Product Development Process
Ulrich
Ulrich
Process Capability
 Cp = (design tolerance width)/(process width) = (max-spec – min-spec)/ /6x
 Example:
 Plane is “on time” if it arrives between T – 15min and T + 15min.
 Design tolerance width is therefore 30 minutes
 x of arrival time is 12 min
 Cp = 30/6*12 = 30/72 = 0.42
 A “capable” process can still miss target if there is a shift in the mean.
 Motorola “Six Sigma” is defined as Cp = 2.0
 I.e., design tolerance width is +/- 6x or 12 x
3
3
process width
min acceptable
Ulrich
Design tolerance width
max acceptable
There are multiple solutions to most parametric design problems
Analytical Expression for Brownie Mix “Chewiness”
HYPOTHETICAL
Chewiness = FactorA + FactorB
Where FactorA = 600(1-exp(-7T/600)) + T/10
And FactorB = 10*Time
FactorA
200F
400F
Temperature
FactorB
20 min
26 min
Time
Option 1
Option 2
Options 1 and 2 deliver the same value of “chewiness.” Why might you prefer one option over the other?
Ulrich
Taguchi Methods
1. Any deviation from the target value is “quality lost.”
Quality
Quality
Loss
Loss = C(x-T)2
Good
Performance
Metric
Bad
Minimum
acceptable
value
Target
value
Maximum
acceptable
value
Performance
Metric, x
Target
value
2. Use of statistical experimentation to find robust combinations of parameters.
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Ulrich
Field is called “Design of Experiments” or “DOE.”
Systematically explore space of possible parameter values.
Based on analysis of relative influence of parameters on mean and variance of performance variable,
select “robust design.”
A robust design is relatively insensitive to random variability in internal and external variables.
Methodology for Achieving Robust Design
1. Identify key variables and metrics
 Articulation of performance metrics, goals
 Causal diagram
 Hypothesized sources of variability
 Analytical models where available
2. Conduct exploratory experiments
3. Reduce variability
 Design changes
 Instructions/aids for user
4. Use logic, analysis, and rough experiments to focus further experimentation
 Avoid wasting experiments on clearly infeasible regions of design space.
5. Perform focused experimentation within narrow ranges of variables
 Use “Design of Experiments” techniques if combinatorically intractable
 See “Robust Design” chapter in Ulrich and Eppinger.
 “Control” variability in laboratory setting
 Focus on identifying combination of settings that minimize variability in performance.
6. Select final values for design variables.
Ulrich