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AQM. What Is Quality?. So how to define Quality management ?. What Is Quality?. The Product?. The Process?. The Training?. Work Environment?. Evolution of Quality as a discipline. Quality Management.

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So how to define quality management

So how to define Quality management?

What is quality1
What Is Quality?

The Product?


The Training?



Quality management
Quality Management

  • Q.M is a system of establishing defect prevention actions and attitudes within a company or organization for the purpose of assuring conforming products or services.

  • Q.M treats the company as a process and the various management systems within that process as the variables that require measurement and control.

Quality management1

Quality Management……

where did it start?

The quality journey
The Quality journey

  • Ancient times …………….Industrial revolution – caveat emptor–“let the buyer beware”

  • Quality definition depended on the customer`s perception.

  • Quality - subjective and experiential (Barbon,1690)

  • Quality experienced in two ways-

    • Immediately- Manifest and

    • Through use - Latent

Quality the journey
Quality – The journey

  • Foodstuffs, footwear and such crafts work- Manifest quality characteristics – caveat emptor was feasible and practical.

  • Apparel – quality characteristics were primarily latent – different system- apprenticeship and guild formation for certain trades.

Quality the journey1
Quality – The journey

  • Measures existed for evaluating quantity of products(dimensions, weights etc.)


  • To evaluate quality- standards almost non-existent.

  • At about 2900 B.C The Pharaoh Khufu decreed that a unit of length would be the distance from the tip of his hand to his elbow- The Royal Egyptian Cubit

Quality the journey2
Quality – The journey

  • Non standardized materials; non-standardized methods - resulted in products of variable quality

  • For complex products evaluation – mechanisms in place were-

    • Punitive actions against craftsmen producing poor quality- The Code of Hammurabi

    • System of marking or trade marking to trace the product origins.

Illustration of hammurabi s code
Illustration of Hammurabi`s code

  • 229. If a builder build a house for some one, and does not construct it properly, and the house which he built fall in and kill its owner, then that builder shall be put to death.

  • 233. If a builder build a house for some one, even though he has not yet completed it; if then the walls seem toppling, the builder must make the walls solid from his own means.

Quality the journey3
Quality – The journey

  • Industrial revolution and henceforth - Quality Control

  • Industrial revolution-

    • Increased production- mass production

    • Complexity of process

    • Larger inventories

    • Factory setups for production- labor issues

    • Mass communication

    • Improvements in transport

Quality the journey4
Quality – The journey

  • Led to evolution of new management systems

  • Based on ideas of

    • Individual motivation

    • Conformance of products

  • About 1911-Frank and Lillian Gilbreth focused on how specific tasks were done the best way with the least amount of effort – basis of work study.

  • Same time period, Fredrick W. Taylor propounded his– “SCIENTIFIC MANAGEMENT” PHILOSOPHY

Quality the journey5
Quality – The journey

  • Four key managerial principles –

  • Develop a science for each man`s work

  • Train and develop the workman

  • Cooperate with others heartily

  • Divide work and responsibility between labor and management.

Quality the journey6
Quality – The journey

  • The managerial philosophy is thus different from the common tools associated with scientific management like-

  • Time study

  • Standardization

  • Compensation schemes

  • Modern cost systems

Quality the journey7
Quality – The journey

  • Conflict between productivity and quality.

  • World War I repercussion – foundation laid for the “Quality Control Department”

  • Responsibilities included-

  • Vendor inspection

  • Process inspection

  • Final inspection

  • Salvage etc.

Quality the journey8
Quality – The journey

  • Paradigm shift - responsibility for controlling manifest quality from the customer back to producer.

  • Concept of ‘Quality Control’ was born

  • Pioneers of this era in the management of quality

    • Walter Schewart

    • Harold Dodge

    • George Edwards

    • Joseph Juran

    • Harry Romig

Quality the journey9
Quality – The journey

  • Concepts and tools developed by them included-

    • statistical sampling plans

    • Percent defective and average quality limits

    • Control charts for identifying process variability

Quality the journey10
Quality – The journey

  • Statistical Process Control(SPC) –

  • The oldest and most widely known of the process control methods.

  • Involves the usage of statistical techniques, such as control charts, to analyze a work process or its output.

  • Identifies underlying causes of problems which cause process variations that are outside the pre-determined tolerance limits and implement controls to fix the problems.

Quality the journey11
Quality – The journey

Societies and Committees came up like-

  • Joint committee for development of Statistical Application in engineering and Manufacturing in1929

  • ASTM formed Committee on the interpretation and presentation of data in 1930

  • British Standards institute formed in 1931

  • British Standards 600``Application of Statistical methods to industrial standardization and Quality control” in 1935

  • U.S food, Drug and Cosmetics act-to establish quality standards for consumer products in 1938

  • German Standards committee – in 1926

Quality the journey12
Quality – The journey

  • World War II – profound impact on the practice of quality in organizations.

  • Prior to WWII – quality was assured through inspection and testing of conformance to specifications.

  • Increased volumes led to productions of standards for acceptance via sampling inspection

  • Armed Service Forces table for sampling inspection 1942 by Edwards,Dodge,Romig and Gause.(later estd. as MIL-STD-105D)

Quality the journey13
Quality – The journey

  • New trained quality practitioners in organizations changed the management of quality-

  • New procedures introduced-

    • Company quality control manuals

    • In-house statistical training

    • Quality data systems

    • Formal problem solving approaches

    • Measurement standards,

    • Quality audits

    • Quality reports

Quality the journey14
Quality – The journey

  • Decline of SQC in 1950`s due to

    • Control chart application dealt with only the sporadic problems and not the chronic waste

    • Process control did not involve the worker directly leading to disassociation of the activity.

