1, product-2, product-3, and product-4 are16, 37,17,8 respectively. This reduced

number of operations in revised VSM supports the manufacturer to minimize the

operator allocation and space reduction from the current VSM.

8.5 COMPARISON OFNUMBER OF OPERATORS

In case of batch production, there used to be one operator in each

machine and one additional person who can work at least in two to three

operations for balancing the flow called floaters. The job of this extra operator

(floater) is to support in critical operations and minimize operational

bottlenecks. In addition to that,helpers will be there for WIP movement

whereasthe automatic WIP conveyors are not available.As per the Lean

principle the number of operators in cellular layout will be lesser than the

number of work stations, which means each operator is responsible for more

than one work stations.Since there won’t any bundle movement in the cellular

layout, there won’t be any bundle handling allowancein the revised VSM.

Whereas in the case of single piece flow the operators are allocated as per

standard minute value (SMV) in each cell and they will balance the work

according to their need. In addition to that, the rotation of operators is defined

by the SAM and situation of WIP.

In PBS layout, the machine operators who complete their targets

cannot extend their support for othersbottleneck operations. Even though they

are idle, there is no mechanism available to engage them. Due to this situation

there will be an unexpected fluctuation in WIP level.But in lean layout, the

operators who finish their task are advised to share the work load of others.

The work ergonomics also supports this scenario in such a way that each team

will be given one or two additional machines for these kinds of activities.

Since productivity is measured in terms of team efficiency instead individual

efficiency (unlike in current VSM), the work load will be shared

automatically in lean layout.

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The following graph (Figure 8.8) indicatecomparative study of

operator’s allocation for the production of 100 pieces per hour in all product

lines (Product-1, Product-2, Product-3 and Producst-4) between the current

VSM and revised VSM.

Figure 8.8 Comparison of number of operator between existing layout

to lean layout

In the Lean layout, for producing 100 pieces per hour , man power

reduction from the current layout for Product-1(Men’s T.Shirt) is 38%,

Product-2(Men’s woven shirt) is 52%, Product-3(knitted bottom) is 23.5%

and for Product -4(under wear) is 55%.The number of operators needed to

complete a job is reduced by eliminating non-value added operation from the

existing production layout. Similarly there is no need of quality checkers after

each section, because quality checkers cannot control the quality of work

performed before checking. In the current layout, quality checkers are

working as the postmen; they can givefeedback about the produced parts but

cannot add any value to the product. In case of lean layout the operators are

communicated about the required quality standards and specification. In this

way if the operator has any confusion or problem during production, he/(she

should clear it before working on it. This helps to minimize the rework level,

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which ultimately increase productivity. In addition to that, because of reduced

WIP level in lean layout, helpers count also reduced.

8.6 COMPARISON OF PRODUCT DEFECT LEVEL DUE TO 5S

TOOL

As mentioned in the methodology chapter, the 5S tool has been

implemented in lean layout. After implementation of 5s tool the researcher

analyzed whether 5s tool minimized the defect level in lean layout, since most

of the products defects are due to improper work ergonomics and work place

management .To analyze this, the researcher selected two product lines such

as Product-1 and Product-3. Product defects rate (an average of 10 reading)

has been recorded for a weeks time without 5s implementation. The same

defects rate has been recorded with 5s implementation for the same duration.

The differences between the recorded defects are analyzed through T Test

statistically.

Table 8.1 Analysis of defect reduction due to 5S tool for product-1

S.No

Average sewing defects level per 100 pcs without

5S implementation

Average sewing defects level per 100 pcs with 5SImplementation

1 7.0 4.02 12.0 2.03 9.0 4.04 6.0 4.05 8.0 5.06 9.0 2.07 11.0 6.08 9.0 4.09 9.0 5.0

10 11.0 4.0

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The above table stats that the 5S implementation reduced the defect

level. To authenticate the result the researcher has adopted “T.Test” in the

research.

