Training technologists
in experimental design
作者：James M Cupello
年代：1999
出處：
Research Technology Management.
Washington: 卷期 42, Iss. 5; pg. 47
報告者：蘇暘展
Outliner
Introduction
1. Curriculum Content
2. Teaching Skill
3. Course Materials
4. In-Class Experiments
5. DOE Software
6. Integration with Other TQM Tools
7. Select Taguchi Methods
In Conclusion
Introduction

Statistically designed experiments have proven to be
one of the few reliable weapons in the 20th century
arsenal of globally competitive firms.

R&D managers would benefit greatly if they could identify
the vital few outstanding courses from among the
hundreds of academic and commercial ones available on
this topic.

Consequently, 7 best practices associated with such a
world-class course are postulated.
1. Curriculum Content
"Curriculum content" and "teaching skill" are truly first
among equals when looking at all seven best
practices.
(1) Calculating factor effects for simple two-level designs,
preferably via a student exercise.
(2) Inclusion of a thorough explanation of interaction
effects, their importance and how they are calculated.
(3) Introducing the concept of orthogonal arrays and how
they are constructed for two-level designs.
(4) A thorough definition, explanation and demonstration
of "confounding" in fractional factorial designs.
(5) The benefits of DOE are compared with the
traditional one-factor-at-a-time (OFAT) designs.
(6) The concept of using center points in two-level
designs is rigorously explained and demonstrated.
(7) Normal and half-normal probability plots are
explained and illustrated by example or in-class exercise.
(8) Plackett-Burman screening designs are introduced
and explained, and contrasted with traditional fractional
factorial designs.
(9) The concept of "foldover designs" is introduced and
explained.
(10) Mixture designs are briefly explained.
(11) The technique known as the "method of steepest
ascent" is introduced and explained.
(12) The advanced topic of "response surface
methodology" (RSM) is introduced by way of lecture.
Total time allocated to RSM should not exceed two to
three hours.
 The resulting course content is captured in the
illustration, next page, which partitions the various course
topics into four areas that mimic the Deming PDCA cycle:
Planning (pre-experimental), (15%)
Design (types),
(30%)
Conduct (of an experiment), (20%)
Analysis (of the data).
(35%)
During course development, I identified ten key
concepts or pedagogical best practices associated with
a DOE course; they are listed below.
Students should have at least one team exercise early in
the course where they use their "pre-course" knowledge to
plan and execute an in-class experiment. This experience
then serves as motivation to learn the new DOE methodology.
 Because variation is a researcher's relentless enemy, the
course should emphasize issues involving variability:
blocking, randomization, measurement error, recording error,
bias, confounding, residual plots, analysis of variance, etc.
Experimentation should be sequential. Emphasize that no
more than 25 percent of one's research budget should be
spent on the first experiment.
Multiple responses are a fact of life in today's complex
world. Students should be shown how to simultaneously
optimize a process involving more than one response
variable.
Software is essential for DOE; no one does calculations by
hand.
Two-level designs are the workhorse of DOE. At least half
of the course schedule should be devoted to them.
A transformation of the response variable is occasionally
required. This is an advanced topic.
Students should be introduced to the idea of
transformations and when they might be needed,
appropriate or essential.
Sample size matters a lot. Students should be shown how
to estimate the sample size required to detect an effect of a
given size for a two-level factorial at various confidence (or, 1)
levels
Taguchi's concepts of variance reduction and robust design
are not only important from a pedagogical standpoint; they
are considered a best practice for a world-class DOE course.
Students must learn how to explain their experimental
results in the context of management briefings without using
DOE jargon and buzzwords.
2. Teaching Skill
Outstanding teachers are truly valuable human beings,
more so because they are rare.
A prospective DOE instructor should provide copies of
student evaluations of his/her teaching of the DOE course
under consideration. Evaluation forms (or rating scores) from
all former students should be included to prevent biased
reporting.
A prospective DOE instructor should provide the names,
addresses and phone numbers of at least two references
who took his/her course, and who are willing to comment on
its content and the quality of instruction.
Managers should have at their disposal information
relating to teaching skill from one or more of the
following sources: student evaluations, reference checks,
and/or course audits.
 With this information, it should be possible to
effectively evaluate a course and its instructor
using the following criteria:
1. The instructor's demonstrated subject-matter
knowledge;
2. The instructor's demonstrated ability to respond
effectively to student questions and comments;
3. The instructor's demonstrated ability to present
information and concepts effectively;
4. The manager's overall assessment of the
instructor's effectiveness as an educator.
3. Course Materials
Essential course materials for a world-class
introductory DOE course

Student Textbook

Course Notes

Supplemental Readings

Design Toolkit

DOE Software
Student textbook
Only a few of the benchmarked courses provided a
student text as part of the course offering.
Students should be provided with an exemplary
textbook to keep after the course is over.
Course notes
It has been claimed that 80 percent of learning occurs
through the sense of sight . If true, this means that the
use of overhead slides by the instructor can be a
significant improvement over pure lecture without notes.
Distribute copies of the instructor's lecture slides or
overheads at the beginning of class, to facilitate
notetaking.
Supplemental readings
Provide students with a useful and extensive selection
of easy-to-understand journal articles relevant to the
subject of experimental design.
Design toolkit
Provide students with an extensive collection of useful
design tools/aids that simplify the design of an
experiment and the analysis of data.
DOE software
Consider introducing any in-class activity designed to reduce
student anxiety typically associated with mathematics,
statistics, and computation.
4. In-Class Experiments
With regard to in-class experiments, students should work
alone, or preferably in small groups of three to five, to
generate and analyze their own experimental data during
class.
Consider the use of one or more video presentations in
class to present course material in an interesting and
informative way.
5.DOE Software
Students should be provided with user-friendly DOE
software during the course for analyzing data.
Students should be provided a free personal copy of
the course software for use upon their return to work.
6. Integration with Other TQM Tools
Two additional tools-flow charting and cause-and-effect
diagrams-tend to be used together to solve problems.
The flow chart documents the actual step-by-step process used
in the conduct of an experiment;
the cause-and-effect diagram is a vehicle for brainstorming
actions that can be taken to reduce variation in each step on
the flow chart.
7. Select Taguchi Methods
Taguchi introduced the concept of robust design, which
is a simple experimental design methodology that
attempts to make products and processes insensitive to
the degradation posed by uncontrollable factors (noise)
in the environment.
Any world-class DOE course should explain or illustrate
Taguchi's approach to identifying variance-reducing
factors.
In Conclusion
DOE is an important methodology for any company
involved in product or process development.
It is becoming increasingly difficult to compete in a
global economy without the use of this and other select
performance-enhancing tools.
Considering that a firm's technical staff consists of some
of the highest paid individuals on the payroll, their time
and talents are too valuable to waste by sending them
to less than stellar courses and workshops.
The End