    • Recession leading to downsizing of the QC groups.

    • In essence-

      Quality Control----evolving ------Quality Assurance but Business environment was not supportive.

Quality the journey15
Quality – The journey

  • Edwards, Juran, Feigenbaum and Deming-

  • Emphasis on the management to be more responsible and responsive to the issue of quality.

  • Quality is to be incorporated in all functional areas of the organization to be effective.

Quality the journey16
Quality – The journey


  • “the underlying principle of TQC is that , to provide genuine effectiveness, true quality control management must start with the design of the product and end only when the product has been placed in the hands of the customer who has remained satisfied…..thus quality is everybody`s job in the business”

Quality the journey17
Quality – The journey

  • In Japan-post WWII, Deming and Juran trained the Businesses in quality

  • Led to Japanese products becoming best in quality in the world.

  • Concept of “Company-Wide Quality Control” was formalized based on the teachings.

  • Phenomenon of QC Circles(abt. 1962-Japan) – inclusion of the worker in the quality control process

Quality the journey18
Quality – The journey

  • Quality Control Circles-

  • A team of departmental workers spend time(off-hours) together to solve departmental quality problems.

  • Membership was voluntary,QC circles- supported by formal training programs in statistical methods and problem solving.

  • Resulted in high motivational levels and were very successful.

Quality the journey19
Quality – The journey

  • Japanese TQC – three management functions-

  • Daily management- employee involvement,QC circles,training and suggestion programs, statistical quality control tools used to yield small incremental improvements or KAIZEN

Quality the journey20
Quality – The journey

  • Cross functional management- interaction between different functional departments like design and production and between organization and environment like customers and suppliers.- leading to innovations like KANBAN system and JUST-In – TIME(JIT)manufacturing.

Quality the journey21
Quality – The journey

  • Hoshin Planning or management by policy –goals of the organization are coalesced into specific policies so as to have an overall organized entity represented to the customer.

    The Japanese TQC led to the development of the concept of TOTAL QUALITY MANAGEMENT(TQM)

Quality the journey22
Quality – The journey

  • The global changes led to adoption of TQM

    • Rise of consumerism

    • Higher quality requirements

    • Intense competition

      Companies had to place emphasis on strategic quality management by investing in concepts of

    • Market research

    • Benchmarking

    • Life-cycle costing and

    • Measurement of customer satisfaction

Quality the journey23
Quality – The journey

  • Changes brought about by TQM-

    • Quality moved from being the responsibility of quality department to everyone`s responsibility

    • Importance of quality extended to include services and information like health care, education etc.

    • Benchmarking and other methods of learning best practices flourished

    • Improvement of process quality, whether through continuous improvement or re-engineering became a mainstream of organizational activity.

    • Measures of customer satisfaction and retention became a key managerial metric.

Quality the journey24
Quality – The journey

  • 1980`s and 1990`s the corporate leadership – espoused the importance of quality

  • Organizational quality practices became the benchmark requirement for supplier certification.

  • European Economic Community – organizational quality system standards which had to be met for the firms to gain market access to EEC`s.

  • ISO 9000 series- published to meet the growing need for international standardization in quality and adoption of third party quality system certification schemes.

Quality the journey25
Quality – The journey

  • Presently- more sophisticated statistical methods like ‘Six Sigma ‘ are being used by organizations to effectively control quality and reap profits.


  • Is a data-driven method for achieving near perfect quality by using the basic fundamentals of quality management documented by Dr. Juran.

  • Sigma is used to denote the standard deviation or the measure of variation in a process.

Quality the journey26
Quality – The journey

  • Six Sigma philosophy aims towards driving out waste, improving quality, cost and time performance of any business.

  • The greater number of sigma's within specifications, the fewer the defects.;the smaller the variation, the lower the cost.

  • Six sigma means defects occur in only 3.4 per million.

  • Best organizations are at 3-4 sigma which is about 6,200 defects per million

Quality the future

Quality – The Future

Will the quality discipline die?

Quality the future1

Quality – The Future

Broaden scope and focus towards enterprise and community?

Knowledge management total value creation

Knowledge management?

Total Value Creation?

Quality – The Future

Quality the future2

Quality – The Future

Product quality…………….. process quality

Process quality …………… service quality Service quality ………..information quality???

Care labelling

Care Labelling

Unit 4

Ref- Mehta and Bhardwaj Ch.4 &11

Ref. mat.- Ms. Divya Satyan

Care labeling
Care Labeling

  • A tag attached to textile or clothing products, showing instructions for proper care of the products.

  • Different care labeling systems for various countries.

  • Some systems are mandatory as required in national regulations,

  • Others are adopted on a voluntary basis.


  • The Federal Trade Commission (FTC) a care labeling regulation requiring care labels to be permanently affixed or attached to the products, with regular care information and instructions distinctly specified and remaining legible as long as the products last.

  • Labels should be attached so they can be seen or easily found by consumers at point of sale. If labels cannot be easily seen or found due to packaging, care information should also appear on the outside of the package or on a hang tag fastened to the product.

  • In developing care instructions, the ASTM standard D-3136 provides the terminology for permanent care labels for consumer textile and leather products other than carpets and upholstery.

Care labelling1
Care Labelling

  • FTC (Federal Trade Commission, USA)has specified what articles come under the care labeling rules. These are

    • All Textile apparel worn to cover or protect the body.

    • Exempt apparel: shoes, gloves and hats.

    • Excluded items:

      • Handkerchiefs, belts, suspenders and neckties because they do not cover or protect the body.

      • Non-woven garments made for one-time use because they do not require ordinary care.

  • Piece goods sold for making apparel at home

International care labeling system ginetex
International Care labeling system-GINETEX

  • The International Association for Textile Care Labeling (GINETEX) had developed a language-independent care labeling system in 1975.

  • GINETEX care labeling system (or international care labeling system) mainly uses symbols to provide care instructions.

  • The system consists of five basic symbols

Basic care symbols
Basic Care Symbols






A cross on any of them means that the treatment shall not be used and a bar under the symbols indicates milder treatment is needed (broken bar indicates a very mild treatment).


ISO Care Symbols

Washing Bleaching Ironing Dry-Cleaning Drying

Canadian care symbols
Canadian Care Symbols

The system consists of five basic symbols which are illustrated in three traffic light colours, with green colour indicates no special precautions, a red colour indicates prohibition and orange colour suggests that precautions necessary.

Japanese care labeling system
Japanese Care Labeling system

The Japanese care labelling system has symbols grouped in six categories: washing, possibility of chlorine-based bleaching, ironing, dry-cleaning, wringing and drying. Based on JIS L 0217 (1995)

May be ironed at 180 - 210 C if a cloth is placed between iron and garment



WASHING (with water)



Product safety

Product Safety

Unit 5

Ref: Mehta and Bhardwaj Ch. 4 & 11

Ref Mat. Ms. Divya Satyan

Product safety concerns
Product safety concerns

Safety issues with regard to the usage of apparel and accessories

Waist drawstrings can become Hood and neck drawstrings can become

entangled in a bus door entangled on playground equipment


January 9, 2004Alert #04-529

February 23, 2006Alert #06-530

Retailer: Victoria's Secret Direct, of Columbus, Ohio

Hazard: The kimono tops are made of fabric that fails to meet mandatory standards of fabric flammability. The sheer outer shell fabric of the kimono top can readily ignite and present a risk of burn injuries

Manufacturer: Susan Bristol Inc., of Boston, Mass.

Hazard: The marabou feather trim on the sweaters is dangerously flammable.

Products recalled from stores

Product safety concerns1
Product safety concerns

June 11, 2009Release # 09-241

Product- Chenille Robes

Product- Charm Bracelet

Reebok received a report of a death caused by lead poisoning of a 4-year-old child from Minneapolis. The child reportedly swallowed a piece from one of these charm bracelets sold by Reebok.

Blair has received reports of six deaths due to the robes catching on fire. Five of the six victims were female, and all five were cooking at the time of the incidents. Three of the victims were in their 80s.

Products recalled from stores

Safe product
SAFE product

  • A “safe product” is any product which under normal or reasonably foreseeable conditions of use presents no risk or only the minimum risk compatible with the product’s use and which is consistent with a high level of protection for consumers.

  • This can take the form of being protected from the event or from exposure to something that causes health or economical losses. It can include protection of people or of possessions.

Product safety regulation
Product Safety Regulation

  • Producers and distributors have for many years been obliged by product safety legislation to provide information and warnings as to the risks their products posed where those risks were not obvious and, where necessary, to provide instructions adequate to consumers’ needs as to the safe operation/use of the product.

Product safety assessment
Product Safety assessment

  • The safety of a product is assessed with regard to a number of matters, in particular:

  • The product’s characteristics;

  • Packaging;

  • Instructions for assembly and maintenance, use and disposal;

  • The effect on other products with which it might be used;

  • Labeling and other information provided for the consumer; and

  • The categories of consumers at risk when using the product, particularly Children and the elderly.

Drawstring hazards
Drawstring Hazards

  • The U.S. Consumer Product Safety Commission (CPSC) & ASTM F1816-97, “Standard Safety Specification for Drawstrings on Children’s Upper Outerwear”

    • remove the hood and neck drawstrings from all children’s upper outerwear, including jackets and sweatshirts, sized 2T to 12.

  • "Choking Risks to Children“- a reserch report evaluated the effectiveness of the ‘small parts cylinder’ test in preventing choking accidents to children under four from small toys or parts Garments and recommended a maximum size for the same.

Flammability regulation
Flammability regulation

  • Nightwear can burn rapidly when accidentally set alight by contact with an open fire or a gas or electric fire or other heat source, and cause serious injury - children and the elderly being especially vulnerable.

  • In consequence, various mandatory and voluntary measures have been taken to control the fire performance of the fabrics used in nightwear and to make the public more aware of the dangers.

UNITED KINGDOM - General Product Safety Regulations 1994 (SI 1994/No. 2328) &The Nightwear (Safety) Regulations 1985

  • The standard creates four categories of acceptable garments for nightwear: 

  • Category One: garments made from fabrics with low flame propagation properties;

  • Category Two: garments, which because of their design, are less likely to catch alight and if they do, the spread of flames is reduced because of the design features;

  • Category Three: all-in-one style garments made predominantly from knitted fabrics, in sizes 00 to 2;

  • Category Four: garments that are assigned a high flammability rating.  

UNITED KINGDOM - General Product Safety Regulations 1994 (SI 1994/No. 2328) &The Nightwear (Safety) Regulations 1985

  • Categories 1, 2 and 3 must have a white label stating 'LOW FIRE DANGER'

  • Category 4 garments must have a red label with a fire emblem, stating


  • Labels showing flammability performance and washing instructions must be permanent and securely sewn into the garment

Managing quality in decentralized manufacturing

Managing Quality In decentralized Manufacturing 1994/No. 2328) &

Unit 6-7

Ref: Dr. Rajesh Bheda

Quality assurance for standard product
Quality assurance for standard product 1994/No. 2328) &

  • Dedicated facility for the product is must

  • can plan detailed Q.A procedures and train people in specialist jobs

  • Processes are well planned in advance and control parameters are in place

  • Random sampling inspection at the end can be used to assess product quality

  • Planners are different from implementers

Managing quality in decentralized manufacturing dr bheda
Managing quality in decentralized manufacturing 1994/No. 2328) &(Dr. Bheda)

Q.Why do you face quality problems?

A.We have no problems at our end but our suppliers don`t understand quality.

A. Subcontractors are not bothered about quality, we do all we can


Reasons for failure
Reasons for failure 1994/No. 2328) &

  • Belief that quality starts with inspection and ends with inspection

  • Quality driven targets for the departments

  • Departmental goals may not synergize with organizational goals

  • Have no idea about the cost of quality in their organization

Role of fabricators
Role of fabricators 1994/No. 2328) &

1. Flexible manufacturing capacity

2. Good at manual value addition

3. Adapt at working on low volume, complex styles

4. Provide additional capacities at times of excess booking or rush orders.

Process capability key to quality in fashion apparel manufacturing
Process capability- key to quality in fashion apparel manufacturing

  • Without Process capability ,Quality cannot be expected

  • It is the responsibility of the top management to ensure the process capability of different process groups

Process model for sewing
Process model for sewing manufacturing



















Process chain
Process chain manufacturing




Process A

Process B

  • Three golden rules

  • Output of previous process becomes the input of the next process

  • No substandard input to be given to any process

  • No process shall allow substandard output to come out

Is average fabricator process capable
Is average fabricator process capable manufacturing

  • No, but they can be made process capable

  • we need to identify the deficiencies

  • to get the solutions, we need to think non-traditionally

  • also check the quality of inputs to the fabricators

Helping achieve process capability
Helping achieve process capability manufacturing

  • Provide machine maintenance support

  • need based technical support and training by master ot outside expert

  • improve illumination level(use of inverters/generators for lights ,fans)

  • encourage cleanliness to avoid stains

  • provide attachments and lease special machines

Suggestions for improving inputs
Suggestions for improving inputs manufacturing

  • Start in house cutting, do not issue fabric

  • cut interlining with die or band knife & carry out in house fusing

  • provide the right needles, thread etc.

  • graphic specifications to be provided in local language

Suggestions for improving inputs1
Suggestions for improving inputs manufacturing

  • multiple templates for pocket, collar etc.

  • set up special operations cell

  • enclosed transport for cut parts transfer

  • proper labeling of parts and transfer in proper bundles

  • receipt of material to be checked against issue and quality check to be carried out at fabricator`s place

The benefits
The benefits manufacturing

  • Promotes knowledge workers

  • right first time

  • reduced inspection

  • increased flexibility

  • minimum repairs and rejections

  • increased productivity

Statistical quality control

Statistical Quality Control manufacturing

Unit 8

Re: Mehta and Bhardwaj Ch.13 and Sara Kadolph Ch 15

SPC manufacturing

  • Statistical process control (SPC) involves using statistical techniques to measure and analyze the variation in processes.

  • Most often used for manufacturing processes

  • SPC is used to monitor product quality and maintain processes to fixed targets.

SPC manufacturing

  • Statistical quality control (SQC)refers to using statistical techniques for measuring and improving the quality of processes and includes SPC in addition to other techniques, such as sampling plans, experimental design, variation reduction, process capability analysis, and process improvement plans.

Statistical process control

· Commonly used tools in SPC include

  • Flow charts

  • Run charts

  • Pareto charts and analysis

  • Cause and effect diagram

  • Frequency histograms

  • Control charts

  • Process capability studies

  • Scatter diagrams

  • Acceptance sampling plans

Control charts
Control Charts manufacturing

  • Control chart -statistical tool for monitoring and improving quality.

  • Originated by Walter Shewhart in 1924 for the manufacturing environment-later extended by W. Edward Deming to quality improvement in all areas of an organization.

  • No matter how well the process is designed, there exists a certain amount of nature variability in output measurements.

  • When the variation in process quality is due to random causes alone, the process is said to be in-control.

  • If the process variation includes both random and special causes of variation, the process is said to be out-of-control.


  • Control charts differentiates between the two types of variations-

  • 1 -that is normally expected of the process due chance or common causes

  • 2- that change over time due to special causes

  • 1.Variations due to common causes

    • have small effect on the process

    • are inherent to the process because of:

      • the nature of the system

      • the way the system is managed

      • the way the process is organized and operated

  • can only be removed by

    • making modifications to the process

    • changing the process


2. Variations due to special causes are variations-

· localized in nature

· exceptions to the system

· considered abnormalities

· often specific to a

o certain operator

o certain machine

o certain batch of material, etc.

Investigation and removal of variations due to special causes are key to process improvement

Control charts1
Control Charts variations-

The control chart -detects the presence of special causes of variation.

In its basic form, the control chart is a plot of some function of process measurements against time. The points that are plotted on the graph are compared to a pair of control limits. A point that exceeds the control limits signals an alarm.

Control charts2
Control Charts variations-

An alarm signaled by a control chart may indicate that special causes of variation are present, and some action should be taken, ranging from taking a re-check sample to the stopping of a production line in order to trace and eliminate these causes

The objective of the quality control system is to minimize the unassignable or special causes of variations and eliminate the assignable or random causes of variation.

Control charts application
Control Charts- application variations-

  • The procedure behind the application of control charts is

    - sample the process at regular intervals

    - plot the statistic (or some measure of performance), e.g.

    - mean

    - range

    - variable

    - number of defects, etc.

    - check (graphically) if the process is under statistical control

    - if the process is not under statistical control, do something about it

SPC variations-

  • Statistical data can be characterized as either variable data or attribute data.

  • Attribute or discrete data-data on a characteristic that can assume certain distinct values. It records the no. of articles that are conforming or non-conforming to a specified requirement

  • Variable or continuous data is one when a record is made of the actual measured quality characteristic such as a dimension.


Different charts are used depending on the nature of the charted data   Commonly used charts are:

· for continuous (variables) data

o Shewhart sample mean( - chart)

o Shewhart sample range (R-chart)

o Cumulative sum (CUSUM)

o Exponentially Weighted Moving Average (EWMA) chart

o Moving-average and range charts

· for discrete (attributes and countable) data

o sample proportion defective (p-chart)

o sample number of defectives (np-chart)

o sample number of defects (c-chart)

o sample number of defects per unit (u-chart or -chart)

Spc implementation in the apparel industry
SPC implementation in the apparel industry charted data   Commonly used charts are:





  • These charts are useful in VISUAL INSPECTION.

  • They can be used for Fabric,Trims,cutting,in-ine and final inspection areas.

  • The usage of this chart is determined during the PRE-PRODUCTION MEETING.

SPC charted data   Commonly used charts are:


  • During the PPM- the QA manager and the QA team will decide about where the charts will be positioned based on the CRITICAL OPERATIONS of the garment.

  • The locations of measurements or variable charts are also determined at this meeting.

  • Critical operations are locations of a garment where the quality team predicts having potential problems due to difficulty in construction etc.

  • The Auditor must have ACCEPTABLE STANDARDS set by the manager in order to conduct an audit.

  • The SEALED SAMPLE can be used as a standard.

SPC charted data   Commonly used charts are:

  • If necessary a mock up of the operation can be established at the critical operation point.

  • The auditor must audit on an HOURLY basis.

  • The auditor could use AQL 2.5 single sampling plan in order to select sample size based on hourly production output.

  • “n” is identified as the sample size.“np” is identified as the number of defects found and “p” is the proportion.


    ____ = “p” p X 100= % of defects.


SPC charted data   Commonly used charts are:

  • The upper control limit(UCL)for this chart is determined by the target rejection rate planned for a particular period ( e.g. 5%).

  • The UCL is a FIXED control limit for in- line audits. Management can decide if they want to lower the defect percentage by bringing the UCL down.

  • For each out of control point a corrective action plan needs to be recorded by answering-





SPC charted data   Commonly used charts are:


  • 5-7 garments are measured per size and per hour at the critical points.

  • Upon measuring, the difference is recorded and plotted onto the chart.

  • In general, ½ to ¾ of the customer`s tolerance range is recommended for using during in-line audits.

  • E.g – waist measurement in a classic 5 pocket jeans can be more to the plus side than on the minus side, the UCL can be kept at +1 / 2” &the LCL at – 1 / 4”. The range in this case is 3 /4”.


  • If 1 out of 7measurements reached 1/8”out of control line, additional 7 measurements are taken and the difference is plotted below the hour column without joining the dots. The appearance will be more like a scatter chart.

SPC charted data   Commonly used charts are:

  • If none of the 7 measurements are out of the control line, then the auditor must return in the next hour.

  • If one or more measurements are out of control line, then Corrective Action, must be taken which could include 100% measurement of the bundle size.

  • If 2 out of 7 measurements reaches 1/8” out of control line or if one or more measurements reached1/4” out of control line, then additional 20 garments must be measured and plotted in a similar fashion.

  • If one or more measurements from the 20 is out of tolerance by ¼” or more then immediate corrective action should be taken.

Seven tools of quality control

Seven tools of Quality control charted data   Commonly used charts are:

Unit 9-10

Ref:Mehta and Bhardwaj Ch 13

Sara Kadolph ch 15

Seven tools
Seven tools charted data   Commonly used charts are:

  • These are the most fundamental quality control (QC) tools. They were first emphasized by Kaoru Ishikawa, professor of engineering at Tokyo University and the father of “quality circles.”

    • Cause-and-effect diagram (also called Ishikawa or fishbone chart): Identifies many possible causes for an effect or problem and sorts ideas into useful categories.

    • Check sheet: A structured, prepared form for collecting and analyzing data; a generic tool that can be adapted for a wide variety of purposes.

    • Control charts: Graphs used to study how a process changes over time.

Seven tools1
Seven tools charted data   Commonly used charts are:

  • Histogram: The most commonly used graph for showing frequency distributions, or how often each different value in a set of data occurs.

  • Pareto chart: Shows on a bar graph which factors are more significant.

  • Scatter diagram: Graphs pairs of numerical data, one variable on each axis, to look for a relationship.

  • Flow chart: A technique that separates data gathered from a variety of sources so that patterns can be seen

Fish bone diagram
Fish Bone diagram charted data   Commonly used charts are:

  • Also Called: Cause-and-Effect Diagram, Ishikawa Diagram

  • -identifies many possible causes for an effect or problem. It can be used to structure a brainstorming session. It immediately sorts ideas into useful categories.

  • Used-When identifying possible causes for a problem and/or Especially when a team’s thinking tends to fall into a rut.

Fish bone diagram procedure
Fish Bone diagram- procedure charted data   Commonly used charts are:

1.Agree on a problem statement (effect). Write it at the center right of the flipchart or whiteboard. Draw a box around it and draw a horizontal arrow running to it.

2.Brainstorm the major categories of causes of the problem. Can use generic headings:

1.Methods 2.Materials

3.Machines (equipment) 4.Measurement

5.People (manpower) 6.Environment

Fish bone diagram1
Fish Bone diagram charted data   Commonly used charts are:

  • This fishbone diagram was drawn by a manufacturing team to try to understand the source of periodic iron contamination. The team used the six generic headings to prompt ideas.

Check sheet
Check sheet charted data   Commonly used charts are:

  • Also called: defect concentration diagram

  • A check sheet is a structured, prepared form for collecting and analyzing data. This is a generic tool that can be adapted for a wide variety of purposes.

  • When to Use

    • When data can be observed and collected repeatedly by the same person or at the same location.

    • When collecting data on the frequency or patterns of events, problems, defects, defect location, defect causes, etc.

    • When collecting data from a production process.

Check sheet1
Check sheet charted data   Commonly used charts are:

  • Procedure

    • Decide what event or problem will be observed. Develop operational definitions.

    • Decide when data will be collected and for how long.

    • Design the form. Set it up so that data can be recorded simply by making check marks or Xs or similar symbols and so that data do not have to be recopied for analysis.

    • Label all spaces on the form.

    • Test the check sheet for a short trial period to be sure it collects the appropriate data and is easy to use.

    • Each time the targeted event or problem occurs, record data on the check sheet.

Check sheet2
Check sheet charted data   Commonly used charts are:

  • Example

  • The figure below shows a check sheet used to collect data on telephone interruptions. The tick marks were added as data was collected over several weeks.

Control chart
Control Chart charted data   Commonly used charts are:

  • Also called: statistical process control chart

  • Different types of control charts can be used, depending upon the type of data. The two broadest groupings are for variable data and attribute data.

  • Variable data are measured on a continuous scale. For example: time, weight, distance or temperature can be measured in fractions or decimals. The possibility of measuring to greater precision defines variable data.

  • Attribute data are counted and cannot have fractions or decimals. Attribute data arise when you are determining only the presence or absence of something: success or failure, accept or reject, correct or not correct. For example, a report can have four errors or five errors, but it cannot have four and a half errors.

Control chart1
Control Chart charted data   Commonly used charts are:

Variables charts

  • –X and R chart (also called averages and range chart)

  • –X and s chart

  • chart of individuals (also called X chart, X-R chart, IX-MR chart, Xm R chart, moving range chart)

  • moving average–moving range chart (also called MA–MR chart)

  • target charts (also called difference charts, deviation charts and nominal charts)

  • CUSUM (also called cumulative sum chart)

  • EWMA (also called exponentially weighted moving average chart)

  • multivariate chart (also called Hotelling T2)

    Attributes charts

  • p chart (also called proportion chart)

  • np chart

  • c chart (also called count chart)

  • u chart

Control chart2
Control Chart charted data   Commonly used charts are:

  • When to Use

    • When controlling ongoing processes by finding and correcting problems as they occur.

    • When predicting the expected range of outcomes from a process.

    • When determining whether a process is stable (in statistical control).

    • When analyzing patterns of process variation from special causes (non-routine events) or common causes (built into the process).

    • When determining whether your quality improvement project should aim to prevent specific problems or to make fundamental changes to the process.

Histogram charted data   Commonly used charts are:

  • A frequency distribution shows how often each different value in a set of data occurs. A histogram is the most commonly used graph to show frequency distributions. It looks very much like a bar chart, but there are important differences between them.

  • When to Use

    • When the data are numerical.

    • When you want to see the shape of the data’s distribution, especially when determining whether the output of a process is distributed approximately normally.

    • When analyzing whether a process can meet the customer’s requirements.

    • When analyzing what the output from a supplier’s process looks like.

    • When seeing whether a process change has occurred from one time period to another.

    • When determining whether the outputs of two or more processes are different.

    • When you wish to communicate the distribution of data quickly and easily to others.

Histogram charted data   Commonly used charts are:

  • Analysis

    • Before drawing any conclusions from your histogram, satisfy yourself that the process was operating normally during the time period being studied. If any unusual events affected the process during the time period of the histogram, your analysis of the histogram shape probably cannot be generalized to all time periods.

    • Analyze the meaning of your histogram’s shape.

Histogram charted data   Commonly used charts are:

  • Normal. A common pattern is the bell-shaped curve known as the “normal distribution.” In a normal distribution, points are as likely to occur on one side of the average as on the other. Be aware, however, that other distributions look similar to the normal distribution. Statistical calculations must be used to prove a normal distribution.

Histogram charted data   Commonly used charts are:

  • Skewed- The skewed distribution is asymmetrical because a natural limit prevents outcomes on one side. The distribution’s peak is off center toward the limit and a tail stretches away from it. For example, a distribution of analyses of a very pure product would be skewed, because the product cannot be more than 100 percent pure. Other examples of natural limits are holes that cannot be smaller than the diameter of the drill bit or call-handling times that cannot be less than zero. These distributions are called right- or left-skewed according to the direction of the tail.

