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Chapter 11Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

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Presentation on theme: "Chapter 11Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc."— Presentation transcript:

1 Chapter 11Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

2 Chapter 1 Quality Improvement in the Modern Business Environment

3 1-1. The Meaning of Quality and Quality Improvement 1-1.1 Dimensions of Quality 1-1.2 Quality Engineering Technology

4 1-1.1 Dimensions of Quality Performance Reliability Durability Serviceability Aesthetics Features Perceived Quality Conformance to standards

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

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

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

8 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?

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

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

11 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

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

13 1-1.1 Dimensions of Quality Definitions of Quality Quality means fitness for use - quality of design - quality of conformance Quality is inversely proportional to variability.

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

15 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

16 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

17 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

18 1-1.1 Dimensions of Quality Quality Improvement Quality improvement is the reduction of variability in processes and products. Alternatively, quality improvement is also seen as “waste reduction.”

19 1-1.2 Quality Engineering Terminology Quality Characteristics Physical - length, weight, voltage, viscosity Sensory - taste, appearance, color Time Orientation - reliability, durability, serviceability

20 1-1.2 Quality Engineering Terminology 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.

21 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

22 1-1.2 Quality Engineering Terminology 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

23 1-1.2 Quality Engineering Terminology 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

24 1-1.2 Quality Engineering Terminology Specifications Nominal or target value –Desired value for a quality characteristic

25 1-1.2 Quality Engineering Terminology Specifications Upper Specification Limit (USL) Lower Specification Limit (LSL) –Largest and smallest allowable values

26 1-1.2 Quality Engineering Terminology 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

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

28 1-1.2 Quality Engineering Terminology 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.

29 1-1.2 Quality Engineering Terminology A new car is purchased A bubble in the paint on the door is noticed –Nonconformity – yes –Defective car - no

30 1-1.2 Quality Engineering Terminology Concurrent Engineering Team approach to design. Specialists from manufacturing, quality engineering, management, etc. work together for product or process improvement.

31 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)

32 1-2. A Brief History of Quality Control and Improvement (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

33 1-2. A Brief History of Quality Control and Improvement (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

34 1-2. A Brief History of Quality Control and Improvement (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

35 Chapter 135Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc. 1.3 Statistical Methods for Quality Control and Improvement

36 Chapter 136Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc. 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

37 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 137Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

38 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 138Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

39 Chapter 139Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc. Walter A. Shewart (1891-1967) Trained in engineering and physics Long career at Bell Labs Developed the first control chart about 1924

40 Chapter 140Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

41 Chapter 141Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

42 Chapter 142Introduction to Statistical Quality Control, 6 th 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

43 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

44 Chapter 144Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

45 Chapter 145Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc. Effective management of quality requires the execution of three activities: 1.Quality Planning 2.Quality Assurance 3.Quality Control and Improvement 1.4 Management Aspects of Quality Improvement

46 Chapter 146Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

47 Chapter 147Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

48 Chapter 148Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

49 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

50 Chapter 150Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc. 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 1.4.1 Quality Philosophy and Management Strategy

51 Chapter 151Introduction to Statistical Quality Control, 6 th 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

52 Chapter 152Introduction to Statistical Quality Control, 6 th 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

53 Chapter 153Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc. 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

54 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

55 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

56 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

57 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

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

59 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

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

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

62 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

63 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

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

65 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

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

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

68 Chapter 168Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc. Deming’s Deadly Diseases 1.Lack of constancy of purpose 2.Emphasis on short-term profits 3.Performance evaluation, merit rating, annual reviews 4.Mobility of management 5.Running a company on visible figures alone 6.Excessive medical costs for employee health care 7.Excessive costs of warrantees

69 Chapter 169Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

70 Chapter 170Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc. Deming’s Obstacles to Success

71 Chapter 171Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

72 Chapter 172Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc. Joseph M. Juran Born in Romania (1904- 2008), 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

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

74 Chapter 174Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc. The Juran Trilogy 1.Planning 2.Control 3.Improvement These three processes are interrelated Control versus breakthrough Project-by-project improvement

75 Chapter 175Introduction to Statistical Quality Control, 6 th 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

76 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.

77 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

78 TQM A success? –Moderately Why not? –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

79 General Reasons for the lack of conspicuous success of TQM 1.lack of top down, high level of management commitment and involvement. 2.inadequate use of statistical methods and insufficient recognition of variability reduction as a prime objective 3.General as opposed to specific business- results-oriented objectives 4.To much emphasis on widespread training as opposed to focused technical education

80 More reasons for lack of success –Zero defects, value engineering, quality is free Programs with no emphasis on reducing variability Chapter 180Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

81 Chapter 181Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc. Quality Systems and Standards

82 Chapter 182Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc. The ISO certification process focuses heavily on quality assurance, without sufficient weight given to quality planning and quality control and improvement

83 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

84 Chapter 184Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

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

86 Chapter 186Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc. The MBNQA process is a valuable assessment tool See Table 1-3 for Performance Excellence Criteria and point values The Malcolm Baldrige National Quality Award

87 Chapter 187Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

88 Chapter 188Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

89 Chapter 189Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

90 Six Sigma Developed by Motorola in the late 80s Consider that + 3  provides 0.00135 in each tail, or 0.00270 in the two tales So, in 1 million parts, 2700 would be defective

91 Chapter 191Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

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

93 93 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.

94 Six Sigma But, + 6  results in 0.999999998 inside specs –(0.999999998) 100 =.9999998 –Or, 2 parts/billion defective i.e., 0.2 ppm –Much better than + 3 

95 Chapter 195Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc. 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?

96 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 196Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

97 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

98 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 198Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

99 Chapter 199Introduction to Statistical Quality Control, 6 th 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)

100 Chapter 1100Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

101 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 1101Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

102 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 1102Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

103 Six Sigma A disciplined and analytical approach to process and product improvement Involves a five-step process (DMAIC) : –Define –Measure –Analyze –Improve –Control Chapter 1103Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

104 Chapter 1104Introduction to Statistical Quality Control, 6 th 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

105 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 1105Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

106 Chapter 1106Introduction to Statistical Quality Control, 6 th 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

107 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 1107Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

108 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 1108Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

109 DFSS DFSS is required to focus on customer requirements while simultaneously keeping process capability in mind Chapter 1109Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

110 DFSS Chapter 1110Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc. Throughout the DFSS process, it is important that the following points to kept in mind

111 Chapter 1111Introduction to Statistical Quality Control, 6 th 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

112 Chapter 1112Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

113 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

114 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

115 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.

116 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

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

118 An example New process introduced –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%

119 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

120 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

121 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

122 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

123 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

124 Chapter 1124Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

125 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 1125Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc.

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

127 Monthly quality costs for PCB assembly Type of defect% of total defectsScrap & rework costs Insufficient solder42$37,500 Misaligned components21$12,000 Defective components15$8,000 Missing components10$5,100 Cold solder joints7$5,000 All other causes5$4,600 Total100$72,200

128 Pareto analysis Insufficient solder –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

129 129 Quality Costs Input Output

130 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

131 1-4.4 Legal Aspects of Quality The re-emergence of quality assurance as an important business strategy is in part a result of 1.Consumerism 2.Product Liability

132 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

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

134 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

135 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

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

137 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

138 Chapter 1138Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery. Copyright (c) 2009 John Wiley & Sons, Inc. 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 Implementing Quality Improvement


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