Food

1. PRESENTED BY:
POONAM SHARMA
112679
B Sc Fashion Technology
Lovely Professional University
PRESENTATION
ON
REDUCTION IN DHU IN SEWING LINE
IN
SARASH IMPLEX PVT. LTD.

2. INTRODUTION OF THE COMPANY:
 COMPANY PROFILE: Established in the year 1969, SARASH IMPLEX PVT. LTD. An apparel manufacturing
industry which is on the path of becoming one of the leading manufacturers, suppliers and exporters of
garments. Company comprises 527 stitching machines in production as well as sampling department
giving a monthly output of nearly 600 sampling production. Presently, 1700 employees are working in the
company as a team to achieve the goal of becoming leading manufacturer, supplier and exporter and to
win tough market competition.
 BUSINESS TYPE: exporters, manufacturers and suppliers
 PRODUCTS : The products exported by the company are ladies fashion accessories, bags, embroidered shoes, artificial
jewellery and ladies garments. The garments exported by the company are dresses, blouses, tops, t-shirts, bottom wear
including trousers, pants, lowers, skirts, beach wear, , scarves, kurtas, wrapping skirts, stoles, paroes, and triangles.
 CLIENTS: miss monella, zabroske, mavi moda, visk swim wear, odel, gulfmysore, minmi,
LIFESTYLE, ankita khan, stedi jaipur,HG collection
 ANNUAL TURNOVER: The annual turnover of the company is 4 crore approx.
INTRODUCTION

3. In the apparel industry the quality is the main factor. In quality there is mainly focus on DHU %. DHU %
means the Defects per Hundred Units. The project is related to defects due to sewing. These problems
occur in garment process line due to sewing and also due to fabric during fabric manufacturing as well as
fabric processing.
 DHU is a statistical tool which is used to measure the quality. It stands for number of total defects in
hundred checked garments.
DHU = (total number of defects found) * 100 / total pieces checked
Whereas, percentage defective stands for:
%defective = (total number of defective pieces) *100 / total pieces checked
In this project the work is done for the improvement in quality by minimizing DHU% due to sewing.
 Data is collected on particular styles of garment for defects found, analyzed it for causes and remedial
action by using BRAINSTORMING and CAUSE – EFFECT diagram. Then corrective actions are implemented
to remove the faults and collected the data again.
From this work compared the DHU % before and after the trials.
INTRODUCTION TO THE PROJECT

4. JUSTIFICATION FOR THE STUDY
Extra labor cost
Extra raw material cost
Extra working hours
Wastage of rejected production
PRODUCTIVITY
SHIPMENT DELAY
EFFECTS COMPANY’S PRODUCTIVITY AND
MARKET REPUTATION
DHU – Defects per hundred units

5. OBJECTIVE
PRIMARY OBJECTIVE
SECONDARY OBJECTIVE
CAUSE OF SEWING DEFECTS
REDUCTION IN DHU IN SEWING LINE
ANALYZE DEFECTS UNDER 4Ms
ANALYZE FACTORS FOR REWORK

6. SCOPE OF THE STUDY
REDUCTION IN REWORK
REDUCTION IN EXTRA WORKING HOURS
REDUCTION IN REWORK COST
IMPROVEMENT IN WORK EFFECIENCY
INCREASE IN COMPANY’S PROFIT
INCREASE IN PRODUCTIVITY
IMPROVEMENT IN QUALITY
INCREASE IN ACCURACY LEVELS
REDUCTION IN DHU

7. LITERATURE REVIEW
1.
• WHAT IS A DEFECT?
2.
• TYPES OF DEFECTS
• SEWING AND NON SEWING DEFECTS
3.
• WHAT ARE DEFECTIVE PIECES?
4.
• ABOUT DHU- Defects per hundred units
• ABOUT PERCENTAGE DEFECTIVE(%age defective)

8. Defect : In terms of QUALITY, defect is a failure to meet specifications and requirements for
meeting customer demands .Frailty or shortcoming that prevents an item from being complete,
desirable, effective and safe.
WHAT IS DHU ?
DHU stands for number of total defects in hundred checked garments.
DHU = (total number of defects found) * 100 / total pieces checked
Whereas, percentage defective stands for:
%defective = (total number of defective pieces) *100 / total pieces checked
For example: Suppose in a day one table checker checked 72 pieces. He found
total 12 defective pieces. So, %defective is (12 * 100)/72= 16.66=17 (approx.)
DEFINE DEFECT……

