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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. - PowerPoint PPT Presentation

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Page 1: AQM

AQM

Page 2: AQM

What Is Quality?

Page 3: AQM

So how to define Quality

management?

Page 4: AQM

What Is

Quality?The Product?

The Process?

Work Environment?

The Training?

Page 5: AQM

Evolution of Quality as a discipline

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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.

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Quality Management……

where did it start?

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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-

1. Immediately- Manifest and 2. Through use - Latent

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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.

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Quality – The journey• Measures existed for evaluating quantity of

products(dimensions, weights etc.)but

• 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

Page 11: AQM

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.

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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.

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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

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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

Page 15: AQM

Quality – The journey• Four key managerial

principles –1. Develop a science for

each man`s work2. Train and develop the

workman3. Cooperate with others

heartily4. Divide work and

responsibility between labor and management.

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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

Page 17: AQM

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.

Page 18: AQM

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

Page 19: AQM

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

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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.

Page 21: AQM

Quality – The journeySocieties 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

Page 22: AQM

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 estd.in 1942 by Edwards,Dodge,Romig and Gause.(later estd. as MIL-STD-105D)

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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

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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.

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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.

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Quality – The journey

• Feigenbaum`s- TOTAL QUALITY CONCEPT(TQC)-

• “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”

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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

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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.

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Quality – The journey

• Japanese TQC – three management functions-

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

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Quality – The journey

2. 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.

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Quality – The journey

3. 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)

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Quality – The journey

• The global changes led to adoption of TQM– Rise of consumerism– Higher quality requirements– Intense competitionCompanies had to place emphasis on strategic

quality management by investing in concepts of– Market research– Benchmarking– Life-cycle costing and– Measurement of customer satisfaction

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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.

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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.

Page 35: AQM

Quality – The journey• Presently- more sophisticated statistical methods

like ‘Six Sigma ‘ are being used by organizations to effectively control quality and reap profits.

• SIX SIGMA – • 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.

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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

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Quality – The Future

Will the quality discipline die?

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Quality – The Future

Broaden scope and focus towards enterprise and community?

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Quality – The Future

Knowledge management?Total Value Creation?

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Quality – The Future

Product quality…………….. process qualityProcess quality …………… service quality Service quality ………..information quality???

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Understanding Quality Management- Joseph Juran

Session 2 -3Assignment 1

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Care Labelling

Unit 4Ref- Mehta and Bhardwaj Ch.4

&11Ref. mat.- Ms. Divya Satyan

Page 43: AQM

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.

Page 44: AQM

American• 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.

Page 45: AQM

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

Page 46: AQM

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

Page 47: AQM

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).

WASHING BLEACHING IRONING Dry-cleaningDRYING

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ISO Care Symbols Washing Bleaching Ironing Dry-Cleaning Drying

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ASTM Standard D5489-96c

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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.

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Japanese Care Labeling systemThe 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)

WASHING (with water) Chlorine-based bleaching May be ironed at 180 - 210 C if a cloth is placed between iron and garment

DRY-CLEANING

WRINGINGDRYING

Page 52: AQM

Product Safety

Unit 5Ref: Mehta and Bhardwaj Ch. 4 & 11

Ref Mat. Ms. Divya Satyan

Page 53: AQM

Product safety concerns

Waist drawstrings can become Hood and neck drawstrings can becomeentangled in a bus door entangled on playground equipment

Safety issues with regard to the usage of apparel and accessories

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January 9, 2004Alert #04-529

Manufacturer: Susan Bristol Inc., of Boston, Mass. Hazard: The marabou feather trim on the sweaters is dangerously flammable.

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

Products recalled from stores

Page 55: AQM

Product safety concerns

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.

Products recalled from stores

June 11, 2009Release # 09-241

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.

Product- Charm Bracelet Product- Chenille Robes

Page 56: AQM

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.

Page 57: AQM

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.

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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.

Page 59: AQM

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.

Page 60: AQM

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.

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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.  

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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

• 'WARNING - HIGH FIRE DANGER - KEEP WAY FROM FIRE‘

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

Page 63: AQM

Managing Quality In decentralized Manufacturing

Unit 6-7Ref: Dr. Rajesh Bheda

Page 64: AQM

Quality assurance for standard product

• 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

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Managing quality in decentralized manufacturing (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

…………..

