Chapter 11Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery....
-
Upload
byron-colding -
Category
Documents
-
view
231 -
download
0
Transcript of Chapter 11Introduction to Statistical Quality Control, 6 th Edition by Douglas C. Montgomery....
Chapter 1 1Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Chapter 1
Quality Improvement in the Modern Business Environment
1-1. The Meaning of Quality and Quality Improvement
1-1.1 Dimensions of Quality
1-1.2 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?
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.
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
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.”
1-1.2 Quality Engineering Terminology
Quality Characteristics
• Physical - length, weight, voltage, viscosity
• Sensory - taste, appearance, color
• Time Orientation - reliability, durability, serviceability
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.
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
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
1-1.2 Quality Engineering Terminology
Specifications Quality characteristics being measured are often
compared to standards or specifications.Desired measure for the quality characteristicExample: Shaft and bearing
Too loose the assembly will wobble causing wear
Too tight, and the assembly can not be made, no clearance
1-1.2 Quality Engineering Terminology
Specifications• Nominal or target value
– Desired value for a quality characteristic
1-1.2 Quality Engineering Terminology
Specifications• Upper Specification Limit (USL)
• Lower Specification Limit (LSL)– Largest and smallest allowable values
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
Design specifications
• Over the wall– From design to manufacturing
• Cooperatively– Between design and manufacturing
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.
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
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.
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)
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
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
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
Chapter 1 35Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
1.3 Statistical Methods for Quality Control and Improvement
Chapter 1 36Introduction to Statistical Quality Control, 6th 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
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 37Introduction 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 38Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Chapter 1 39Introduction to Statistical Quality Control, 6th 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
Chapter 1 40Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Chapter 1 41Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Chapter 1 42Introduction 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
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
Chapter 1 44Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Chapter 1 45Introduction to Statistical Quality Control, 6th 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
Chapter 1 46Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Chapter 1 47Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Chapter 1 48Introduction 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
Chapter 1 50Introduction to Statistical Quality Control, 6th 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
Chapter 1 51Introduction 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 52Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Deming’s 14 Points1. Create constancy of purpose toward improvement 2. Adopt a new philosophy, recognize that we are in a time of
change, a new economic age3. Cease reliance on mass inspection to improve quality4. End the practice of awarding business on the basis of price
alone5. Improve constantly and forever the system of production and
service6. Institute training7. Improve leadership, recognize that the aim of supervision is
help people and equipment to do a better job8. Drive out fear9. Break down barriers between departments
Chapter 1 53Introduction to Statistical Quality Control, 6th 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 standards12. Remove barriers that rob workers of the right to pride in the
quality of their work13. Institute a vigorous program of education and self-
improvement14. Put everyone to work to accomplish the transformation
Note that the 14 points are about change
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
Chapter 1 68Introduction to Statistical Quality Control, 6th 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
Chapter 1 69Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Chapter 1 70Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Deming’s Obstacles to Success
Chapter 1 71Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Chapter 1 72Introduction to Statistical Quality Control, 6th 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
Dr. Joseph Juran
• A founder of SQC
• Co-author of QC Handbook (1957)
• His philosophy is based on management of the quality function
Chapter 1 74Introduction to Statistical Quality Control, 6th 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
Chapter 1 75Introduction 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
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?– 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
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
More reasons for lack of success
– Zero defects, value engineering, quality is free• Programs with no emphasis on reducing variability
Chapter 1 80Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Chapter 1 81Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Quality Systems and Standards
Chapter 1 82Introduction to Statistical Quality Control, 6th 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
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
Chapter 1 84Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
ISO 9000
• US$40 billion annual business worldwide– Registrars, auditors, consultants
• Plus, 1000s of hours of internal costs
• Effective?– Does it reduce variability?
Chapter 1 86Introduction to Statistical Quality Control, 6th 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
Chapter 1 87Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Chapter 1 88Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Chapter 1 89Introduction 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 + 3 provides 0.00135 in each tail, or 0.00270 in the two tales
• So, in 1 million parts, 2700 would be defective
Chapter 1 91Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
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 3will fail
• Not usually an acceptable situation
93
Width of landing strip1/2 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, + 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
Chapter 1 95Introduction to Statistical Quality Control, 6th 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?
10
4
12
{Single meal good} (0.99) 0.9044
Family of four, once a month: {All meals good} (0.9044) 0.6690
{All visits during the year good} (0.6690) 0.0080
P
P
P
10 4
12
{single meal good} (0.999) 0.9900, {Monthly visit good} (0.99) 0.9607
{All visits in the year good} (0.9607) 0.6186
P P
P
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 96Introduction 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 98Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Chapter 1 99Introduction 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 100Introduction 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 101Introduction 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 102Introduction 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 103Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Chapter 1 104Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
DMAIC Solves Problems by UsingSix 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
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 105Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
Chapter 1 106Introduction 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
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 107Introduction 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 108Introduction 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 109Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
DFSS
Chapter 1 110Introduction to Statistical Quality Control, 6th 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
Chapter 1 111Introduction 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 112Introduction 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– 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
Chapter 1 124Introduction to Statistical Quality Control, 6th Edition by Douglas C. Montgomery.Copyright (c) 2009 John Wiley & Sons, Inc.
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 125Introduction 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– 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
Quality CostsInput
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
1. Consumerism
2. 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
Chapter 1 138Introduction to Statistical Quality Control, 6th 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