Table 8.2 T-test output-group statistics

5s Tool N Mean Std. Deviation

Std. Error Mean

Garment defect/100 pcs

before 5s 10 9.1000 1.85293 .58595After 5s 10 4.0000 1.24722 .39441

Table 8.3 Independent samples test

Levene's Test

for Equality of

Variances

t-test for Equality of Means

F Sig. T dfSig.

(2-tailed)

Mean

Difference

Std.

Error

Differenc

e

95% Confidence

Interval of the

Difference

Lower Upper

Garment

defect/100

pcs

Equal

variances

assumed

1.277 .273 7.221 18 .000 5.10000 .70632 3.61608 6.58392

Equal

variances not

assumed

7.221 15.766 .000 5.10000 .70632 3.60086 6.59914

The first table 8.2 stats that the mean defect level for 100 pcs

without 5s implementation is 9.1 with a standard deviation of 1.85 and with

5s implementation it is 4.0 with a standard deviation of 1.15.

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The second Table 8.3 gives the t value with degree of freedom,

significance level and 95% confidence interval for the mean .The significance

value is 0.00(p value), which is lesser than 0.05(alpha). Therefore, we reject

the null hypothesis and the conclusion is defect level with 5s implementation

is lesser than without 5s implementation.

Table 8.4 Analysis of defect reduction due to 5s tool for product-3

S.No

Average sewing defects level per 100 pcs without 5s

implementation

Average sewing defects level per 100 pcs with 5s Implementation

1 12.0 2.0

2 11.0 4.0

3 14.0 3.0

4 10.0 3.0

5 12.0 5.0

6 14.0 2.0

7 9.0 3.0

8 12.0 4.0

9 13.0 2.0

10 9.0 3.0

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Table 8.5 T-Test output-group statistics

5s Tool N MeanStd.

Deviation Std. Error

MeanGarment

defect/100 pcs before 5s 10 11.6000 1.83787 .58119

After 5s 10 3.1000 .99443 .31447


Levene's Test for Equality of Variances


F Sig. T DfSig. (2-

tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the

Difference

Lower Upper

Garment defect/100 pcs

Equal variances assumed

4.135 .057 12.863 18 .000 8.50000 .66081 7.11169 9.88831

Equal variances not assumed

12.863 13.854 .000 8.50000 .66081 7.08130 9.91870

The first Table 8.5 stats that the mean defect level for 100 pcs

without 5s implementation is 11.6 with a standard deviation of 1.83 and with

5s implementation it is 3.1 with a standard deviation of 0.99.

The second Table 8.6, gives the t value with degree of freedom,


value is 0.00(p value) ,which is lesser than 0.05(alpha). Therefore, we reject

the null hypothesis and the conclusion is defect level with 5s implementation

is lesser than without 5s implementation.

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8.7 ANALYSIS OF PRODUCTIVITY IMPROVEMENT DUE TO

KAIZEN IMPLEMENTATION

As mentioned in the methodology chapter, the Kaizen tool has been

implemented in the form of work aid introduction and method modification in

lean layout.After implementationof Kaizen tool the researcher analyzed

whether the kaizen tool has minimized the production cycle time in the lean

layout.To analyze this, the researcher has selected two product lines such as

Product-1 and Product-4. Without kaizen implementation the production data

has been recorded for a week. With Kaizen implementation the production

data of each module has been collected once in a week for 3 subsequent

weeks from the date of implementation of Kaizen. The differences between

the recorded data have been analyzed to identify the reduction of production

cycle time due toKaizen implementation.

Table 8.7 Analysis of hourly production improvement due to Kaizen

tool for product-1

S.No Week1(Qty) Week3(Qty) 1 265.0 280.0

2 258.0 291.0

3 246.0 277.0

4 263.0 293.0

5 248.0 288.0

6 254.0 286.0

7 261.0 292.0

8 251.0 290.0

9 261.0 285.0

10 267.0 274.0

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The Table 8.7 stats that the hourly production has improved from

week1 to week 3 due to kaizen tool. To authenticate the result the researcher

has adopted “T.Test” in the research.