9. These pieces mainly contains minor as well as major defects that can be result of
cutting, sewing, finishing, dyeing, washing and wrong pattern following. These are
mainly responsible for making reduction in the quality of the production.
Defects can be categorized into two categories:
SEWING DEFECTS: Defects of sewing that occurs during sewing process are called sewing
defects. These defects occur mainly during manufacturing process. It can occur due to improper
sewing techniques, wrong sewing methods and unskilled labour. These are mainly responsible for
affecting the quality of the garment hence affecting the productivity. Sewing defect is the
outcome which can be due to multiple reasons.
NON SEWING DEFECTS: Defects rather than sewing like pattern making defects, cutting
defects, bundling defects, marker defects, dyeing defects etc are called non sewing defects
What are DEFECTIVE PIECES?

10. Some of the SEWING DEFECTS
1. BROKEN STITCH AND SKIPPED STITCH: It can be defined as the discontinuity in the
stitch line causing improper attachment of any two panels or even more of garment. Skipped stitch
occurs when the loop of needle thread is not picked up by the point of the hook or the looper.
2. OPEN SEAM: It occurs when the threads in the seam ruptured causing a hole at that point in
the stitch line. Sometimes uneven adjusted SPI- Stitch per Inch causes open seam.

11. 3. MISSING PARTS: Absence of some parts of the garment while cutting, bundling, production,
finishing, sampling and packing. The components so missed can be
• Absence of strings as per required design and style from manufactured
pieces.
• Absence of trims like buttons, sequins, zipper, etc
4. WRONG LABEL ATTACHMENT : The descriptive and well defined pieces giving clear
information regarding the:
• Warnings regarding washing, drying, dry cleaning, ironing, bleaching etc.
• Size if the garment
• Colour, quality and composition
• About the brand and cost of the garment
5. MEASUREMENT OUT OF TOLERANCE: This fault occurs
when operator is not enough knowledgeable about how to take
proper measurements. It can also occur due to improper seam allowances,
wrong marking while cutting, etc

12. 6. STAINS: Stains refers to the marks that can either be removed or can’t be removed. In
majority stains can be removed when the pieces are send for inspection but sometimes it is
impossible to remove some marks resulting the piece in surplus.
• Yellow machine oil marks
• Marker marks
• Vegetable marks
• Tobacco marks
• Dye marks
• Rust marks
• Ink marks
• Sticker marks
• Fusing marks (shining marks)
7. CUT AND DAMAGE- This term refers to the defect that occurs mainly while sewing of
garments. It can also be the outcome of washing, cutting, dyeing, operator’s mistake and
finishing.

13. 8. IMPROPER PICO: It mainly occurs when the stitches of pico are cut,
damaged, uneven, over stitched, and broken. It all happens due to improper
machine settings as well as improper handling by the operator.
9. UNEVEN STITCH: The stitches are not straight and form a disorder.
Uneven stitching mainly occurs due to wrong method and technique
followed by operator.
10. PUCKERING: Seam pucker may be defined as a ridge, Corrugation of the material or a
number of wrinkles running across
and into one another which appear at the seam, when sewing together
two pieces of cloth.

14. BRAINSTORMING MODEL
OBJECTIVE DETECT THE DEFECT
DATA COLLECTION
CONSULTATION
CONCERNED
DEPARTMENTS
OPERATORS
PRODUCTION MANGER
STAFF
SUPERVISORS
INDUSTRY MENTOR
FINISHING MANGER
SAMPLING MANAGER
DATA ANALYZATION
SOLUTION MAJORLY CONTRIBUTING FACTOR
RESULTS

15. CAUSE AND EFFECT DIAGRAM

16. Serial no. CAUSE SOLUTION
1. When the thread tension is too tight Tension can be adjusted easily by using tension
dial. If it is too tight then it can be loosen up by
decreasing the tension to lower number
2. When thread is of poor quality Threads like POLYSTER possess great strength as
well as elasticity which help in avoiding any
thread breakage while sewing.
3. Improper lubrication in machine parts To provide smooth working to machine, the parts
must be oiled after regular intervals of time
depending upon the machine.
4. Improper threading It is very important that the threading must be
correct and proper for which the bobbin should
be wounded correctly. It shouldn’t have any loose
threads or loops sticking out.
The best solution always prefers empty bobbin.
Keep the pressure foot up every time you pull
the thread through the machine.
5. Needle hole of throat plate is burred Polish needle hole or replace throat plate
SOLUTIONS SORTED OUT BY USING BRAINSTORMING AND FISHBONE DIAGRAM

