Design for

1
Chapter 12

• Design for
• Six Sigma

2
DFSS ActivitiesFour Principal 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

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.
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

5
Key IdeaConcept Development
Developing a basic functional design involves
translating customer requirements into measurable
technical requirements and, subsequently, into
detailed design specifications.
6
Key IdeaQFD
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.
7
House of Quality
8
(No Transcript)
9
Quality Function Deployment
10
Building the House of Quality

1. Identify customer requirements.
2. Identify technical requirements.
3. Relate the customer requirements to the technical
   requirements.
4. Conduct an evaluation of competing products or
   services.
5. Evaluate technical requirements and develop
   targets.
6. Determine which technical requirements to deploy
   in the remainder of the production/delivery
   process.

11
Tools for Design Development

• Tolerance design
• Design failure mode and effects analysis
• Reliability prediction

12
Key IdeaTools for Design Development
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.
13
Tolerance Design

• Determining permissible variation in a dimension
• Understand tradeoffs between costs and
  performance

14
Key IdeaTolerance Design
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.
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.

16
DFMEA

• Failure modes
• Effect of the failure on the customer
• Severity, likelihood of occurrence, and detection
  rating
• Potential causes of failure
• Corrective actions or controls

17
Reliability Prediction

• Reliability
• 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

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

19
Types of Reliability

• Inherent reliability predicted by product
  design
• Achieved reliability observed during use

20
Reliability Measurement

• Failure rate (l) number of failures per unit
  time
• Alternative measures
• Mean time to failure (MTTF)
• Mean time between failures (MTBF)

21
Cumulative Failure Rate Curve
22
Failure Rate Curve
Infant mortality period
23
Average Failure Rate
24
Key IdeaReliability Prediction
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.
25
Product Life Characteristic Curve

• Three distinct time period
• Early failure
• Useful life
• Wearout period

26
Predicting System Reliability

• Series system
• Parallel system
• Combination system

27
Series Systems
RS R1 R2 ... Rn
28
Parallel Systems
RS 1 - (1 - R1) (1 - R2)... (1 - Rn)
29
Series-Parallel Systems
C
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)
30
Tools for Design Optimization

• Taguchi loss function
• Optimizing reliability

31
Key IdeaTools for Design Optimization
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.
32
Loss Functions
Traditional View
Taguchis View
33
Loss function
34
Taguchi Loss Function

• No strict cut-off point divides good quality from
  poor quality. Rather, losses can be approximated
  by a quadratic function so that larger deviations
  from target correspond to increasingly larger
  losses.

35
Optimizing Reliability

• Standardizationuse components with proven track
  records
• Redundancyprovide backup components
• Physics of failureunderstand physical properties
  of materials

36
Tools for Design Verification

• Reliability testing
• Measurement systems evaluation
• Process capability evaluation

37
Key IdeaTools for Design Verification
Design verification is necessary to ensure that
designs will meet customer requirements and can
be produced to specifications.
38
Reliability testing

• Life testing
• Accelerated life testing
• Environmental testing
• Vibration and shock testing
• Burn-in (component stress testing)

39
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.

40
Metrology - Science of Measurement

• Accuracy - closeness of agreement between an
  observed value and a standard can lead to
  systematic bias.
• Precision - closeness of agreement between
  randomly selected individual measurements can
  lead to random variation.

41
Accuracy vs. Precision
42
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

43
Key IdeaCalibration
One of the most important functions of metrology
is calibrationthe 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.
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

45
Process Capability StudyTypical Questions Asked

• Where is the process centered?
• How much variability exists in the process?
• Is the performance relative to specs acceptable?
• What proportion of output will be expected to
  meet the specs?
• What factors contribute to variability?

46
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)

47
Process Capability
48
Process Capability
Process is capable
49
Process Capability
Process is not capable
50
Effects of Reducing Variability on Process
Capability
51
Key IdeaProcess Capability
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.
52
Process Capability Index
UTL - LTL 6s
Cp
UTL - m 3s
Cpu
m - LTL 3s
Cpl
Cpl, Cpu
Cpk min