Module 8: Six Sigma and Its Application to Textiles

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Statistical Quality Control in Textiles
Module 8Six Sigma and Its Application to
Textiles
Dr. Dipayan Das Assistant Professor Dept. of
Textile Technology Indian Institute of Technology
Delhi Phone [phone] E-mail
Dipayan_at_textile.iitd.ac.in
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What is Six Sigma? 1
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Six Sigma as a Statistical Measure

• The lowercase Greek letter sigmasstands for
  standard deviation, which is known to be a
  measure of variation present in a set of data, a
  group of items, or a process.
• For example, if you weigh fabric pieces of many
  different sizes, youll get a higher standard
  deviation than if you weigh fabric pieces of all
  the same size.
• The sigma measurement develops to help
• (1) Focussed measurements of paying the customers
  of a business. Many of the measures, such as
  labour hours, costs, and sales volume, companies
  have traditionally used evaluate things that are
  not related to what the customer really cares
  about

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Six Sigma as a Statistical Measure (Contd.)

• (2) Provide a consistent way to measure and to
  compare different processes. Using the sigma
  scale, we could assess and compare performance
  of, say, the cloth dying process with the cloth
  delivery processtwo very different but critical
  activities.
• In the language of Six Sigma, customer
  requirements and customer expectations are
  called critical to quality (CTQ).

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Six Sigma as a Goal

• Even if youre on the right track, youll get
  run over if you just sit there.
  
  
  WILL ROGERS
• When a business violates important customer
  requirements, it is generating defects,
  complaints, and cost. The greater the number of
  defects that occur, the greater the cost of
  correcting them, as well as the risk of losing
  the customers. Ideally, your company wants to
  avoid any defects and the resulting cost in money
  and customer satisfaction.
• We use the sigma measure to see how well or
  poorly a process performs and to give everyone a
  common way to express that
• measure.

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Six Sigma as a System of Management
A significant difference between Six Sigma and
seemingly similar programs of past years is the
degree to which management plays a key role in
regularly monitoring program results and
accomplishments. managers at all levels are held
accountable for a variety of measures Customer
satisfaction Key process performance
Scorecard metrics on how the business is
running Profit-and-loss statements Employee
attitude These measures provide feedback on the
performance of the regions. At regular meetings,
managers review key measures within their hotels
and select new Six Sigma projects that target
those measures that have fallen off.
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Six Sigma as a System of Management (Contd.)

• In short, Six Sigma is a system that combines
  both strong leadership and grassroots energy and
  involvement. In addition, the benefits of Six
  Sigma are not just financial. People at all
  levels of a Six Sigma company find that better
  understanding of customers, clearer processes,
  meaningful measures, and powerful.