17. Serial no. CAUSE SOLUTION
BROKEN STITCH
6. Wrong placement of needle Poor thread tension often comes from an
incorrectly inserted needle. Machine
needles have a flat side that should always
face the back of the sewing machine.
7. Improper handling of worker The worker must be trained enough to
handle the materials and machine properly.
8. Mismatch in thread and needle size The thread and needle hole size must
match each other hence avoiding flagging
9. Either wrong thread or wrong needle used for
application
It must be very clear about the type of
needle to be used for sewing woven fabrics
like cotton, linen, etc. These fabrics require
sharp needles not ballpoint needles.
10. Worn out/defective sewing machine parts Thread guiding elements must be polished
to avoid burrs
11. Hook/looper damaged, or incorrectly adjusted, Regular polishing of hook/looper is required
and if damaged then it must be replaced.
12. Excessive needle heat To avoid needle heating, needle coolers like
thread lubrication or use of corespun
thread can be applied.

18. FISHBONE DIAGRAM FOR BROKEN STITCH
BROKEN STITCH
MACHINE METHOD
MATERIAL
MAN
IMPROPER HANDLING
HOOK/LOOPER DAMAGED
WRONG THREAD TENSION
IMPROPER THREADING
WRONG NEEDLE PLACEMENT
WRONG THREAD/NEEDLE USED
MISMATCH IN THREAD and NEEDLE SIZE
POOR QUALITY THREAD

19. METHODOLOGY
ANALYZE
DATA COLLECTION
DATA ANALYZE
IDENTIFICATION
PROBLEM DETECTION
IDENTIFYING THE
SOLUTION
IMPLEMENTATION
RESULTS
BRAINSTORMING
CAUSE AND EFFECT
DIAGRAM

20.  Review of existing working system in industry
 Targeted sewing department due to majorly occurring sewing defects
 Working within sewing department to collect data on the basis of :
Various types of sewing defects
Focusing on frequently occurring defects
Developing check sheets and formats to maintain records
 Data categorization on the basis of :
• Style type
• Defect type
• Daily routine basis of defect occurrence
 Further categorization on the basis of 4 Ms :
• Man
• Method
• Material
• Machine
STEPS AND PROCESSES FOLLOWED TO REDUCE DHU

21. STYLE
NUMBERS
CUT
AND
DAMAGE
IMPROPER
PICO
MISSING
PARTS
ROPING
MEASUREMENT
OUT
PUCKERING
BROKEN
STITCH
WRONG
LABEL
STAINS
UNEVEN
TOP
SEAM
OPEN
SEAM
SKIPPED
STITCH
LOOSE
STITCH
SLIPPED
STITCH
UN
BACK
TUCK
STITCH
IMPROPER
KAJ/BUTTON
ATTACHMENT
TOTAL
DEFECT
NO.
TOTAL
PIECES
CHECKED
22982 12 33 16 3 25 5 2 17 7 38 16 2 176 186
23587 2 7 11 5 2 3 13 9 3 21 7 18 11 47 112 124
23901 10 15 9 2 7 49 3 6 13 12 12 24 8 217 200
23262 7 8 6 1 23 3 1 31 13 33 21 4 27 146 152
22990 37 18 21 4 8 21 3 2 12 41 11 18 5 228 248
22992 11 16 3 5 21 4 3 15 13 21 32 3 147 312
Data collection and identification on the basis of STYLE WISE: Inspecting six styles defect wise

22. 22900
22982
23901
STYLES – TARGETED FOR STUDY

23. Segregation of data on the basis of defect wise and on the basis on daily
report analysis.
Development of graph tool on the basis of collected data
 DATA collection and GRAPH analysis on the basis of daily routine work
 Sorting out critical defects effecting QUALITY and PRODUCTIVITY of company
Analysis of data collected to identify majorly occurring defects.
Spreadsheets containing data
Graph analysis on the basis of data collected

