1. Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

2. Learning Objectives Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

3. What is Quality?
Quality definition of American Society for Quality (ASQ):
A subjective term for which each person has his or her own definition.
In technical usage, quality can have two meanings:
The characteristics of a product or service that are relevant to the ability to satisfy stated or implied needs.
(doing the right things)
A product or service free of deficiencies.
(doing things right all the time)
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013  John Wiley & Sons, Inc.

4. Will the product do the intended job?
Dimension
Meaning and example
Performance
Will the product do the intended job?
Primary product characteristics, such as brightness of the picture
Features
Secondary characteristics, added features (features beyond the basic performance), such as remote control
Conformance to standards
Is the product made exactly as the designer intended?
Meeting specifications or industry standards, quality of work
Manufactured parts that do not exactly meet the designer’s requirements may not perform as the designer intended and can cause significant quality problems.
Reliability
How often does the product fail?
Consistency of performance, average time for the unit to fail
You should expect that an automobile will require occasional repair, but if the car requires frequent repair, we say that it is unreliable.
Durability
How long does the product last?
Useful life, effective service life of the product, including repair
Automobile and major appliance industries are examples of businesses where this dimension is very important to most customers.
Serviceability
How easy is it to repair the product?
Resolution of problems and complaints, ease of repair
How long did it take a credit card company to correct an error in your bill?
Aesthetics
What does the product look like?
Sensory characteristics, such as exterior finish
Perceived quality
What is the reputation of the company or its product?
Past performance and other intangibles, such as ranking first
Sources: Yang, K., El-Haik, B.S. (2009) Design for Six Sigma: A Roadmap for Product Development. 2nd ed. McGraw-Hill.
Montgomery, D.C. (2013) Statistical Quality Control, 7th ed. John Wiley & Sons, Inc.

5. Traditional Approach to Quality
Conformance to specifications:
All products that meet specifications are equally good.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

6. This is a modern definition of quality.
This definition implies that if variability in the important characteristics of a product decreases, the quality of the product increases.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013  John Wiley & Sons, Inc.

7. The Television Example
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

8. The Transmission Example
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

9. The television and transmission examples illustrate the utility of this definition
An equivalent definition is that quality improvement is the elimination of waste. This is useful in service or transactional businesses.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

10. Variation
Sources of variability include differences in materials, differences in the performance and operation of the manufacturing equipment , differences in the way the operators perform their tasks
Many sources of uncontrollable variation exist in any process
Excessive variation results in product failures, unhappy customers, and unnecessary costs
Statistical methods can be used to identify and quantify variation to help understand it and lead to improvements

11. 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 and that the variability around these desired levels is minimum.

12. Off-line quality control
Various Stages of the Life Cycle of a Product
Product planning and design
Production process design
Production
Costumer usage
Off-line quality control
On-line quality control
Warranty and service
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013  John Wiley & Sons, Inc.

13. Quality characteristics may be of several types:
Every product has a number of elements that jointly describe what the user or consumer thinks of as quality. These parameters are often called quality characteristics. Sometimes these are called critical-to-quality (CTQ) characteristics.
Quality characteristics may be of several types:
Physical: length, weight, voltage, viscosity
Sensory: taste, appearance, color
Time Orientation: reliability, durability, serviceability
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013  John Wiley & Sons, Inc.

14. Since variability can only be described in statistical terms, statistical methods play a central role in quality improvement efforts.
In the application of statistical methods to quality engineering, it is typical to classify quality characteristics as
Attributes: discrete data
Variables: continuous measurements, such as length, voltage, or viscosity.
Statistical-based quality engineering tools for dealing with both types of data.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

15. Measurement Scales
How variables are measured or scaled influences the type of permissible mathematical operations and statistical analyses we perform.
Four types of measurement scales (Stevens, 1968):
Nominal scale
Ordinal scale
Interval scale
Ratio scale

16. Measurement Scales
Nominal scale: A scale that implies only mutually exclusive groups/categories.
Gender: female, male
Identity numbers
Although the categories can be labeled by numbers these numbers just distinguish one category from another without carrying quantitative information.
Ordinal scale: A scale in which categories have a natural ordering (however, intervals/differences between the categories are not numerically meaningful)
Grades: AA, BA, BB, CC, DC, DD, FF
Sizes: XS, S, M, L, XL
Rank at the end of a race: 1st, 2nd, 3rd
Mathematical operations are meaningless. Only logical operations such as =,≠,<,> are permitted.

17. Measurement Scales
Interval scale: In the interval scale, the difference between any two adjacent categories is equal to the difference between any other two adjacent categories.
A scale with a unit of measurement. Zero point is arbitrary, it does not denote the absence of whatever characteristics is being observed.
Temperature in Celsius and Fahrenheit
0°C does not mean there is no temperature. On the Celsius scale, the zero value is taken as the point at which water freezes and the 100°C value when water begins to boil at the sea level and between these extreme values the scale is divided into hundred equal divisions.
One can say that a temperature of 40°C is higher than a temperature of 30°C by 10°C, and that an increase from 20°C to 40°C is twice as much as an increase from 30°C to 40°C. But it does not make sense to say that 20°C is twice as hot as 10°C since the scale does not have an absolute zero.
90°F is not six times hotter than 15°F.
Addition and subtraction are permitted mathematical operations.