Histogram charted data   Commonly used charts are:

  • Double-peaked or bimodal. The bimodal distribution looks like the back of a two-humped camel. The outcomes of two processes with different distributions are combined in one set of data. For example, a distribution of production data from a two-shift operation might be bimodal, if each shift produces a different distribution of results. Stratification often reveals this problem.

Histogram charted data   Commonly used charts are:

  • Plateau. The plateau might be called a “multimodal distribution.” Several processes with normal distributions are combined. Because there are many peaks close together, the top of the distribution resembles a plateau.

Histogram charted data   Commonly used charts are:

  • Edge peak. The edge peak distribution looks like the normal distribution except that it has a large peak at one tail. Usually this is caused by faulty construction of the histogram, with data lumped together into a group labeled “greater than…”

Histogram charted data   Commonly used charts are:

  • Truncated or heart-cut. The truncated distribution looks like a normal distribution with the tails cut off. The supplier might be producing a normal distribution of material and then relying on inspection to separate what is within specification limits from what is out of spec. The resulting shipments to the customer from inside the specifications are the heart cut.

Histogram charted data   Commonly used charts are:

  • Dog food- The dog food distribution is missing something—results near the average. If a customer receives this kind of distribution, someone else is receiving a heart cut, and the customer is left with the “dog food,” the odds and ends left over after the master’s meal. Even though what the customer receives is within specifications, the product falls into two clusters: one near the upper specification limit and one near the lower specification limit. This variation often causes problems in the customer’s process.

Bar chart
Bar Chart charted data   Commonly used charts are:

  • Also called: Pareto diagram, Pareto analysis

  • A Pareto chart is a bar graph. The lengths of the bars represent frequency or cost (time or money), and are arranged with longest bars on the left and the shortest to the right. In this way the chart visually depicts which situations are more significant.

    When to Use

    • When analyzing data about the frequency of problems or causes in a process.

    • When there are many problems or causes and you want to focus on the most significant.

    • When analyzing broad causes by looking at their specific components.

    • When communicating with others about your data.

Bar chart1
Bar Chart charted data   Commonly used charts are:

  • Figure 1 shows how many customer complaints were received in each of five categories.

  • Figure 2 takes the largest category, “documents,” from Figure 1, breaks it down into six categories of document-related complaints, and shows cumulative values.

  • If all complaints cause equal distress to the customer, working on eliminating document-related complaints would have the most impact, and of those, working on quality certificates should be most fruitful.

Scatter diagram
Scatter Diagram charted data   Commonly used charts are:

  • Also called: scatter plot, X–Y graph

  • The scatter diagram graphs pairs of numerical data, with one variable on each axis, to look for a relationship between them. If the variables are correlated, the points will fall along a line or curve. The better the correlation, the tighter the points will hug the line.

  • When to Use

    • When you have paired numerical data.

    • When your dependent variable may have multiple values for each value of your independent variable.

    • When trying to determine whether the two variables are related, such as when trying to identify potential root causes of problems.

    • After brainstorming causes and effects using a fishbone diagram, to determine objectively whether a particular cause and effect are related.

    • When determining whether two effects that appear to be related both occur with the same cause.

    • When testing for autocorrelation before constructing a control chart.

Scatter diagram some facts
Scatter Diagram- some facts charted data   Commonly used charts are:

  • Even if the scatter diagram shows a relationship, do not assume that one variable caused the other. Both may be influenced by a third variable.

  • When the data are plotted, the more the diagram resembles a straight line, the stronger the relationship.

  • If a line is not clear, statistics (N and Q) determine whether there is reasonable certainty that a relationship exists. If the statistics say that no relationship exists, the pattern could have occurred by random chance.

  • If the scatter diagram shows no relationship between the variables, consider whether the data might be stratified.

  • If the diagram shows no relationship, consider whether the independent (x-axis) variable has been varied widely. Sometimes a relationship is not apparent because the data don’t cover a wide enough range.

  • Think creatively about how to use scatter diagrams to discover a root cause.

  • Drawing a scatter diagram is the first step in looking for a relationship between variables.

Flow chart
Flow Chart charted data   Commonly used charts are:

Or run chart is used to understand the process and identify the variables affecting it.

Cost of quality and quality maturity grid

Cost Of Quality and Quality Maturity Grid charted data   Commonly used charts are:

Unit 11-12

Ref. Philip Crosby-Quality is free.

This is what us congress says about importance of quality
This is what US Congress says about importance of Quality charted data   Commonly used charts are:

  • Even the U.S. Congress has recognized national importance of quality in a 1988 report [8], “Quality as a Means to Improve Our Nation’s Competitiveness,” which opens with a statement,

  • “It is important we recognize a significant portion of our trade deficit is due to the ability of foreign competitors to deliver higher quality products that are either novel, less costly to produce, promise better service or some combination of the above.

This is what us congress says about importance of quality1
This is what US Congress says about importance of Quality charted data   Commonly used charts are:

  • What finally sank into US industry is the tremendous cost of ignoring quality. In most traditional factories that cost is probably the biggest item on their list of expenses, and it is always bigger than gross profit. But because the cost of quality is rarely broken out in gory detail, management has no idea of its true dimensions. When quality audits are performed, they invariably uncover huge “hidden plants” staffed and equipped just to find and fix defective products.

Why quality
Why Quality? charted data   Commonly used charts are:

  • Quality related costs can be as high as 25% of sales.

