1. Chapter 12 Design for Six Sigma
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

2. DFSS Activities
Concept development, determining product functionality based upon customer requirements, technological capabilities, and economic realities
Design development, focusing on product and process performance issues necessary to fulfill the product and service requirements in manufacturing or delivery
Design optimization, seeking to minimize the impact of variation in production and use, creating a “robust” design
Design verification, ensuring that the capability of the production system meets the appropriate sigma level
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

3. Key Idea
Like Six Sigma itself, most tools for DFSS have been around for some time; its uniqueness lies in the manner in which they are integrated into a formal methodology, driven by the Six Sigma philosophy, with clear business objectives in mind.
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

4. Tools for Concept Development
Concept development – the process of applying scientific, engineering, and business knowledge to produce a basic functional design that meets both customer needs and manufacturing or service delivery requirements.
Quality function deployment (QFD)
Concept engineering
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5. Key Idea
Developing a basic functional design involves translating customer requirements into measurable technical requirements and, subsequently, into detailed design specifications.
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6. Quality Function Deployment
technical
requirements
component
characteristics
process
operations
quality plan
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

7. Key Idea
QFD benefits companies through improved communication and teamwork between all constituencies in the value chain, such as between marketing and design, between design and manufacturing, and between purchasing and suppliers.
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

8. House of Quality Interrelationships Customer requirement
Technical requirements
Voice of
the
customer
Relationship
matrix
Technical requirement
priorities
Customer
requirement
Competitive
evaluation
Interrelationships
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

9. Building the House of Quality
Identify customer requirements.
Identify technical requirements.
Relate the customer requirements to the technical requirements.
Conduct an evaluation of competing products or services.
Evaluate technical requirements and develop targets.
Determine which technical requirements to deploy in the remainder of the production/delivery process.
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

10. Concept Engineering Understanding the customer’s environment.
Converting understanding into requirements.
Operationalizing what has been learned.
Concept generation.
Concept selection.
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11. Tools for Design Development
Tolerance design
Design failure mode and effects analysis
Reliability prediction
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12. Key Idea
Manufacturing specifications consist of nominal dimensions and tolerances. Nominal refers to the ideal dimension or the target value that manufacturing seeks to meet; tolerance is the permissible variation, recognizing the difficulty of meeting a target consistently.
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

13. Tolerance Design Determining permissible variation in a dimension
Understand tradeoffs between costs and performance
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14. Key Idea
Tolerances are necessary because not all parts can be produced exactly to nominal specifications because of natural variations (common causes) in production processes due to the “5 Ms”: men and women, materials, machines, methods, and measurement.
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

15. DFMEA
Design failure mode and effects analysis (DFMEA) – identification of all the ways in which a failure can occur, to estimate the effect and seriousness of the failure, and to recommend corrective design actions.
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16. MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

17. Reliability Prediction
Generally defined as the ability of a product to perform as expected over time
Formally defined as the probability that a product, piece of equipment, or system performs its intended function for a stated period of time under specified operating conditions
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

18. Types of Failures
Functional failure – failure that occurs at the start of product life due to manufacturing or material detects
Reliability failure – failure after some period of use
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

19. Types of Reliability
Inherent reliability – predicted by product design
Achieved reliability – observed during use
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20. Reliability Measurement
Failure rate (l) – number of failures per unit time
Alternative measures
Mean time to failure
Mean time between failures
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21. Cumulative Failure Rate Curve
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

22. Key Idea
Many electronic components commonly exhibit a high, but decreasing, failure rate early in their lives (as evidenced by the steep slope of the curve), followed by a period of a relatively constant failure rate, and ending with an increasing failure rate.
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

23. Failure Rate Curve “Infant mortality period”
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24. Average Failure Rate
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

25. Reliability Function Probability density function of failures
f(t) = le-lt for t > 0
Probability of failure from (0, T)
F(t) = 1 – e-lT
Reliability function
R(T) = 1 – F(T) = e-lT
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