18. Measurement Scales
Ratio scale: A scale with a measurement unit and an absolute zero (zero means there is none of the quantity being measured)
Temperature in Kelvin (zero on the Kelvin scale means absolute zero, the case in which all motion stops)
Weight in kilograms
Length in centimeters or inches
Age in years
When a variable is measured on a ratio scale, the ratio of two numbers is meaningful: 30m. is twice as long as 15m.
Addition, subtraction, multiplication and division are meaningful (permissible mathematical operations)

19. Measurement Scales
Ratio and interval scales convey more information that ordinal and nominal scales.
The same property can be measured on different scales:
Age can be measured as ratio (in years) or ordinal (young, middle, old)
Scores at a race: 10 seconds, 15 seconds, 107 seconds; ranks: 1st, 2nd, 3rd

20. Measurement Scales
Data in nominal or ordinal are known as categorical or qualitative data.
Data in interval or ratio scale are known as numerical or quantitative data.

21. Target or nominal value
Quality characteristics are often evaluated relative to specifications
Lower specification limit
Upper specification limit
Specifications are usually the result of the engineering design process for the product
A product that fails to meet one or more of its specifications is called nonconforming.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

22. The Link between Quality and Productivity
Consider the manufacture of a mechanical component used in a copier machine. The parts are manufactured in a machining process at a rate of approximately 100 parts per day.
About 75% of the process output conforms to specifications.
About 60% of the fallout (the 25% nonconforming) can be reworked into an acceptable product, and the rest must be scrapped.
The direct manufacturing cost through this stage of production per part is approximately $20.
Parts that can be reworked incur an additional processing charge of $4.
What is the manufacturing cost per good part produced?

23. The Link between Quality and Productivity
An engineering study of this process reveals that excessive process variability is responsible for the extremely high fallout. A new statistical process-control procedure is implemented that reduces variability.
Process fallout decreases from 25% to 5%.
Of the 5% fallout produced, about 60% can be reworked, 40% are scrapped.
Installation of statistical process control and the reduction of variability that follows result in a 10.3% reduction in manufacturing cost.
Productivity is up by 9%. This amounts to an increase in production capacity of 9%, without any additional investment in equipment, workforce, or overhead.

24. Statistical Methods for Quality Control and Improvement
Production process inputs and outputs

25. Statistical Methods for Quality Control and Improvement
Statistical process control (SPC):Control charts, plus other problem-solving tools
Control charts:
Useful in monitoring processes, reducing variability through elimination of assignable causes,
applied to the output variable(s) in a system
On-line technique
A typical control chart

26. Walter A. Shewart (1891-1967) Trained in engineering and physics
Long career at Bell Labs
Developed the first control chart about 1924
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

27. Statistical Methods for Quality Control and Improvement
Designed experiments (DOE)
Discovering the key factors that influence process performance
An approach to systematically varying controllable input factors in the process and determining the effect of these factors on the output product parameters.
Process optimization, crucial on reducing variability
Off-line technique

28. Statistical Methods for Quality Control and Improvement
Acceptance Sampling
Connected with the inspection and testing of product
Inspection can occur at many points in a process
Modern quality assurance systems usually place less emphasis on acceptance sampling and attempt to make statistical process control and designed experiments the focus of their efforts. Acceptance sampling does not have any feedback into either the production process or engineering design or development that would necessarily lead to quality improvement.

29. Statistical Methods for Quality Control and Improvement
Variations of acceptance sampling

30. 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
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

31. Quality planning involves
identifying customers, both external and internal,
identifying their needs (this is sometimes called listening to the voice of the customer)
developing products or services that meet or exceed customer expectations
determining how these products and services will be realized.
Planning for quality improvement on a specific, systematic basis is also a vital part of this process.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

32. Quality assurance is the set of activities that ensures the quality levels of products and services are properly maintained and that supplier and customer quality issues are properly resolved.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

33. Quality control and improvement involve the set of activities used to ensure that the products and services meet requirements and are improved on a continuous basis.
Since variability is often a major source of poor quality, statistical techniques, including SPC and designed experiments, are the major tools of quality control and improvement.
Quality improvement is often done on a project-by-project basis and involves teams led by personnel with specialized knowledge of statistical methods and experience in applying them.
Projects should be selected so that they have significant business impact and are linked with the overall business goals for quality identified during the planning process.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

34. 1.2. History of Quality Improvement
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

35. Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

36. Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

37. Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

38. 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
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