Table 8.8 Output -group statistics

week N Mean Std. Deviation

Std. Error Mean

hourlyproduction

week1 10 257 7.29079 2.30555

Week3 10 285 6.58618 2.08273

Table 8.9 Independent Samples Test

Levene's

Test for

Equality of

Variances


F Sig. T Df Sig. (2-

tailed)

Mean

Difference

Std. Error

Difference


Difference

Lower Upper

hourly

production

Equal

variances

assumed

.295 .594 -9.076 18 .000 -28.20000 3.10698 -34.72753 -21.67247

Equal

variances

not

assumed

-9.076 17.817 .000 -28.20000 3.10698 -34.73233 -21.66767

The first Table 8.8 stats that the mean hourly production per hour in

week 1 is 257 with the standard deviation of 7.29 and in mean hourly

production per hour in week 3 is 285 with a standard deviation of 6.58.

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The second Table 8.9, gives the t value with degree of freedom,


value is 0.00(p value) ,which is lesser than 0.05(alpha).Therefore ,we reject

the null hypothesis and the conclusion is Hourly production in week 3 is

higher than week 1.

Table 8.10 Analysis of hourly production improvement due to Kaizen

tool for product-4

S.No-1 Week1(Qty) Week3(Qty)

1 185.0 200.0

2 190.0 212.0

3 188.0 223.0

4 175.0 212.0

5 178.0 207.0

6 189.0 207.0

7 182.0 214.0

8 175.0 200.0

9 178.0 210.0

10 180.0 220.0

The first Table 8.10 states that the hourly production has improved

from week1 to week 3 due to kaizen tool. To authenticate the result the

researcher has adopted “T.Test” in the research.

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Table 8.11 Output-Group Statistics

week N MeanStd.

Deviation Std. Error

Mean

hourlyproduction

week 1 10 182 5.69600 1.80123

week 3 10 210.5 7.51665 2.37697


Levene's Test for

Equality of Variances


F Sig. t Df Sig. (2-

tailed)

MeanDifference

Std. Error Difference


Difference

Lower Upper

hourly production

Equal variances assumed

.297 .592 -9.556 18 .000 -28.50000 2.98236 -34.76570 -22.23430

Equal variances not assumed

-9.556 16.773 .000 -28.50000 2.98236 -34.79871 -22.20129

The first table 8.11 states that the mean hourly production per hour

in week 1 is 182 with the standard deviation of 5.6 and in mean hourly

production per hour in week 3 is 210.5 with a standard deviation of 7.5.

The second table 8.12, gives the t value with degree of freedom,


value is 0.00(p value), which is lesser than 0.05(alpha). Therefore, the null

hypothesis is rejected and the conclusion is hourly production in week 3 is

higher than week1.

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From the above analysis, it is understood that the Kaizen tool has

done remarkable improvement in the production efficiency for product-1 and

product-4.

8.8 COMPARISON OF STYLE CHANGE OVER TIME

The researcher believed that the lean layout will reduce the

changeover time. So an investigation of changeover time comparison between

the current layout andlean layout has been done. For that the researcher has

chosen Product-1 as well as Product-2 production layout. In Lean layout the

product-2(men’s shirt)is replaced by new woven men’s top (Casual shirt). The

production setting time for this replacement is analyzed in minutes. The same

replacement procedure is done on the current PBS layout.

In the same way, in Lean layout the product-1(crew neck T-Shirt) is

replaced by new polo T-Shirt. The production setting time for this

replacement is analyzed in minutes. The same replacement procedure is done

on the current PBS layout.

Figure 8.9 Comparison of change over time between current layout to

revised layout

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The statistics in the graph above indicates that there is a significant

amount of changeover time reduction in lean layout from current PBS layout.

In lean layout there is a 42% of reduction in changeover time in Product-1 and

41% of reduction in Product-2.