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Six Sigma Quality 2
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Limitation of Three Sigma Quality
Let us consider that a product consists of 100
mutually independent parts and the probability of
producing the product within 3-sigma control
limit is 0.9973. Then, the probability that any
specific part of the product is non-defective is
0.9973?0.9973?0.9973?100 times (0.9973)100
0.7631. If it is assumed that all 100 parts must
be non-defective for the product to function
satisfactorily, then 23.70 of the products
produced under the three-sigma quality will be
defective. This is not an acceptable situation,
because there are many products that have many
components assembled in them.
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Six-sigma Quality
Under six-sigma quality, the probability that any
specific unit of the hypothetical product above
is non-defective is 0.9999998, or 0.002 parts per
million (ppm), a much better situation.
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Statistics of Six-sigma Quality
Process is centered on target
6?
?T
2?
4?
-4?
-2?
-6?
Specification limit Percent inside specifications ppm defective
?1 sigma 68.27 317300
?2 sigma 95.45 45500
?3 sigma 99.73 2700
?4 sigma 99.9973 63
?5 sigma 99.9999943 0.57
?6 sigma 99.9999998 0.002
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Statistics of Six-sigma Quality (Continued)
When six-sigma concept was developed, an
assumption was made that when the process reached
the six-sigma quality level, the process mean was
still subject to disturbances that could cause it
to shift by as much as 1.5 times standard
deviations off target. Under this scenario. A
six-sigma process would produce about 3.4 ppm
defective.
?T
6?
1.5?
-1.5?
4?
-4?
-6?
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Statistics of Six-sigma Quality (Continued)
Process mean is shifted 1.5? from the target
Specification limit Percent inside specifications ppm defective
?1 sigma 30.23 697700
?2 sigma 69.13 608700
?3 sigma 93.32 66810
?4 sigma 99.3790 6210
?5 sigma 99.97670 233
?6 sigma 99.999660 3.4
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Themes of Six Sigma 1
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Theme One Genuine Focus on Customer
As mentioned, companies launching Six Sigma have
often been appalled to find how little they
really understand about their customers. In six
sigma, customer focus becomes the top priority.
For example, the measures of Six Sigma
performance begin with the customer. Six Sigma
improvements are defined by their impact on
customer satisfaction and value.
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Theme Two Data- and-Fact-Driven Management
Six Sigma takes the concept of management by
fact to a new, more powerful level. Despite the
attention paid in recent years to improved
information systems, knowledge management, and so
on, many business decisions are still being based
on opinions and assumptions. Six Sigma discipline
begins by clarifying what measures are key to
gauging business performance and then gathers
data and analyzes key variables. Then problems
can be much more effectively defined, analyzed,
and resolvedpermanently. At a more down-to-earth
level, Six Sigma helps managers answer two
essential questions to support data-driven
decisions and solutions. 1. What
data/information do I really need? 2. How
do we use that data/information to maximum
benefit?
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Theme Three Processes Are Where Action is
Whether focused on designing products and
services, measuring performance, improving
efficiency and customer satisfaction, or even
running the business, Six Sigma positions the
process as the key vehicle of success. One of the
most remarkable breakthroughs in Six Sigma
efforts to date has been convincing leaders an
managersparticularly in service-based functions
and industriesthat mastering processes is a way
to build competitive advantage in delivering
value to customers.
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Theme Four Proactive Management
Most simply, being proactive means acting in
advance of events rather than reacting to them.
In the real world, though, proactive management
means making habits out of what are, too often,
neglected business practices defining ambitious
goals and reviewing them frequently, setting
clear priorities, focusing on problem prevention
rather than firefighting, and questioning why we
do things instead of blindly defending them. Far
from being boring or overly analytical, being
truly proactive is a starting point for
creativity and effective change. Six Sigma, as
well see, encompasses tools and practices that
replace reactive habits with a dynamic,
responsive, proactive style of management.
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Theme Five Boundary Less Collaboration
Boundarylessness is one of Jack Welchs mantras
for business success. Years before launching Six
Sigma, GEs chairman was working to break down
barriers and to improve teamwork up, down, and
across organizational lines. The opportunities
available through improved collaboration within
companies and with vendors and customers are
huge. Billions of dollars are lost every day
because of disconnects and outright competition
between groups that should be working for a
common cause providing value to customers.
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Theme Six Drive for Perfection Tolerate
Failure
How can you be driven to achieve perfection and
yet also tolerate failure? In essence, though,
the two ideas are complementary. No company will
get even close to Six Sigma without launching new
ideas and approacheswhich always involve some
risk. If people who see possible ways to be
closer to perfect are too afraid of the
consequences of mistakes, theyll never try.
Fortunately, the techniques well review for
improving performance include a significant dose
of risk management so the downside of setbacks or
failures is limited. The bottom line, though, is
that an company that makes Six Sigma its goal
will have to keep pushing to be ever more perfect
while being will in to acceptand
manageoccasional setbacks.
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Implementation of Six Sigma 1
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On-ramp 1 The Business Transformation

• Employees and managers can often sense the need
  for a company to break away from old habits and
  to transform itself. For those organizations with
  the need, vision, and drive to launch Six Sigma
  as a full-scale change initiative, this first
  on-ramp, business transformation, is the right
  approach.
• Everywhere, management will be trying to drive
  results from the changes and to control their
  impact. As an employee, you may find yourself on
  a Six Sigma team challenged to improve a critical
  business process or a key product.
• Teams chartered along the business-transformation
  highway are often asked to look at key process
  areas and to make recommendations for change.
• These teams may scrutinize-
• Distribution of the products by the company

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On-ramp 1 The Business Transformation (Contd.)

• The effectiveness of the sales process
• New-product development
• Critical customer complaints
• Product defects and habitual problems
• Information systems critical to business
  decision making
• Large-scale cost reductions
• If your company chooses the business-transformatio
  n on ramp, youll know it! This approach will
  have an impact on your work, how you measure your
  work, how you interact with customers and peers,
  and how you and your job performance are
  evaluated.

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On-ramp 2 Strategic Improvement
The middle on-ramp offers the most options. A
strategic improvement effort can be limited to
one or two critical business needs, with teams
and training aimed at addressing major
opportunities or weaknesses. Or, it may be a Six
Sigma effort concentrated in limited business
units or functional areas of the organization.
In fact, to those directly involved, the
strategic-improvement approach can seem as
all-encompassing as the all-out corporate wide
effort, but it simply is not as extensive or
ambitious as the most aggressive efforts. On the
other hand, a number of companies that have
started with the more limited strategic focus
have later expanded Six Sigma into a full-scale
corporate change initiative, and yours may evolve
that way, too.
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On-ramp 3 Problem Solving
The problem-solving approach is best for
companies that want to tap into the benefits of
Six Sigma methods without creating major change
ripples within the organization. If your business
takes this approach, theres a strong probability
that only a few people will be significantly
engaged in the effortunless, of course, it gets
ramped up later. The benefit of this approach is
in focusing on meaningful issues and addressing
their root causes, using data and effective
analysis rather than plain old gut feel. As an
example of this on-ramp, a major real estate
company is running a few training classes and
putting people to work on some key problems.
Although the company will have a handful of Black
Belts trained and some projects completed in a
few months, thats about all you can predict for
now. This company, like most others taking a
problem-solving route, is really just kicking the
tires on the Six Sigma vehicle.
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Process of Problem Solving Using Six Sigma 1
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Phase 1 Identifying and Selecting Project(s)
In this phase, management reviews a list of
potential Six Sigma projects and selects the most
promising to be tackled by a team. Setting good
priorities is difficult but very important to
making the teams work pay off. We counsel
leaders to pick projects based on the two Ms
meaningful and manageable. A project has to have
real benefit to the business and customers and
has to be small enough so the team can get it
done. At the end of this phase, your leadership
group should have identified high-priority
problems and given them some preliminary
boundaries.
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Phase 2 Forming The Team
Hand-in-hand with problem recognition comes team
and team leader (Black Belt or Green Belt)
selection. Naturally, the two efforts are
related. Management will try to select team
members who have good working knowledge of the
situation but who are not so deeply rooted in it
that they may be part of the problem. Smart
leaders realize that DMAIC team participation
should not be handed to idle slackers. If you are
chosen for a team, it means that you are viewed
as someone with the smarts and the energy to be a
real contributor!
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Phase 3 Developing The Charter
The Charter is a key document that provides a
written guide to the problem or project. The
Charter includes the reason for pursuing the
project, the goal, a basic project plan, scope
and other considerations, and a review of roles
and responsibilities. Typically, parts of the
Charter are drafted by the Champion and added to
and refined by the team. In fact, the Charter
usually changes over the course of the DMAIC
project.
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Phase 4 Training The team
Training is a high priority in Six Sigma. In
fact, some people say that training is a
misnomer because a lot of classroom time is
spent doing real work on the Black Belts or
teams project. The focus of the training is on
the DMAIC process and tools. Typically, this
training lasts one to four weeks. The time is
spread out, though. After the first week, the
team leader and/or team members go back to their
regular work but budget a key portion of their
time to working on the project. After a two- to
five-week intersession comes the second
training session, then another work period and
another week of training.
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Phase 5 DMAIC and implementing Solutions
Nearly all DMAIC teams are responsible for
implementing their own solutions, not just
handing them off to another group. Teams must
develop project plans, training, pilots, and
procedures for their solutions and are
responsible for both putting them in place and
ensuring that they workby measuring and
monitoring resultsfor a meaningful period of
time.
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Phase 6 Handing Off The Solution
Eventually, of course, the DMAIC team will
disband, and members return to their regular
jobs or move on to the next project. Because they
frequently work in the areas affected by their
solutions, team members often go forward to help
manage the new process or solution and ensure its
success. The hand-off is sometimes marked by a
formal ceremony in which the official owner,
often called Process Owner, of the solutions
accepts responsibility to sustain the gains
achieved by the team. (Dancing and fun may go on
until the wee hours of the morning. . . .) Just
as important, the DMAIC team members take a new
set of skills and experience to apply to issues
that arise every day.
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Case Studies
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Case Study I Reduction of Shade Variation of
Linen Fabrics Using Six Sigma 3

• The objective of this work was to reduce the
  shade matching time in the fabric dyeing process
  by optimizing the effect of the controllable
  parameters. The problem was tackled using the
  DMAIC cycle of disciplined Six Sigma methodology.
  Initially, the process baseline sigma level was
  found as 0.81 and a target sigma level was set at
  1.76.
• Actions taken on the critical activities led to
  the reduction in average excess time as 0.0125
  h/m. The yield of the overall process has
  improved to 82 with an improved sigma level of
  2.34. The estimated annual saving is to the tune
  of Rupees eighteen lakhs (over 40,000).