26. Series Systems RS = R1 R2 ... Rn 1 2 n
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27. Parallel Systems RS = 1 - (1 - R1) (1 - R2)... (1 - Rn) 1 2 n
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

28. Series-Parallel SystemsC RA RB RD RC A B D C RC
Convert to equivalent series system RA RB RD A B C’ D
RC’ = 1 – (1-RC)(1-RC)
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

29. Tools for Design Optimization
Taguchi loss function
Optimizing reliability
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

30. Key Idea
Design optimization includes setting proper tolerances to ensure maximum product performance and making designs robust, that is, insensitive to variations in manufacturing or the use environment.
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

31. Loss Functions loss no loss nominal tolerance Traditional View
Taguchi’s
View
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

32. Taguchi Loss Function Calculations
Loss function: L(x) = k(x - T)2
Example: Specification = .500  Failure outside of the tolerance range costs $50 to repair. Thus, 50 = k(.020)2. Solving for k yields k = 125,000. The loss function is:
L(x) = 125,000(x )2
Expected loss = k(2 + D2)
where D is the deviation from the target.
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

33. Optimizing Reliability
Standardization
Redundancy
Physics of failure
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

34. Tools for Design Verification
Reliability testing
Measurement systems evaluation
Process capability evaluation
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

35. Key Idea
Design verification is necessary to ensure that designs will meet customer requirements and can be produced to specifications.
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

36. Reliability testing Life testing Accelerated life testing
Environmental testing
Vibration and shock testing
Burn-in (component stress testing)
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

37. Measurement System Evaluation
Whenever variation is observed in measurements, some portion is due to measurement system error. Some errors are systematic (called bias); others are random. The size of the errors relative to the measurement value can significantly affect the quality of the data and resulting decisions.
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

38. Metrology - Science of Measurement
Accuracy - closeness of agreement between an observed value and a standard
Precision - closeness of agreement between randomly selected individual measurements
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

39. Repeatability and Reproducibility
Repeatability (equipment variation) – variation in multiple measurements by an individual using the same instrument.
Reproducibility (operator variation) - variation in the same measuring instrument used by different individuals
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

40. Repeatability & Reproducibility Studies
Quantify and evaluate the capability of a measurement system
Select m operators and n parts
Calibrate the measuring instrument
Randomly measure each part by each operator for r trials
Compute key statistics to quantify repeatability and reproducibility
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

41. Spreadsheet Template
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

42. R&R Evaluation Under 10% error - OK 10-30% error - may be OK
over 30% error - unacceptable
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

43. Key Idea
One of the most important functions of metrology is calibration — the comparison of a measurement device or system having a known relationship to national standards against another device or system whose relationship to national standards is unknown.
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

44. Process Capability
The range over which the natural variation of a process occurs as determined by the system of common causes
Measured by the proportion of output that can be produced within design specifications
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

45. Types of Capability Studies
Peak performance study - how a process performs under ideal conditions
Process characterization study - how a process performs under actual operating conditions
Component variability study - relative contribution of different sources of variation (e.g., process factors, measurement system)
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

46. Process Capability Study
Choose a representative machine or process
Define the process conditions
Select a representative operator
Provide the right materials
Specify the gauging or measurement method
Record the measurements
Construct a histogram and compute descriptive statistics: mean and standard deviation
Compare results with specified tolerances
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

47. Process Capability specification natural variation (a) (b) (c) (d)
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48. Key Idea
The process capability index, Cp (sometimes called the process potential index), is defined as the ratio of the specification width to the natural tolerance of the process. Cp relates the natural variation of the process with the design specifications in a single, quantitative measure.
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

49. Process Capability Index
UTL - LTL 6s
Cp =
UTL - m 3s
Cpu =
m - LTL 3s
Cpl =
Cpk = min{
Cpl, Cpu }
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing

50. Spreadsheet Template
MANAGING FOR QUALITY AND PERFORMANCE EXCELLENCE, 7e, © 2008 Thomson Higher Education Publishing