8.9 ANALYSIS OF SEWING MACHINE PERFORMANCE DUE

TO TPM IMPLEMENTATION

As mentioned in the methodology chapter, the TPM tool has been

implemented in selected lean layout.The researcher is interested to find the

influence of TPM on performance efficiency of the sewing machine. So four

machines from three modules of Product-1 are taken for this study. The

average break down of sewing machine per day due to maintenance related

problems areanalyzed before implementing TPM tool. With the average break

down data, the performance efficiency of the sewing machine is calculated.

The same performance efficiency of the sewing machine is calculated after

TPM tool implementation. Both the calculated data are plotted in the

following graph.

Figure 8.10 Influence of TPM tool on performance efficiency of the

sewing machine

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The statistics in the graph above indicates that the influence of

TPM tool has significantly increases the sewing machine performance in all

the cases.Because of the TPM tool implementation, the operator gets

additional skills of troubleshooting of sewing machines, basic maintenance

and lubrication. Due to this the operator will not expect help from

maintenance team which reduces the sewing machine idle time significantly,

whereas the actual maintenance team will be involved in other development

tasks.

8.10 ANALYSIS OF INTERACTION EFFECT OF KAIZEN AND

TPM ON LEAD TIME

The researcher has analyzed the interaction effect of TPM and

Kaizen on lead time reduction at Cellular layout .The study is conducted for

analyzing production lead time for making 100 pieces of product -2 garments.

Two way ANOVA tool is utilized to study the same. For that ,two level of

experiment is executed and for each level combination the experiment is

replicated five times. The following tables indicate the details of experiment

Table 8.13 Interaction effect of Kaizen and TPM on lead time Product-2

Production lead time for 100 pcs of garment

Without TPM With TPM

Without Kaizen 55,58,55,49,51 31,28,33,29,30

With Kaizen 32,29,32,34,29 20,18,19,22,25

The tests Hypotheses are as follows

Ho: There is no interaction effect between TPM and Kaizen on Lead

time

H1: Interaction effect is exist between TPM and Kaizen on Lead time

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Between-Subjects Factors

Value Label N

Kaizen 1 Without 10

2 With 10

TPM 1 Without 10

2 With 10

Table 8.14 Tests of between-subjects effects

Dependent Variable:Lead time for 100 pcs production

Source Type III Sum of

Squares df Mean Square F Sig.

CorrectedModel

2903.350a 3 967.783 133.949 .000

Intercept 23052.050 1 23052.050 3.191E3 .000

Kaizen 1428.050 1 1428.050 197.654 .000

TPM 1264.050 1 1264.050 174.955 .000

Kaizen * TPM 211.250 1 211.250 29.239 .000

Error 115.600 16 7.225

Total 26071.000 20

CorrectedTotal

3018.950 19

a. R Squared = .962 (Adjusted R Squared = .955)

The output (Table 8.14) states that the F value against Kaizen,TPM

and Kaizen*TPM is 197,174 and 29.23 respectively and the significance (p

value) is 0.000 in all the cases. Since the p value is less than 0.01, it is

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concluded that Kaizen tool implementation on lead time for making 100 pcs is

significant. Similarly with TPM tool implementation on lead time for making

100 pcs is significant. The interactive influence of Kaizen and TPM on lead

time for making 100 pcs is also significant. So it is umderstood that the

interaction effect exists between TPM and Kaizen on Lead time for making

100 pcs of garments.

The above said similar experiment is repeated for Product -4 also.

Table 8.15 Interaction effect of Kaizen and TPM on Lead time product-4

Production lead time for 100 pcs of garment

Without TPM With TPM

Without Kaizen 45,47,51,48,52 32,29,29,31,30

With Kaizen 35,32,33,31,30 18,21,20,29,22

The tests Hypotheses are as follows

Ho: There is no interaction effect between TPM and Kaizen on Lead

time

H1: Interaction effect is exist between TPM and Kaizen on Lead time

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Table 8.16 Tests of between-subjects effects

Dependent Variable: Lead time for 100 pcs production

Source Type III Sum of Squares

dfMean

Square F Sig.