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Project Background

• In the weaving department, for some qualities,
  fabrics are woven from the dyed yarn (called yarn
  dyed quality) and for other qualities, fabrics
  are prepared from grey/bleached yarn and coloring
  is carried out in the dyeing department (called
  piece dyed quality) . These fabrics are single
  colored fabrics. Shade variation is found in the
  case of piece dyed quality of the fabrics, which
  literary means not meeting the customers
  expectation regarding that particular shade.
• Owing to variation of the shade as compared to
  the sample, color addition/ color stripping are
  carried out which unnecessarily increases the
  process cycle time, labor cost along with the
  wastage of dyes, chemicals, power, and sometimes
  fabrics also.

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Project Background (Continued)

• The sole purpose of selection of this project
  was
• to improve the productivity by reducing the shade
  matching time.
• to reduce the cost of poor dyeing quality.
• to reduce the process cycle time.
• to deliver the product to the customer on time.
• to impart moral strength to shop floor people
  regarding shade matching.

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Objective of The Project

• The core objective of the project is to reduce
  the shade matching time in the fabric dyeing
  process by optimizing the effect of the
  controllable parameters involved in the dyeing
  process through a disciplined Six Sigma
  methodology.

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Six Sigma Methodology (DMAIC Cycle)

• Define Phase of the Study
• The steps in this phase are
• Developing a project charter, where primarily the
  project team and the project boundary are
  identified.
• Preparing a process diagram, which is shown in
  Table 1 in the form of supplier-input-process-outp
  ut-customer (SIPOC).
• Defining terms related to a Six Sigma like unit
  (each lot of fabric under the process of dyeing)
  and defect (a particular lot/unit generates a
  defect if its shade does not meet the customers
  requirement at the first attempt after the dyeing
  process).
• Estimating project completion time of four months
  including system standardization

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DMAIC (Continued)
SIPOC details for dye house process
Supplier Input Process Output Customer
HRD Labor, technical personnel Scouring and bleaching Dyed fabrics Common people
Weaving Grey fabrics Dyeing and mercerization Special fabrics Special customer
Utility Steam, plant air, DM water, power Calendering and stentering Chagall fabrics Defense ministry
Chemical supplier Dye stuff, other chemicals Sanforizing Heavy duty fabrics Indian railways
Maintenance M/c parts Checking delivery Flame proof fabrics Defense ministry, airlines company, Indian railways
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Measure Phase of The Study

• The steps in this phase are
• to identify the relevant parameters for
  measurement.
• to develop proper data collection plans both for
  historical data and planned data.
• to estimate the baseline process performance
  through the sigma level based on process yield
  and fixing the target sigma level.
• to estimate the status quo of the dyeing process
  through the identified parameters.
• to segregate the significant factors for the next
  course of study through analysis and improvement
  phase

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Performance of Fabric Quality
Lots reprocessed Lots reprocessed Lots reprocessed Lots reprocessed Lots reprocessed Lots reprocessed
Quality (coded) Lots accepted Less tone More tone Total defect Grand total
F/Q-1 20 56 11 67 87
F/Q-2 14 28 11 39 53
F/Q-3 2 0 2
F/Q-4 2 2 2
F/Q-5 1 1 1
F/Q-6 1 1 1
F/Q-7 1 1 1
F/Q-8 1 1 1
F/Q-9 1 1 1
F/Q-10 1 0 1
F/Q-11 1 1 1
F/Q-12 1 1 1
Total 37 93 22 115 152
High demand
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Comparison of Defects Against Shades
Olive, D.K. grey, teak, magenta, and navy were
processed more frequently along with the frequent
generation of defective lots. These five shades
were contributing to 68 of the total defective
lots.
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Machinewise Performance of Fabric Lots
Lots not okay due to Lots not okay due to Lots not okay due to Lots not okay due to Lots not okay due to Lots not okay due to
M/C type Lots ok Less tone More tone Total defects defects
P/Jig-A 7 26 7 33 33/4082.5
P/Jig-B 7 20 6 26 26/3378.8
P/Jig-C 10 24 5 29 29/3974.4
P/Jig-D 13 23 4 27 27/4067.5
Jig A and Jig B were found to be more prone
towards generation of defects.
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Case Study II Reduction of Yarn Packing Defects
Using Six Sigma 4

• This project was aimed at reduction of rejection
  during packing of finished yarn cones through
  measuring the current performance level and
  initiating proper remedial action thereafter.

