Copyright (c) 2009 John Wiley & Sons, Inc.

Quality Improvement in the Modern Business Environment
Chapter 1 Quality Improvement in the Modern Business Environment

1-1. The Meaning of Quality and Quality Improvement
Dimensions of Quality Quality Engineering Technology

1-1.1 Dimensions of Quality
Performance Reliability Durability Serviceability Aesthetics Features Perceived Quality Conformance to standards

Performance Will the product perform its intended job?
Evaluate software spreadsheet packages. One outperform another with respect to the execution speed

Reliability How often does the product fail?
How often does this car require repair?

Durability How long does the product last?
The product should perform satisfactorily over a long period of life

Serviceability How easy is it to repair the product?
If amazon.com sends the wrong book, how hard is it to get this error corrected? How long did it take a credit card company to correct an error in your bill?

Aesthetics What does the product look like?
Do you like the box in which Shoes are packaged?

Features What will the product do beyond the basics? Added features
Spreadsheet software package that has built in statistical analysis features

Perceived quality What is the reputation of the company selling this product? Prefer to use a particular airline in which the flight almost always arrive on time and does not lose or damage the luggage

Conformance to standards
Is the product made exactly as the designer intended? How well does the hood fit on a new car?

Definitions of Quality Quality means fitness for use - quality of design - quality of conformance Quality is inversely proportional to variability.

Quality of design Automobile differences
Materials used in construction Specifications of the components Reliability of drive train components Reliability of accessories

Quality of conformance
How well does the product conform to the specifications required by the design? Quality of conformance is influenced by Choice of manufacturing processes Training of the workers Supervision of the workers Motivation of the workers Quality-assurance procedures that were used

Quality is inversely proportional to variability
Toyota versus Ford That transmission noise (or lack of it) is wasted energy caused by components that don’t fit precisely Imprecise components lead to wear and tear

1-1.1 Dimensions of Quality – Transmission Example
Your customer does not see the mean of your process, he only sees the variability around that target that you have not removed

Quality Improvement Quality improvement is the reduction of variability in processes and products. Alternatively, quality improvement is also seen as “waste reduction.”

1-1.2 Quality Engineering Terminology
Quality Characteristics Physical - length, weight, voltage, viscosity Sensory - taste, appearance, color Time Orientation - reliability, durability, serviceability

Quality engineering is the set of operational, managerial, and engineering activities that a company uses to ensure that the quality characteristics of a product are at the nominal or required levels.

Inherent variability No two products are ever identical
Slight differences in materials Slight differences in machine settings Slight differences in operators Slight differences in ambient temperature during production

Two types of data: Attributes Data - discrete data, often in the form of counts Variables Data - continuous measurements such as length, weight Both types will be discussed in the course

Specifications Quality characteristics being measured are often compared to standards or specifications. Desired measure for the quality characteristic Example: Shaft and bearing Too loose the assembly will wobble causing wear Too tight, and the assembly can not be made, no clearance

Specifications Nominal or target value Desired value for a quality characteristic

Specifications Upper Specification Limit (USL) Lower Specification Limit (LSL) Largest and smallest allowable values

Specifications Upper Specification Limit (USL) Lower Specification Limit (LSL) One-sided The compression strength of a Coke bottle must be greater than a given psi value Two-sided The weight of potato chips in the bag can be between 7.8 and 8.3 ounces

Design specifications
Over the wall From design to manufacturing Cooperatively Between design and manufacturing

When a component or product does not meet specifications, it is considered to be nonconforming. A nonconforming product is considered defective if it has one or more nonconformities that may seriously affect the safe or effective use of the product.

A new car is purchased A bubble in the paint on the door is noticed Nonconformity – yes Defective car - no

Concurrent Engineering Team approach to design. Specialists from manufacturing, quality engineering, management, etc. work together for product or process improvement.