CorrectedModel

1862.950a 3 620.983 79.613 .000

Intercept 22111.250 1 22111.250 2.835E3 .000

Kaizen 1022.450 1 1022.450 131.083 .000

TPM 756.450 1 756.450 96.981 .000

Kaizen * TPM 84.050 1 84.050 10.776 .005

Error 124.800 16 7.800

Total 24099.000 20

CorrectedTotal

1987.750 19

a. R Squared = .937 (Adjusted R Squared = .925)

The output indicates, that the F value against Kaizen, TPM and

Kaizen*TPM is 131,96.98 and 10.776 respectively and the significance

(p value) is 0.000 in all the cases. Since the p value is less than 0.01, it is

concluded that with kaizen tool implementation on lead time for making

100 pcs is significant .Similarly with TPM tool implementation on lead time

for making 100 pcs is significant. The interactive influence of Kaizen and

TPM on lead time for making 100 pcs is also significant.So it is understood

that the interaction effect exists between TPM and Kaizen on Lead time for

making 100 pcs of garments.

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8.11 COMPARISON OF INTERNAL TRANSPORTATION

In garment industry one of the crucial activities is internal

transportation. Basically improper internal transportation will lead to delay in

material flow between the cutting section to sewing section. After extreme

brain storming it was found that the material flow line contains various non-

value added activities at ABC in the current VSM.In general fabric will

besupplied from the fabric store and the fabric store should be maintained in

the central place of the factory. But in most of the factories including ABC,

this fabric store is kept completely away from the production floor .There is

no modern fabric storage devices availableto store the fabric effectively. This

in turn affects the fabric internal transportation. The Figure 8.11 shows the

current map of process layout from cutting section to sewing section.

In general the fabric from fabric store will be transferred to the

cutting section, then numbering and then bundling section. In ABC, the

distance between the fabric cutting sections to numbering section is 20ft and

the numbering section to sewing section is 20 ft. All together fabric from

cutting section to sewing section will have a distance of 40 ft.

For transporting 100 Pieces of fabric in the existing layout =30 sec

Loading & unloading time=40 sec

Totally 70 sec is taken for transferring 100 Pcs of fabric from

cutting section to sewing section.

Total No of pieces to be produced for 10 days with the

Current VSM layout is = (59,000/100)*70=41300 Sec

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Figure 8.11 Internal transport distance between cutting to sewing

section in current VSM

For overcoming improper internal transportation in garment

industry, Pilot Lean layout model has been createdfrom cutting section to

sewing section. In this model, two cutting sections are created and the fabric

store is placed in between these two cutting section, which enables the cut

panels quickly reach the sewing section without any problem.

In addition to that the time to travel from cutting section to sewing

section is minimized to 15 sec.The following Figure 8.12 depicts the above

mentioned lean layout

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Figure 8.12 Pilot lean layout for internal transportation

For taking 100 pcs of fabric in the existing layout=15 sec

Loading & unloading time=40 sec

Total 55 sec for transferring 100 Pieces of fabric from cutting

section to sewing section.

Total No of pieces to be produced for 10 days with the

Lean layout is = (59,000/100)*55=32450 sec.

The following graph indicates the comparison of time taken for

internal transportation in current VSM and revised VSM.

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Figure 8.13 Comparison of material movement between current VSM to

Revised VSM

8.12 COMPARISON OF MATERIAL MOVEMENT WITHIN

SEWING LINE

In addition to the comparative study on internal transportation

between the cutting section to sewing section in both the layouts, the

researcher is interested to investigatethe material movement within the sewing

department before and after implementation of lean production system.For

that the researcher has taken 10 different reading on the internal movement of

material within sewing department before and after lean implementation.

Since the number of machines has been reduced from the current

VSM to revised VSM, the transportation of material movement between the

machines is also reduced significantly. The following chart indicates the

difference graphically.