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Pareto Chart for No. of Defectives for various
Defects
Defects No. of defectives
Light 8803
Heavy 7696
Jali 3307
Threado 1730
Dirty 1604
Fluf 1262
Bas shap 769
Soft 546
Ribbon 487
Low TPI 199
Wrongle 146
Tip spot 139
Oil spot 105
Black sp 74
Less ply 55
Broken 52
Corkscrew 32
Mix 20
High TPI 19
Almost 65 of rejections were due to weight
variation of cones (i.e., either overweight and
underweight).
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Defectives due to Underweight
Count No. of defectives
2/42P 3392
4/12P 759
2/20P 603
3/20P 599
1/30V 531
3/12P 519
2/57LY 416
2/40P 379
2/30P/V 306
2/40P/V 303
2/30V 146
The major counts in terms of packing rejection
due to underweight were Ne 2/42sP, Ne 4/12sP, Ne
2/20sP, Ne 3/20sP, Ne 1/30sV, Ne 3/12sP.
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Defectives due to Overweight
Count No. of defectives
2/42P 2763
1/30V 775
4/12P 773
2/57LY 726
3/20P 601
3/12P 434
2/20P 230
2/40P/V 220
2/30P/V 208
2/30V 96
It is found that the major counts in terms of
packing rejection due to overweight were Ne
2/42sP, Ne 1/30sV, Ne 4/12sP, Ne 2/57sLY, Ne
3/20sP.
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Sales Volume for various Counts
Count Sales volume (Lakhs)
2/42P 82.97
4/12P 59.93
2/20P 52.15
2/60P 50.42
3/12P 39.05
3/20P 34.08
2/50P 34.05
1/30V 31.14
2/30V 20.56
2/30P 15.96
2/80P 10.35
It is found that the major counts in terms of
sales volume were Ne 2/42sP, Ne 4/12sP, Ne
2/20sP, Ne 2/60sP, Ne 3/12sP, and Ne 3/20sP.
These counts accounted for more than 75 of the
revenue.
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Frequently Asked Questions Answers
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Frequently Asked Questions Answers
Q1 How many pieces out of one million garments
are found to be defective under six sigma
process? A1 0.002 out of one million garments
are found to be defective under six sigma
process. Q2 How many defective garments a six
sigma process would produce if the process means
shifts to 1.5 times the standard deviation off
the target? A2 Under this scenario, a six-sigma
process would produce about 3.4 ppm defective.
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References

• Pande, P. and Holpp, L., What is Six Sigma?
  McGraw-Hill, New York, 2002.
• Montgomery, D. C., Introduction to Statistical
  Quality Control, John Wiley Sons, Inc.,
  Singapore, 2001.
• Das, P. and Roy, S., An application of six sigma
  methodology to reduce lot-to-lot shade of linen
  fabrics, Journal of industrial Textile, Vol. 36,
  No. 3, pp. 227-252, 2007.
• Mukhopadhyay, A. R. and Ray, S., Reduction of
  yarn packing defects using six sigma, Quality
  engineering, Vol. 18, pp. 189-206, 2006.

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Sources of Further Reading

1. Pande, P. and Holpp, L., What is Six Sigma?
   McGraw-Hill, New York, 2002.
2. Stamatis, D. H., Six Sigma Fundamentals A
   Complete Guide to The System, Methods, and Tools,
   Productivity Press, New York, 2004.
3. Levine, D. M., Statistics for six Sigma Green
   Belts with Minitab and JMP, Pearson and Prentice
   Hall, New Jersey, 2006.
4. Taghizadegan, S., Essentials of Lean Six Sigma,
   Elsevier Inc., USA, 2006.
5. Montgomery, D. C., Introduction to Statistical
   Quality Control, John Wiley Sons, Inc.,
   Singapore, 2001.