03 Prioritizing Responses for a DoE

By info@stefan-moser.com
factors (X)
Input
variables
Transfer function
Disturbances
Target
values
Cause – Effect – Model
System
or
process
Response (y)
How to define and
prioritize responses within
a QBD-DoE Investigation.

Hen or egg, response or factors first?
According to Karl Popper, it is above all
the imagination, that can generate ideas
to investigate and understand things in
context.
factors (X)
Input
variables
Transfer function
Disturbances
Target
values
Cause – Effect – Model
System
or
process
Response (y)

Once I received a postcard which
said, “If you know your goals, you’ll
find a way!”
The definition of the optimization target, should
therefore come first, an important aspect to
differentiate symptoms and targets in advance.
The good thing is, that the number of Responses does
not affect the number of experiments, but the
workload of testing the experiment results.
symptoms
symptoms
symptoms
Target
Specs
Goals

are you doing to achieve your goal?
do you want to achieve your goal?
and for what it is for you of importance?
In the style of Why, How, What – Simon Sinek
Initially the following questions should
be asked to discuss the responses and
targets of the investigation.

• Why should this investigation be started and why now?
• What consequences would it have if the investigation could not be started?
• What priority does the problem have in comparison with concurrent
problems
• Since when has the problem been known?
• How did you hear about the problem
• Did the demands of this process/investigation change?
• Did anybody try to solve the problem? If yes: what are the results?
• Does the DoE fulfill the requirements of the business strategy?
• What groups will be happy whether the problem is fixed or not?
When it is my job to lead a team through
this process, I ask the following
questions.
…Sometimes through this, I make new friends …

Demands
0% fulfilled
Demands
100% fulfilled
High priority of (USP)
requirements
Low priority of (USP)
or basic requirements
VOC
VOC
VOC
VOC
VOC VOC
VOC
VOC
The Kano model helps to reflect the needs
from the customer's point of view.
It’s always tricky to judge responses. As Henry
Ford told “If I had asked people what they want,
it would have been ‘Faster horses’ ”

7
For a "process/company/customer" that has a "problem/need,"
this approach is a way to examine the "1-n problems" we have in a
structured, holistic approach, as well as "the opportunities, trade-
offs, and contradictions" based on the results of the investigation.
After clarifying the questions, the team
should be able to explain the need for
the research. The elevator pitch could be
a nice way to do this.

Of course prior to this, the “Voice of
customer” should be analysed and the
“Quality attributes” derived.
The Quality Function Deployment is a nice tool
capable of correlating customer needs to
Quality attributes.
Critical to quality
Attributes
Voice of customer
attributes
Correlation pattern

Further more the current process can be
compared with concurrent alternatives,
different Customers or processes in order
to set priorities with the swot analysis.
SWOT Analysis
Based on the SWOT Analysis USP’S might be
discovered, scaled or adapted.
USP scaling
Do it later
Dump it
Delegate Do it first
- importance +
-
urgency
+
Concurrent alternatives

With technical Benchmark quality
attributes can be analysed weather they
are measurable and reachable.
Technical
Benchmark
Quality Attributes with high column values are
suitable to judge / measure the fulfillment of the
customer's voice.
Bottleneck Analysis
Do it later
Dump it
Delegate Do it first
- importance +
-
urgency
+

Measurability: Responses which are only
defined by good and bad are not useful.
If a target variable has only two characteristic
values, the transition from good to bad cannot
be modeled - alternative scales must be found!
Approaches could: Proportions, Percentage, Grades,
Sorting, Segmentation, Evaluation, Estimation,
Comparison, Gradual Classification, Ranking,
Groupings, or Pairwise Comparison for instance with
sensory panels.
Good Bad
0 1 2 3 4
0 1 2 3 4
Good Bad

Even if your response is easy, cheap and
quick to measure ... it can still become
critical in terms of the resolution of the
measurement devices.
d d
D
It is ideal if the mean spread “D” is more than five
times larger than the limit span ”d”. Thus, the
differences between good and bad parts can be
reliably differentiated.

In other words, the instrument resolution
is crucial for the discriminability of the
gradual differences of the results.
To estimate the correct size of a histogram interval,
the number of distinguishable categories "ndc" can be
calculated. If the resolution of the device is not
adequate, the probabilities and confidence intervals
cannot be calculated sufficiently.
bad resolution good resolution

After that, the response variables should
be classified according to their weighting
in the target specification. The “MoSCow
Method” could be useful.
Doing this in advance and documenting it carefully
might be helpful if the outcome is contradictory and
compromises need to be discussed. Sometimes it is
also useful to justify subsequent steps.
xxx
xxx
xxx
xxx
xxx
xxx
xxx
“Must”
Requirement
s
“Could”
Nice to have
“Should”
Interesting
“Won’t”
xxx
xxx
xxx

Do you find my slides helpful?
..and would like to use
them? Then please
contact me.
Thank you for
referencing me when
using my training
materials.

Would you like to receive support or
attend a course to learn more about
QBD-DoE methods? Please contact me.
like share connect
www.stefan-moser.com
info@stefan-moser.com

03 Prioritizing Responses for a DoE

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