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Reasons for failure

• 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

Page 67: AQM

Role of fabricators

1. Flexible manufacturing capacity2. Good at manual value addition3. Adapt at working on low volume, complex

styles4. Provide additional capacities at times of

excess booking or rush orders.

Page 68: AQM

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

Page 69: AQM

Process model for sewing

MOTIVATED PEOPLE

KNOW-HOW

SKILLS

TRAINING

PLANT & MACHINERY

QUALITYINPUT

=

RAW MATERIAL+

SPECIFICATIONS

QUALITYOUTPUT

=

PROCESSEDCOMPONENTS

ORGARMENTS

Page 70: AQM

Process chain

Output

=

InputProcess 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

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Is average fabricator process capable

• 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

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Helping achieve process capability

• 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

Page 73: AQM

Suggestions for improving inputs

• 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

Page 74: AQM

Suggestions for improving inputs

• 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

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The benefits

• Promotes knowledge workers• right first time• reduced inspection• increased flexibility• minimum repairs and rejections• increased productivity

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Statistical Quality Control

Unit 8Re: Mehta and Bhardwaj Ch.13

and Sara Kadolph Ch 15

Page 77: AQM

SPC• 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.

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SPC

• 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.

Page 79: AQM

STATISTICAL PROCESS CONTROLCommonly 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

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Control Charts• 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.

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• 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

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2. Variations due to special causes are · 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

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Control ChartsThe 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.

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Control ChartsAn 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 causesThe 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.

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Control Charts- application• 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

Page 86: AQM

SPC• 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.

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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)

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SPC implementation in the apparel industry

• THERE ARE 2 TYPES OF CHARTS BEING USED • WORMANSHIP CONTROL CHART OR ATTRIBUTE

CHART• MEASUREMENT CONTROL CHART OR VARIABLES

CHART • WORKMANSHIP OR ATTRIBUTE CHART PROCEDURE • 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.

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SPC• WORKMANSHIP OR ATTRIBUTE CHART PROCEDURE-

• 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.

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SPC• 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.“np”

____ = “p” p X 100= % of defects.“n”

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SPC• 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-

• WHAT HAPPENED,• HOW DID IT HAPPEN, • HOW WAS IT CORRECTED &• WHO CORRECTED?

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SPC• MEASUREMENT OR VARIABLE CHART PROCEDURE:-

• 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”.

CONDITIONS-• 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.

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SPC

• 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.

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Seven tools of Quality control

Unit 9-10Ref:Mehta and Bhardwaj Ch 13

Sara Kadolph ch 15

Page 95: AQM

Seven tools• 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.

Page 96: AQM

Seven tools– 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

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Fish Bone diagram• 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.

Page 98: AQM

Fish Bone diagram- procedure

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

Page 99: AQM

Fish Bone diagram• 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.

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Check sheet• 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.

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Check sheet• 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.

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Check sheet• 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.

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Control Chart• 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.

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Control ChartVariables 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

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Control Chart• 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.

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Histogram• 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.

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Histogram

• 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.

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Histogram• 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.

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Histogram• 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.

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Histogram

• 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.

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Histogram

• 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.

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Histogram

• 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…”

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Histogram• 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.

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Histogram• 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.

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Bar Chart• 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.

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Bar Chart• 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.

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Scatter Diagram• 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.

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Scatter Diagram- some facts 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.

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Flow Chart

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

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Cost Of Quality and Quality Maturity Grid

Unit 11-12Ref. Philip Crosby-Quality is free.

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This is what US Congress says about importance of Quality

• 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.

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This is what US Congress says about importance of Quality

• 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.

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Why Quality?

• 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%.

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Quality : DefinitionQuality : Definition

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

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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.

Cont...

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.

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

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Failure CostsExternalExternal

• Repair• Warranty Claims• Complaints• Returns• Liability

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Failure CostsInternalInternal

• SCRAP

• Rework or Rectification

• Down Grading

• Failure Analysis

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Appraisal Costs

• Inspection and Test

• Quality Audits

• Inspection Equipment

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Prevention Costs

• Setting Standards

• Quality Planning

• Quality Assurance

• Inspection Equipment

• Training

• Miscellaneous

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Non Quality Levels in Apparel Industry(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.

