Severine
Gahide
http://www4.ncsu.edu/~sgahide/cv.html
Under
the Direction of:
|
Dr. Timothy G. Clapp
Professor
North Carolina State University
tclapp@tx.ncsu.edu |
Dr.
Michael S. Slocum
Adjunct Assistant Professor
North Carolina State University
mslocum@ontro.com |
Abstract
Research
and development managers have the difficult task of forecasting technological
changes. TRIZ methods are applied
to assess the maturity of a technical system.
With this information, a decision is made to optimize existing
technologies or to develop new core technology. Patterns of evolution are applied to forecast future
technological R&D plans. A case
study is presented to show how maturity mapping and patterns of evolution are
used to predict yarn formation technology.
1.
Introduction
Making
strategic decisions for product development is one of the toughest jobs that
managers of Research and Development have in an organization. Deciding between
optimizing existing technologies or developing new core technology is one of
them. There is a high uncertainty
related to these decisions and although many decision tools are available and
have been successful to various degrees, the decision-maker’s intuition is
sometime the only element for directing the company’s line of products.
TRIZ, the Russian acronym for Theory of Inventive Problem Solving is
emerging as a powerful scientific tool that helps decision-makers to make these
strategic forecasting decisions.
The
purpose of this paper is to review two TRIZ tools, maturity mapping and patterns
of evolution and to illustrate them with a case study.
This
paper will describe Maturity Mapping, then give elements to guide the
optimization or innovation decision involved in product development strategies. Patterns of evolution will be defined and explained through
examples. A textile equipment case
study is presented to demonstrate the methodology.
2.
Technology Assessment
Assessment
of a company’s current technology should drive the direction of the R&D
planning process. Ellen Domb [1]
suggests that “people tend to do an initial assessment of their product
maturity based on their emotional state. If
people are excited they will place their product in the ‘growth stage’ but
if they are frustrated - may be because of technical or physical contradictions-
they will place it in the maturity stage.”
There needs to be a systematic process for assessing technology.
Altschuller
found that any system is evolving in a biological pattern, meaning that it will
go through four main stages also known as: infancy, growth, maturity, and
decline. These stages are plotted
on the biological “S-Curve” on Figure 1.

Figure
1:
Biological S-Curve of a system [2]
Four main descriptors are used to assess the life cycle
stage (or technological maturity) of a technological system on its S-curve.
They are 1) the number of patents per time period, 2) the level of
innovation per time period, 3) technical performance per time period and 4) the
profitability per time period. Each
descriptor has a characteristics profile or shape as shown in Figure 2.

Figure
2: Four
curves plotted versus time [3]
The
company can collect data to construct each of the descriptor curves.
The shapes of each of the descriptor curves are compared with the shapes
of the characteristic curves. A
composite analysis of the four curves provides a data-driven assessment of the
maturity of the company’s technological system.
Other
descriptors are sometime used to refine the maturity of a system such as cost
reduction-related inventions [4]
.
Darrell Mann defined “cost reduction-related inventions” as
inventions that relate to making the product cheaper – such as improvements to
manufacturing technology or method of assembly [4]. The number of such inventions tends to increase as the system
matures, as Figure 3 shows.

Figure
3: Likely
“number of cost reduction inventions” versus product maturity characteristic
3.
Innovation or Optimization
Once
the maturity of a company’s technology has been assessed, the management team
must decide the future R&D direction. Should
investments be made to optimize the technology around the core technology?
Or should investments be made to innovate a new core technology to
replace the existing core technology?
R&D,
Research and Development, suggests there are two activities. While most R&D projects deal with slight changes of an
existing product (optimization),
few actually create innovative new products (innovation)
[4]. Therefore, the issue in defining and selecting projects for
R&D requires a decision to innovate or to optimize.
If
the company’s core technology is in the mature or decline stage, innovation in
the core technology is recommended. If
the core technology is in the infancy or growth stage, optimization of the core
technology is recommended. Once the
decision is made, TRIZ patterns of evolution can be used to forecast future
technological developments.
4.
Patterns of Evolution
Patterns
of evolution represent a compilation of trends that document strong,
historically recurring tendencies in the development of manmade or natural
systems [5]. This tool, extensively described in the following section, is
the main tool for technology forecasting.
Altshuller
identified eight original trends. The
eight original trends are: 1) biological evolution, 2) increasing ideality, 3)
evolution toward dynamization and controllability, 4) complexity-simplicity, 5)
evolution with matching and mismatching elements, 6) non-uniform development, 7)
evolution toward micro-level and the use of field, and 8) decrease human
involvement [3]. Several books and
papers have been published to describe the patterns [5, 6, 7, 8].
Systematically
applying the patterns of evolution to a company’s technological system will
result in a number of possible solution paths.
The solutions or directions recommended by one trend are not unique as
they often overlap one onto another. Once
a company has generated multiple solution paths, management decisions can be
made to develop the R&D plan for the company.
A
case study is presented to illustrate the process of assessing and predicting
the development of yarn equipment technology.
Case
Study: Yarn Rotor Spinning
1.
Introduction
Textile
Machinery industry is a typical case where TRIZ applies.
Long term policies, for their Research and Development department, are
defined many years before the expected deadline of commercialization of the
machine. Machines are complex and
require a long development period before they can be sold.
Therefore, budgets and policies have to be carefully defined.
A wrong direction would not only result in short-term profit loss but
also would create a huge technological gap that may be fatal to the company.
Spinning machinery is an example. The
following is a case study on yarn rotor spinning.
2.
Rotor Spinning Technological Maturity:
S-curve Descriptors
2.1
The Database
A
database under MS Access was created to build the graphs.
It contained a collection of patents for rotor spinning technology.
Extensive searching of the US Patent Office’s database was performed
using a list of company names and the key words “rotor and spinning.”
The US Patent Office’s database covers the period from Jan. 1, 1976 to
the present (Aug. 1999, in this case). Earlier
patents were obtained from a compilation of important patents related to
open-end spinning and covered the years 1930 to 1967.
Obviously, this database is not comprehensive due to the lag in the years
searched and omissions from the list of company names, but is believed to be
representative of the rotor spinning industry. Building this database was a very important step of our case
study. It can be sorted and
filtered in many ways. