Design for

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Chapter 12

• Design for
• Six Sigma

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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

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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.
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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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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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Quality Function Deployment
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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.
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House of Quality
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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.

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Concept Engineering

• Understanding the customers environment.
• Converting understanding into requirements.
• Operationalizing what has been learned.
• Concept generation.
• Concept selection.

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Tools for Design Development

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

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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.
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Tolerance Design

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

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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.
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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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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

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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

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Types of Reliability

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

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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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Cumulative Failure Rate Curve
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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.
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Failure Rate Curve
Infant mortality period
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Average Failure Rate
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Reliability Function

• Probability density function of failures
• f(t) le-lt for t gt 0
• Probability of failure from (0, T)
• F(t) 1 e-lT
• Reliability function
• R(T) 1 F(T) e-lT

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Series Systems
RS R1 R2 ... Rn
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Parallel Systems
RS 1 - (1 - R1) (1 - R2)... (1 - Rn)
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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)
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Tools for Design Optimization

• Taguchi loss function
• Optimizing reliability

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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.
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Loss Functions
Traditional View
Taguchis View
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Taguchi Loss Function Calculations
Loss function L(x) k(x - T)2
Example Specification .500 ? .020. 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 - .500)2 Expected loss k(?2
D2) where D is the deviation from the target.
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Optimizing Reliability

• Standardization
• Redundancy
• Physics of failure

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Tools for Design Verification

• Reliability testing
• Measurement systems evaluation
• Process capability evaluation

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Key Idea
Design verification is necessary to ensure that
designs will meet customer requirements and can
be produced to specifications.
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Reliability testing

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

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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.

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Metrology - Science of Measurement

• Accuracy - closeness of agreement between an
  observed value and a standard
• Precision - closeness of agreement between
  randomly selected individual measurements

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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

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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

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Spreadsheet Template
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RR Evaluation

• Under 10 error - OK
• 10-30 error - may be OK
• over 30 error - unacceptable

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Key Idea
One of the most important functions of metrology
is calibrationthe comparison of a measurement
device or system having a known relation-ship to
national standards against another device or
system whose relationship to national standards
is unknown.
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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

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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)

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Process Capability Study

1. Choose a representative machine or process
2. Define the process conditions
3. Select a representative operator
4. Provide the right materials
5. Specify the gauging or measurement method
6. Record the measurements
7. Construct a histogram and compute descriptive
   statistics mean and standard deviation
8. Compare results with specified tolerances

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Process Capability
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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.
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Process Capability Index
UTL - LTL 6s
Cp
UTL - m 3s
Cpu
m - LTL 3s
Cpl
Cpl, Cpu
Cpk min
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Spreadsheet Template