1-2. A Brief History of Quality Control and Improvement
(Refer to Table 1-1) Frederick Taylor (1875) introduces the principles of scientific management; dividing work into tasks with standardized procedures The Gilbreths developed standard times and motions (1920s)

(Refer to Table 1-1) Walter Shewhart (1924) introduced statistical control chart concepts and QC begins Dodge and Romig (1928), Bell Labs, develop acceptance sampling as an alternate to 100% inspection During WW II the shells didn’t fit the howitzers leading to development of MIL-STDs

(Refer to Table 1-1) The American Society for Quality Control formed in 1946 [now known as the American Society for Quality (ASQ)] 1950s and 1960s saw an increase in reliability engineering, experimental design, and statistical quality control

(Refer to Table 1-1) Competition from foreign industries (Japan) increases during the 1970s and 1980s. Statistical methods for quality improvement use increases in the United States during the 1980s

Statistical Methods Statistical process control (SPC) Control charts, plus other problem-solving tools Useful in monitoring processes, reducing variability through elimination of assignable causes On-line technique Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Designed experiments (DOX)
Experimental design is an approach to systematically varying the controllable input factors in the process then determining the effect these factors have on the output responses. Discovering the key factors that influence process performance Process optimization Off-line technique Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Acceptance Sampling Acceptance sampling is the inspection and classification of a sample of the product selected at random from a larger batch or lot and the ultimate decision about disposition of the lot. Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Walter A. Shewart ( ) Trained in engineering and physics Long career at Bell Labs Developed the first control chart about 1924 Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Quality cannot be inspected into the product
When the organization realizes this, process improvement efforts begin Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

The objective Systematic reduction of variability
First, by using acceptance sampling Then, by using SPC Finally, by using DOE We don’t stop when requirements are met Further reductions in variability lead to better performance

1.4 Management Aspects of Quality Improvement Effective management of quality requires the execution of three activities: Quality Planning Quality Assurance Quality Control and Improvement Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

1-4.1 Quality Philosophy and Management Strategies
Three Important Leaders W. Edwards Deming - Emphasis on statistical methods in quality improvement Joseph Juran - Emphasis on managerial role in quality implementation Armand V. Feigenbaum - Emphasis on organizational structure

1.4.1 Quality Philosophy and Management Strategy W. Edwards Deming Taught engineering, physics in the 1920s, finished PhD in 1928 Met Walter Shewhart at Western Electric Long career in government statistics, USDA, Bureau of the Census During WWII, he worked with US defense contractors, deploying statistical methods Sent to Japan after WWII to work on the census Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Deming Deming was asked by JUSE to lecture on statistical quality control to management Japanese adopted many aspects of Deming’s management philosophy Deming stressed “continual never-ending improvement” Deming lectured widely in North America during the 1980s; he died 24 December 1993 Demanded management commitment to use statistical methods Deming Prize in Japan For quality improvement Deming was a harsh critic of US management practices Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Deming’s 14 Points 1. Create constancy of purpose toward improvement 2. Adopt a new philosophy, recognize that we are in a time of change, a new economic age 3. Cease reliance on mass inspection to improve quality 4. End the practice of awarding business on the basis of price alone 5. Improve constantly and forever the system of production and service 6. Institute training 7. Improve leadership, recognize that the aim of supervision is help people and equipment to do a better job 8. Drive out fear 9. Break down barriers between departments Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Note that the 14 points are about change
14 Points cont’d 10. Eliminate slogans and targets for the workforce such as zero defects 11. Eliminate work standards 12. Remove barriers that rob workers of the right to pride in the quality of their work 13. Institute a vigorous program of education and self-improvement 14. Put everyone to work to accomplish the transformation Note that the 14 points are about change Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

1. Create a constancy of purpose
Focus on the improvement of products and services Constantly improve product design and performance Invest in R&D Innovate

2. Adopt a new philosophy Eliminate defective products
It costs as much to produce a defective unit as a good one Dealing with scrap and rework is very expensive

3. Don’t rely on inspection
Inspection only sorts out defectives Already have paid to produce them Inspection is too late in the process It’s also ineffective Prevent defectives through process improvement

4. Don’t award business on price alone
Consider supplier quality as well Give preference to those suppliers that demonstrate process control and process capability

5. Focus on continuous improvement
Involve the workforce Use statistical techniques

6. Invest in training Everyone should be trained in the technical aspects of their job, QC, and process improvement Workers should be encouraged to put this training to use