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Quality Failure CostQuality Failure Cost

12

10

16

36

14

12

Human Error

Bad Inspection

Bad Specification

Design*Fault

Poor Planning

Others

CA

USE

% OF TOTAL

Cause

* New Design or Unproven New Materials

52% 66%

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MEASUREMENT CATEGORIESMEASUREMENT CATEGORIES

• Management Understanding and Attitude

• Quality Organization Status

• Cost of Quality as percentage of Sales

• Quality Improvement Actions

• Summation of Company Quality Posture

Stage-IStage-IUNCERTAINTYUNCERTAINTY

Stage-IIStage-IIAWAKENINGAWAKENING

Stage-IIIStage-IIIENLIGHTENMENTENLIGHTENMENT

Stage-IVStage-IVWISDOMWISDOM

Stage-VStage-VCERTAINTYCERTAINTY

Source: Quality is Free by Philip B. Crosby

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

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Stage-IStage-IUNCERTAINTYUNCERTAINTY

Management Attitude Quality Org. Status

Cost Of Quality%

Quality Imp. Actions

Co.’s Quality Posture

•No comprehension of quality as a management tool. •Tend to blame quality department for “quality problems.

•Quality is hidden in manufacturing or engineering department. •Inspection probably not part of organisation.•Emphasis on appraisal and sorting

Reported-Unknown Actual-20%“We don’t know why we

have problems with quality?”

No organized activities. No understanding of such activities.

Source: Quality is Free by Philip B. Crosby

Quality Maturity Grid Quality Maturity Grid

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Stage-IIStage-IIAWAKENINGAWAKENING

Management Attitude Quality Org. Status

Cost Of Quality%

Quality Imp. Actions

Co.’s Quality Posture

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

Reported-3%Actual-18%

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

Trying obvious “motivational” short-range efforts.

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

Source: Quality is Free by Philip B. Crosby

Quality Maturity Grid Quality Maturity Grid

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Stage-IIIStage-IIIENLIGHTENMENTENLIGHTENMENT

Management Attitude Quality Org. Status

Cost Of Quality%

Quality Imp. Actions

Co.’s Quality Posture

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

Reported-8%Actual -12%

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

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.

Source: Quality is Free by Philip B. Crosby

Quality Maturity Grid Quality Maturity Grid

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Stage-IVStage-IVWISDOMWISDOM

Management Attitude Quality Org. Status

Cost Of Quality%

Quality Imp. Actions

Co.’s Quality Posture

•Participating. •Understand absolutes of quality management.•Recognize their personal role in continuing emphasis.

Reported-6.5%Actual- 8%“Defect prevention is a

routine part of our operation.”

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.

Source: Quality is Free by Philip B. Crosby

Quality Maturity Grid Quality Maturity Grid

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Stage-VStage-VCERTAINTYCERTAINTY

Management Attitude Quality Org. Status

Cost Of Quality%

Quality Imp. Actions

Co.’s Quality Posture

Consider quality management an essential part of company system.

Reported- 2.5%Actual - 2.5%“We know why we do not

have problems with quality.”

Quality improvement is a normal and continued activity.

Quality manager on board of directors.Prevention is main concern. Quality is a thought leader.

Source: Quality is Free by Philip B. Crosby

Quality Maturity Grid Quality Maturity Grid

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Interrelationship of Quality Costs

Distribution of Quality Costs

Maturity of the Quality System

Qua

lity

Cos

ts

% of Sales

20

18

16

14

12

10

8

6

4

2

0

Total

Internal Failure

Appraisal Prevention

External Failure

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Quality & ProfitabilityQuality & ProfitabilityIMPROVED IMPROVED CONFORMANCECONFORMANCE

BETTER OUTGOING BETTER OUTGOING QUALITYQUALITY LOWER REWORK LOWER REWORK

AND SECONDS AND SECONDS COSTSCOSTS

LOWER COSTS OF LOWER COSTS OF RETURNSRETURNS

INCREASED INCREASED PRODUCTIVITYPRODUCTIVITY

LOWER PRODUCTION LOWER PRODUCTION COSTSCOSTS

INCREASED PROFITSINCREASED PROFITS