24. PERCENTAGE DEFECTIVE (On daily basis)
DATE(JAN,FEB,
MARCH)
CUT
AND
DAMAGE
PUCKERING
LABEL
ATTACHMEBT
MEASUREMEN
T
OUT
ROPING
UNEVEN
TOP
SEAM
KAJ/BUTTON
IMPROPER
OVERLOCKING
SLIP
SEAM
STAINS
PICO
OTHERS
TOTAL
PIECES
CHECKED
TOTAL
DEFECTIVE
PIECES
%age
DEFECTIVE

25. GRAPH analysis on daily basis detected %age defective %age defective = 12.36%
16.66
20.62
21.43
41.46
17.19
9 9.19
11.36
11.43
9.21
14.43
12.32
8.6 8.16
10.81
7.29
10.45
13.73
14.05
5.29
9.41
4.2
9.39
7.45
10
8.7
11.92
0
5
10
15
20
25
30
35
40
45
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
%age DEFECTIVE

26. DEFECT TYPE MACHINE DEFECTS MAN DEFECTS
METHOD/MATERIAL
DEFECTS
PRE - DHU %age 9.44 5.4 5.7
9.44
5.4 5.7
0
1
2
3
4
5
6
7
8
9
10
MACHINE DEFECTS MAN DEFECTS METHOD/MATERIAL DEFECTS
PRE - DHU %age

28. I. FRIENDLY ENVIRONMENT TO THE LABORS
II. SEGMENTATION OF OPERATORS FOLLOWED BY END LINE INSPECTION SYSTEM
a) Segmenting operators into three categories depending upon their efficiency
levels - Segment A , B and C divided in three lanes with ten workers each.
b) A – higher working efficiency levels , B – average working efficiency, C- low
working efficiency levels
c) Depending upon the efficiency levels, operators were provided with their
respective operations.
d) For taking readings after implementation , at the end of each lane , end line
inspection was followed through 100% inspection system.
MODEL FOLLOWED FOR REDUCING MAN CAUSING DEFECTS

29. OPERATORS SEGMENTATION MODEL
SAMPLE AREA
SAMPLE SIZE
OPERATOR
SEGMENTATION
SEWING FLOOR
30 OPERATORS
A – HIGHER WORKING EFFICIENCY
B – AVERAGE WORKING EFFICIENCY
C – LOW WORKING EFFICIENCY
OPERATIONS PROVIDED
READINGS TAKEN END-LINE INSPECTION THROUGH 100% INSPECTION
PRE-POST READINGS
COMPARISON
RESULTS
5 OPERATORS
17 OPERATORS
8 OPERATORS

30. • FOR REDUCING MACHINE SEWING DEFECTS – THE MAINTENANCE FORMAT
RECOMMENDED :
• THE FORMAT WAS IMPLEMENTED ON NUMBER OF MACHINES TRIAL BASIS
• THE FORMAT SO COMPILED WAS FILLED BY CONCERNED SUPERVISORS AND
PRODUCTION MANAGERS
MAINTENANCE FORMAT FOLLOWED FOR REDUCING MACHINE CAUSING DEFECTS

31. • TRAINING FOR THE LABORS
PROCEDURES FOLLOWED FOR REDUCING METHOD/MATERIAL CAUSING DEFECTS
SAMPLE AREA
SAMPLE SIZE
RESULTS
FINDINGS
RANDOMLY INSPECTED
INSTRUCTIONS PROVIDED
SAMPLE TYPE
SEWING FLOOR
17 OPERATORS
FOR ex. IMPLEMENTATION OF HEMMING
FOLDERS FOR BEST QUALITY
OPERATORS WITH AVERAGE WORKING
EFFICIENCY

32. FOUR POINT FABRIC INSPECTION SYSTEM : 4 Point system for fabric inspection is
widely used in apparel industry for fabric quality inspection. It follows the criteria of giving
penalty points based on defects and defect length.
1. Fabric inspection method or preparation
2. Criteria of giving penalty points based on defects and defect length.
3. Calculation method of total penalty points for total defects found in a fabric
roll
4. A Check sheet or format for recording data
5. Knowledge of different types of defects (how a defect looks and
its appearance)
FABRIC AND RAW MATERIAL INSPECTION SYSTEM RECOMMENDED TO
SORCING DEPARTMENT