7. Practice modern supervision methods
Help the employees improve the system in which they work

8. Drive out fear Create an environment where the workers will ask questions, report problems, or point out conditions that are barriers to quality

9. Break down the barriers
Break down the barriers between the functional areas of the business Only through teamwork can quality and process improvement take place

10. Eliminate targets and slogans
Useless without a plan for the achievement of the target or goal Instead, improve the system and provide information on that

11. Eliminate quotas Numerical quotas and work standards often conflict with quality control

12. Encourage employees to do their job
Remove the barriers Listen to the workers The person doing the job knows more about it than anyone else

13. Have ongoing education and training
Teach them simple yet powerful statistical techniques Use the basic SPC tools, particularly the control chart

14. Involve top management
Management should be advocates for these points

Deming’s Deadly Diseases
Lack of constancy of purpose Emphasis on short-term profits Performance evaluation, merit rating, annual reviews Mobility of management Running a company on visible figures alone Excessive medical costs for employee health care Excessive costs of warrantees Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Deming’s Obstacles to Success

Joseph M. Juran Born in Romania ( ), immigrated to the US Worked at Western Electric, influenced by Walter Shewhart Juran Institute is still an active organization promoting the Juran philosophy and quality improvement practices Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Dr. Joseph Juran A founder of SQC Co-author of QC Handbook (1957)
His philosophy is based on management of the quality function

The Juran Trilogy Planning Control Improvement These three processes are interrelated Control versus breakthrough Project-by-project improvement Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Armand Feigenbaum Author of Total Quality Control, promoted overall organizational involvement in quality, Three-step approach emphasized quality leadership, quality technology, and organizational commitment Says that QC should be concentrated in a specialized department Conflicts with Deming on this point Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

1-4.1 Quality Philosophy and Management Strategies
Total Quality Management (TQM) Quality Standards and Registration ISO 9000 Six Sigma Just-In-Time, Lean Manufacturing, Poka-Yoke, etc.

TQM It is a strategy for implementing and manageingt quality improvement activities on an organizationwide basis Began in the early 80s based on the philosophies of Deming and Juran Evolved into wide spectrum of ideas Participation in quality groups Work culture Customer focus Supplier quality improvement Cross-functional teams concerned with quality

TQM A success? Why not? Moderately
Not enough concern for reduction of variability Ineffective training conducted by HR people No knowledge of what is important Success measured by % of workforce trained Management not committed

General Reasons for the lack of conspicuous success of TQM
lack of top down, high level of management commitment and involvement. inadequate use of statistical methods and insufficient recognition of variability reduction as a prime objective General as opposed to specific business- results-oriented objectives To much emphasis on widespread training as opposed to focused technical education

More reasons for lack of success
Zero defects, value engineering, quality is free Programs with no emphasis on reducing variability Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Quality Systems and Standards

The ISO certification process focuses heavily on quality assurance, without sufficient weight given to quality planning and quality control and improvement Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

ISO 9000 Quality system oriented Say what you do, do what you say
Much effort devoted to paperwork and bookkeeping Not much to reducing variability and improving processes

ISO 9000 US$40 billion annual business worldwide
Registrars, auditors, consultants Plus, 1000s of hours of internal costs Effective? Does it reduce variability?

The Malcolm Baldrige National Quality Award
The MBNQA process is a valuable assessment tool See Table 1-3 for Performance Excellence Criteria and point values Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Six Sigma Developed by Motorola in the late 80s
Consider that + 3s provides in each tail, or in the two tales So, in 1 million parts, 2700 would be defective

Six Sigma Consider an assembly of 100 parts that must all function for the assembly to function .9973 x x … = (.9973)100 = .7631 Thus, about 23.7% of the products under 3s will fail Not usually an acceptable situation

Pilot’s Six-Sigma Performance
Width of landing strip 1/2 Width of landing strip If pilot always lands within 1/2 the landing strip width, we say that he has Six-sigma capability.