  • One fourth of the people employed do not produce but re-do and re-inspect & re-re-do.

  • Quality costs are greater than gross profit.

  • In world class companies these costs can be brought down to 2.5%.


Quality : Definition charted data   Commonly used charts are:

Offering product or services that a customer has never dreamt of, forget alone specifying the need for it. But having received the product the customer feels that he always needed it

The ASQC Quality Cost Committee (5) recommends breaking down quality costs into the following four areas

1. Prevention Cost

The cost associated with personnel engaged in designing, implementing and maintaining the quality system. Maintaining the quality system includes auditing the system.

2. Appraisal Costs

The costs associated with the measuring, evaluating or auditing of products, components and purchased materials to assure conformance with quality standards and performance requirements.



The ASQC Quality Cost Committee (5) recommends breaking down quality costs into the following four areas

3. Internal Failure Cost

The costs associated with defective products, components and materials that fail to meet quality requirements and result in manufacturing losses.

4. External Failure Costs

The costs generated when defective products are shipped to customers.

Failure costs external
Failure Costs quality costs into the following four areasExternal

  • Repair

  • Warranty Claims

  • Complaints

  • Returns

  • Liability

Failure costs internal
Failure Costs quality costs into the following four areasInternal


  • Rework or Rectification

  • Down Grading

  • Failure Analysis

Appraisal costs
Appraisal Costs quality costs into the following four areas

  • Inspection and Test

  • Quality Audits

  • Inspection Equipment

Prevention costs
Prevention Costs quality costs into the following four areas

  • Setting Standards

  • Quality Planning

  • Quality Assurance

  • Inspection Equipment

  • Training

  • Miscellaneous

Non quality levels in apparel industry as per a us study by jonathan cope assoc
Non Quality Levels in Apparel Industry quality costs into the following four areas(As per a US study by Jonathan Cope Assoc.)

  • Fabric vendor defective level = 2 to 5 %.

  • Work-in-process delays due to 20% in-line re-work.

  • Average plant labor includes 10% non value adding checkers.

  • Contractor defect level is 8%.

  • Finished product quality audit level is 10%.

  • 30% late deliveries, 30% under-shipments.

  • 1% customer returns but about 10% dissatisfied customers.


Quality Failure Cost quality costs into the following four areas



* New Design or Unproven New Materials


Cost of Quality: The objective Indicator of the Quality Maturity of Organisations


  • Management Understanding and Attitude

  • Quality Organization Status

  • Cost of Quality as percentage of Sales

  • Quality Improvement Actions

  • Summation of Company Quality Posture











Source: Quality is Free by Philip B. Crosby


Stage-I Maturity of Organisations


Quality Maturity Grid

Management Attitude

Quality Imp. Actions

Quality Org. Status

  • No comprehension of quality as a management tool.

  • Tend to blame quality department for “quality problems.

No organized activities. No understanding of such activities.

  • Quality is hidden in manufacturing or engineering department.

  • Inspection probably not part of organisation.

  • Emphasis on appraisal and sorting

Cost Of Quality%

Co.’s Quality Posture



“We don’t know why we have problems with quality?”

Source: Quality is Free by Philip B. Crosby


Stage-II Maturity of Organisations


Quality Maturity Grid

Management Attitude

Quality Imp. Actions

Quality Org. Status

  • A stronger quality leader is appointed but main emphasis is still on appraisal and moving the product. Still part of manufacturing or other

  • Recognizing that quality management may be of value but not willing to provide money or time to make it all happen.

Trying obvious “motivational” short-range efforts.

Cost Of Quality%

Co.’s Quality Posture



“Is it absolutely necessary to always have problems with quality?”

Source: Quality is Free by Philip B. Crosby


Stage-III Maturity of Organisations


Quality Maturity Grid

Management Attitude

Quality Imp. Actions

Quality Org. Status

While going through quality improvement program learn more about quality management; becoming supportive and helpful.

Implementation of the 14-step program with thorough understanding and establishment of each seep.

Quality department reports to top management, all appraisal is incorporated and manager has role in management of company.

Cost Of Quality%

Co.’s Quality Posture

“Through management commitment and quality improvement we are identifying and resolving our problems.”


Actual -12%

Source: Quality is Free by Philip B. Crosby


Stage-IV Maturity of Organisations


Quality Maturity Grid

Management Attitude

Quality Org. Status

Quality Imp. Actions

  • Participating.

  • Understand absolutes of quality management.

  • Recognize their personal role in continuing emphasis.

Continuing the 14-step program and starting Make Certain.

Quality manager is an officer of company; effective status reporting and preventive action.

Involved with consumer affairs and special assignments.

Co.’s Quality Posture

Cost Of Quality%


Actual- 8%

“Defect prevention is a routine part of our operation.”

Source: Quality is Free by Philip B. Crosby


Quality Maturity Grid Maturity of Organisations



Management Attitude

Quality Imp. Actions

Quality Org. Status

Quality improvement is a normal and continued activity.

Quality manager on board of directors.

Prevention is main concern. Quality is a thought leader.

Consider quality management an essential part of company system.

Co.’s Quality Posture

Cost Of Quality%

Reported- 2.5%

Actual - 2.5%

“We know why we do not have problems with quality.”

Source: Quality is Free by Philip B. Crosby

Interrelationship of quality costs
Interrelationship of Quality Costs Maturity of Organisations

% of Sales

Distributionof Quality Costs













External Failure


Internal Failure



Maturity of the Quality System


Quality & Profitability Maturity of Organisations