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Figure 8.14 Comparison of product wise material movement between

current and revised VSM

8.13 COMPARISON OF OPERATOR SKILL LEVEL

IMPROVEMENT

Skill matrix will define the capacity level of each operator skills

against various operations. In current VSM, on an average each operator has

skills on 1 to 2 operations, but in the revised VSM, on an average each

operator has skills on 4 to 5 operations which is technically defined as “multi

skilling”. The following Figure depicts the differences in skill level between

current and revised VSM .

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Figure 8.15 Operator skill level comparison between existing VSM to

revised VSM in product -1



195

Figure 8.17 Operator skill level comparison between existing VSM to revised VSM in product -3



The above graphs indicate that revised layout has significantly

increases the operator’s skill level. The average skill level of an operator in

the revised lean layout is around 5 as compared with 1 or 2 in the existing

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layout. Due to multi skilling, there are so many improvements such as

Optimization in the material flow and Operator getting co-operator support

during back logging.

8.14 COMPARISON OF PROCESS RATIO

A comparative analysis is carried out towards the process ratio

between current VSM to future state VSM (Lean layout). The process ratio is

the difference between the value added time to total process time. In the lean

layout, non-value added activities are removed larger extend by merging

some of the operation (as number of operations reduced the individual sewing

allowance for each operation will also be reduced) with other, removing few

of the non-value added activities from the current VSM, and implementation

of kaizen, TPM and 5s tools have reduced the non-value added activities still

further.

The following graph (Figure 8.19) indicates the comparison of

process ratio between the all the selected products line.

Figure 8.19 Comparsion of process ratio

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As compared with current production system the process ratio has

increased in revised system such as, In product -1 the process ratio has

increased 4.64 times from the current VSM, Product -2 process ratio

increased 6.2 times, in product -3 the process ratio increased 4.5 times from

the current level, in product -4 process ratio has increased 3.5 times from the

current level..

8.15 COMPARISON OF INFORMATION FLOW

In existing layout the production line is very long, starting from

preparatory to the end of assembly. Because of this, communication and

information flow is difficult and for each and every thing supervisor has to

walk around the line frequently. In case of new layout (cellular layout) the

information flow is effective and quick. Because, the group of people who are

in the same cell, works in compact area where each operator is indirect

contact with other operator of the cell and they know each other’s job inside

the cell. This makes information flow fast and accurate. Whereas this cannot

be achieved in long PBS layout; where one operator is in contact with only

two operators (one operator before and one operator after his operation) so

neither he can give any suggestion nor he knows the issues of other operation

i.e. workers are not participating in each other’s work, rather working

independently.

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8.16 OPERATOR MOTIVATION

In new layout, operators are motivated because all operators are working in multiple operations in rotation. So there is no arguing that someone is doing a difficult operation and others are working in easier operations. On the other hand, this is not possible in batch production because of specific allocated work for the whole day. Similarly, in case of new layout, operators are treated as a group inside the cell so their combined effort is to do better and produce more. Likewise, operators cannot work carelessly because they will be immediately caught by the next operator inside the cell, so the combined result of all these factors motivates them to do better in each step.

8.17 SUMMARY

In this chapter comparison of various process parameters are analyzed before as well as after implementation of lean tools in the selected product line. The comparison parameters are throughput time, SMV, WIP level, number of operator requirement for producing same quantity of garment,style changeover time, product defect level,product lead time,materialmovement,processratio,etc.

After implementation of lean tools, results observed are highly encouraging. The production cycle time decreased by 35% for T.Shirt and 14% decreased in men’s woven shirt. WIP level reduced by 86% for T.Shirt, 80% for men’s woven shirt and 77% for knitted trousers. Number of operatorsrequired to produce equal amount of garment decreased by 41% for T.Shirt, 30% for men’s Shirt and 23% for knitted trousers. Rework levelreduced by 50% for T.Shirt and 70% for knitted trousers. Style change over time has reduced by 57% for T.Shirt and 50 % for men’s shirt. Average machine down time reduced by 83% from the existing level due to implementation TPM tool and other positive improvements are gained due to the lean tool implementation

CHAPTER 8 RESULTS AND DISCUSSION -...

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