Six Sigma But, + 6s results in 0.999999998 inside specs
( )100 = Or, 2 parts/billion defective i.e., 0.2 ppm Much better than + 3s

Why “Quality Improvement” is Important: A Simple Example
A visit to a fast-food store: Hamburger (bun, meat, special sauce, cheese, pickle, onion, lettuce, tomato), fries, and drink. This product has 10 components - is 99% good okay? Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Six sigma Process performance is not predictable unless the process behavior is stable If the mean is drifting around, and ends up as much as 1.5 standard deviations off target, a prediction of 3.4 ppm defective may not be very reliable Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Six Sigma Has moved beyond Motorola Has come to encompass much more
Has become a method for improving corporate business performance Companies involved in Six Sigma use teams that work on projects involving quality and costs

Six sigma Companies involved in a six sigma effort utilize specially trained individuals, called Green Belts (GBs), Black Belts (BBs), and Master Black Belts (MBBs) The “belts” have specialized training and education on statistical method and the quality and process improvement tools. Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Six Sigma Specialized roles for people; Champions, Master Black belts, Black Belts, Green Belts Top-down driven (Champions from each business) BBs and MBBs have responsibility (project definition, leadership, training/mentoring, team facilitation) Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

The leadership team is the executive responsible for that business unit and appropriate members of his /her staff and direct reports. Each project has a champion, a business leader whose job is to facilitate project identification and selection, identify Black Belts and other team members, remove barrier, make sure that the resources are available, and conduct regular meeting with the team or Black Belt. Black Belts are team leaders that are involved in the actual project completion activities. Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Green Belts have less training and experience. A Master Black Belt is a technical leader and may work with the champion and the leader team in project identification and selection, project reviews, consulting with Black Belts on technical issues, and training of Green Belts and Black Belts Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Six Sigma A disciplined and analytical approach to process and product improvement Involves a five-step process (DMAIC) : Define Measure Analyze Improve Control Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

DMAIC Solves Problems by Using Six Sigma Tools
DMAIC is a problem solving methodology Closely related to the Shewhart Cycle Use this method to solve problems: Define problems in processes Measure performance Analyze causes of problems Improve processes  remove variations and non-value-added activities Control processes so problems do not recur Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Six Sigma Three Generations
Generation I: focused on defect elimination and basic variability reduction (such as Motorola) Generation II: tie variability and defect reduction to projects and activities that improved business performance through cost reduction (such as General Electric) Generation III: additional focus of creation value throughout the organization and for its stakeholders (such as Caterpillar and Bank of America). Creating value can take many forms: increasing stock prices, job retention or expansion, expanding markets for company products/ services, developing new products/ services that reach new and broader market, and increasing the customer satisfaction. Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Six Sigma Focus Initially in manufacturing Commercial applications Banking Finance Public sector Services Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Design for Six Sigma (DFSS)
Taking variability reduction upstream from manufacturing (or operational six sigma) into product design and development Six sigma is used to achieve operational excellence, while DFSS is focused on improving business results by increasing the sales revenue generated from new products and services and finding new applications or opportunities for existing ones Every design decision is a business decision Once the a product is designed and released to manufacturing, it is almost impossible for the manufacturing organization to make it better Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Design for Six Sigma (DFSS)
An important gain from DFSS is the reduction of development lead time; that is, the cycle time to commercialize new technology and get the resulting new products to market. DFSS is directly focused on increasing value in the organization DMAIC is applicable. Also some organizations use DMADV: Define, Measure, Analyze, Design, and Verify. Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

DFSS DFSS is required to focus on customer requirements while simultaneously keeping process capability in mind Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

DFSS Throughout the DFSS process, it is important that the following points to kept in mind Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Lean Systems Focuses on elimination of waste Long cycle times Long queues – in-process inventory Inadequate throughput Rework Non-value-added work activities Makes use of many of the tools of operations research and industrial engineering Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Six Sigma More successful than TQM
More managerial commitment Involves costs But, it’s still another slogan and program Better to train everyone in quality tools and make efforts to reduce variability

JIT, Poka-Yoke, etc. Programs that devote too little attention to variance reduction For example, JIT It is impossible to reduce the in-process inventory when a large and unpredicted fraction of the process output is defective and where there are significant uncontrolled sources of variability

1-4.2 The Link Between Quality and Productivity
Effective quality improvement can be instrumental in increasing productivity and reducing cost. The cost of achieving quality improvements and increased productivity is often negligible.