39. W. Edwards Deming
Deming was asked by JUSE to lecture on statistical quality control to management
He became a consultant to Japanese industries and convinced their top management of the power of statistical methods and importance of quality as a competitive weapon.
Japanese adopted many aspects of Deming’s management philosophy. This commitment to and use of statistical methods has been a key element in the expansion of Japan’s industry and economy.
JUSE created the Deming Prize for quality improvement in his honor.
Deming lectured widely in North America during the 1980s; he died 24 December 1993
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

40. Deming’s 14 Points
1. Create constancy of purpose toward improvement : Invest in research, development, and innovation which will have long-term payback to the organization.
2. Adopt a new philosophy, recognize that we are in a time of change, a new economic age: The cost of dealing with scrap, rework, and other losses created by defectives is an enormous drain on company resources.
3. Cease reliance on mass inspection to improve quality: Quality results from prevention of defectives through process improvement, not inspection.
4. End the practice of awarding business on the basis of price alone: Preference should be given to suppliers who use modern methods of quality improvement and who can demonstrate process control and capability. It is important to build long-term relationships.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

41. 14 Points cont’d
5. Focus on continuous improvement: Constantly try to improve the production/service system. Involve the workforce in these activities and make use of statistical methods.
6. Institute training: Everyone should be trained in the technical aspects of their job and in modern quality improvement methods. The training should encourage all employees to practice these methods everyday.
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: Teamwork among different organizational units is essential for effective quality and productivity improvement
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

42. 14 Points cont’d
10. Eliminate slogans and targets for the workforce such as zero defects: Numerical goals and slogans are worthless unless employees are provided with the tools to achieve management’s desires.
11. Eliminate numerical quotas and work standards, substitute leadership: These are tools of the short-term view and must be eliminated to achieve continuous improvement quality.
12. Remove barriers that discourage employees from doing their jobs
13. Institute an ongoing program of education and self-improvement for all employees
14. Create a structure in top management that will dynamically advocate the first 13 points: everyone in the organization must know that continuous improvement is a common goal.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

43. Also known as Deming cycle or PDCA (PDSA) cycle
The process is almost always iterative and may require several cycles for solving complex problems.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

44. Joseph M. Juran Born in Romania (1904-2008), immigrated to the US
Worked at Western Electric, influenced by Walter Shewhart
Emphasizes a more strategic and planning oriented approach to quality than does Deming
Juran Institute is still an active organization promoting the Juran philosophy and quality improvement practices
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

45. The Juran Trilogy Planning Control Improvement
Customers and their needs are identified.
Products or services that meet these customer needs are designed and/or developed.
Processes for producing these products or services are developed.
Control
Employed to ensure that product or service meets requirements
SPC is one of the primary tools of control
Improvement
Project-by-project improvement
Improvement can be either incremental or by breakthrough
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

46. Genichi Taguchi
Variation can be reduced by good design: extended the quality assurance activities to the earlier stages of the product life cycle.
Taguchi’s quality engineering is also called the robust deign method.
Robustness means insensitivity to variations caused by noise factors, which may include environmental factors, user conditions, and manufacturing disturbances.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013  John Wiley & Sons, Inc.

47. Some of the Other “Gurus”
Kaoru Ishikawa
Son of the founder of JUSE, promoted widespread use of basic tools
Armand Feigenbaum
Author of Total Quality Control, promoted overall organizational involvement in quality,
Three-step approach emphasized quality leadership, quality technology, and organizational commitment
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

48. Total Quality Management (TQM)
TQM is a strategy for implementing and managing quality improvement activities on an organizationwide basis.
Started in the early 1980s,
Deming/Juran philosophy as the focal point
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

49. Principles of TQM
1. Customer-focused: The customer ultimately determines the level of quality.
2. Total employee involvement: All employees participate in continual improvement. Total employee commitment can only be obtained after fear has been driven from the workplace, when empowerment has occurred, and management has provided the proper environment. High-performance work systems integrate continuous improvement efforts with normal business operations.
3. Process-centered: A fundamental part of TQM is a focus on process thinking.
4. Integrated system: Although an organization may consist of many different functional specialties often organized into vertically structured departments, it is the horizontal processes interconnecting these functions that are the focus of TQM.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013  John Wiley & Sons, Inc.

50. Principles of TQM
5. Strategic and systematic approach 6. Continual improvement 7. Fact-based decision making: In order to know how well an organization is performing, data on performance measures are necessary. TQM requires that an organization continually collect and analyze data in order to improve decision making accuracy, achieve consensus, and allow prediction based on past history. 8. Communications
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013  John Wiley & Sons, Inc.

51. Total Quality Management (TQM)
Some general reasons for the lack of noticeable success of TQM:
Lack of top-down, high-level management commitment and involvement
Inadequate use of statistical methods and insufficient recognition of variability reduction as a prime objective
Too much emphasis on widespread training, as opposed to focused training
No project-by-project implementation strategy
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

52. Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.

53. Learning Objectives Chapter 1
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Copyright (c) 2013  John Wiley & Sons, Inc.