33. SIZE OF DEFECT PENALTY POINT
LENGTH OF DEFECTS IN FABRIC
Defects up to 3 inches 1
Defects > 3 inches < 6 inches 2
Defects > 6 inches < 9 inches 3
Defects > 9 inches 4
Holes and openings(largest dimension)
1 inch or less 2
Over 1 inch 4
CRITERIA FOR GIVING PENALTY POINTS

34. FOUR POINT FABRIC INSPECTION MUST BE FOLLOWED FOR EACH AND
EVERY TYPE OF FABRIC
LOW QUALITY FABRIC HIGH QUALITY FABRIC

35. IMPLEMENTATION OF FOLDERS- HEMMING FOLDER

36. 53.5
47.75
44
45
46
47
48
49
50
51
52
53
54
1 2
Series1
GRAPH ANALYSIS OF HEMMING FOLDER-average time reduction in seconds
Average time reduces by 53.5-47.75=5.75

37. 2.79
0.82
1.58
0
0.5
1
1.5
2
2.5
3
MACHINE DEFECTS MAN DEFECTS METHOD/MATERIAL DEFECTS
POST - DHU %age
DEFECT TYPE MACHINE DEFECTS MAN DEFECTS METHOD/MATERIAL DEFECTS
POST - DHU %age 2.79 0.82 1.58

38. POST IMPLEMENTATION %age DEFECTIVE(DAILY BASIS )= 8.09
DATE(MARCH
AND
APRIL)
CUT
AND
DAMAGE
PUCKERING
LABEL
ATTACHMEBT
MEASUREMEN
T
OUT
ROPING
UNEVEN
TOP
SEAM
KAJ/BUTTON
IMPROPER
OVERLOCKING
SLIP
SEAM
STAINS
PICO
OTHERS
TOTAL
PIECES
CHECKED
TOTAL
DEFECTIVE
PIECES
%age
DEFECTIVE

39. GRAPH ANALYSIS (ON DAILY BASIS)
9.72
14.43
16.07
26.83
10.94
5
5.75
6.82
5.71 5.92
8.46
7.97
5.38
4.08
6.31
4.17
5.97
9.8
10.74
3.57
5.98
3.1
6.97
5.32
7.8
6.75
8.96
0
5
10
15
20
25
30
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
%age defective

41. DEFECT TYPE MACHINE DEFECTS MAN DEFECTS
METHOD/MATERIAL
DEFECTS
PRE - DHU %age 9.44 5.4 5.7
POST - DHU %age 2.79 0.82 1.58
PRE-POST IMPLENTATION DATA COMPARISON

42. 9.44
5.4
5.7
2.79
0.82
1.58
0
1
2
3
4
5
6
7
8
9
10
MACHINE DEFECTS MAN DEFECTS METHOD/MATERIAL
DEFECTS
PRE - DHU %age
POST - DHU %age
PRE-POST IMPLEMENTATION 4M’s GRAPH ANALYSIS

43. DHU COMPARISON- PRE AND POST IMPLEMENTATION
STYLE BASIS
6.6
1.6
0
1
2
3
4
5
6
7
PRE-IMPLEMENTATION POST-IMPLEMENTATION
DHU
DHU

44. GRAPH ANALYSIS- PRE-POST IMPLEMENTATION %age defect on daily basis
9.72
14.43
16.07
26.83
10.94
5
5.75
6.82
5.71 5.92
8.46 7.97
5.38
4.08
6.31
4.17
5.97
9.8
10.74
3.57
5.98
3.1
6.97
5.32
7.8
6.75
8.96
16.66
20.62
21.43
41.46
17.19
9 9.19
11.3611.43
9.21
14.43
12.32
8.6 8.16
10.81
7.29
10.45
13.7314.05
5.29
9.41
4.2
9.39
7.45
10
8.7
11.92
0
5
10
15
20
25
30
35
40
45
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
pre %age defective
post %age DEFECTIVE

45. Average DHU percentage before implementation = 12.36 %
Average DHU percentage after implementation= 8.09%
Final average reduction in DHU% = 12.36 %– 8.09% = 4.27%
RESULTS AFTER IMPLEMENTING INSPECTION SYSTEM:

46. THANK YOU