An example Data 100 parts/day are manufactured 75% are conforming
60% of the nonconforming can be reworked for a cost of $4 Remainder are scrapped Direct manufacturing cost is $20/part

An example Cost/conforming part
[$20 (100) + $4 (15)]/90 = $22.89 Note that the yield is 90 conforming/day

An example New process introduced Cost/conforming part
Fallout is 5% 60% can be reworked Cost/conforming part [$20 (100) + $4 (3)]/98 = $20.53 Note that the yield is 98 conforming/day Up from 90/day And, costs are reduced by 10.3%

1-4.3 Quality Costs Quality Costs are those categories of costs that are associated with producing, identifying, avoiding, or repairing products that do not meet requirements. These costs are: Prevention Costs Appraisal Costs Internal Failure Costs External Failure Costs

Quality costs Prevention costs: those costs associated with effort in design and manufacturing that are directed toward the prevention of nonconformance “ make it right the first time” Quality planning and engineering New products review Product/process design Process control Burn-in Training Quality data acquisition and analysis

Appraisal costs Costs associated with measuring, evaluating, or auditing products, components, and purchased materials to insure conformance to the standards that have been imposed Costs of activities designed to ensure quality or discover defects Inspection and test of incoming material Product inspection and test Materials and services consumed Maintaining accuracy of test equipment

Internal failure costs
Costs incurred to fix problems that are detected before the product/service is delivered to the customer Scrap Rework Retest Failure analysis Downtime Yield losses Downgrading

External failure costs
All costs incurred to fix problems that are detected after the product/service is delivered to the customer. Complaint adjustment Returned product/material Warranty charges Liability costs Indirect costs

Leverage effect Dollars invested in prevention and appraisal have a payoff in reducing dollars incurred in internal and external failures that exceeds the original investment Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Pareto analysis Cost reduction through identifying improvement opportunities Identifying quality costs by category, or by product, or by type of defect or nonconformity

Monthly quality costs for PCB assembly
Type of defect % of total defects Scrap & rework costs Insufficient solder 42 $37,500 Misaligned components 21 $12,000 Defective components 15 $8,000 Missing components 10 $5,100 Cold solder joints 7 $5,000 All other causes 5 $4,600 Total 100 $72,200

Pareto analysis Insufficient solder Work on that defect first
42% of defects and 52% of scrap and rework costs Work on that defect first Most of the cost reductions will come from attacking the few problems that are responsible for the majority of the quality costs

Quality Costs Input Output

Appraisal or prevention
Many firms spend far too much of their quality management budget on appraisal and not enough on prevention Money spent on prevention has a much better payoff than money spent on appraisal

1-4.4 Legal Aspects of Quality
The re-emergence of quality assurance as an important business strategy is in part a result of Consumerism Product Liability

Consumerism Virtually every product line of today is superior to that of yesterday But, many consumers see it otherwise Consumer tolerance for minor defects & aesthetic problems has decreased considerably Blemishes, surface-finish defects, noises, appearance problems

Consumerism Many manufacturers introduce new designs before they are fully evaluated and tested To remain competitive Unproved designs

Product liability Manufacturers and sellers are likely to incur a liability when they have been unreasonably careless or negligent in what they have designed, or produced, or how they have produced it

More stringent: Strict liability
1. There is a strong responsibility for both manufacturer and merchandiser requiring immediate responsiveness to unsatisfactory quality through product service, repair, or replacement of defective product Extends into the period of use by the consumer By producing the product, manufacturer and seller must accept responsibility for use

More stringent: Strict liability
2. All advertising statements must be supportable by valid company quality or certification data

1-4.5 Implementing Quality Improvement
Strategic management of quality Almost all successful efforts have been management-driven. Too much emphasis on registration and certification programs (ISO, QS) Insufficient focus on quality planning and design, quality improvement, overemphasis on quality assurance Poor use of available resources

Implementing Quality Improvement
A strategic management process, focused along the eight dimension of quality Suppliers and supply chain management must be involved Must focus on all three components: Quality Planning, Quality Assurance, and Quality Control and Improvement Chapter 1 Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

Copyright (c) 2009 John Wiley & Sons, Inc.

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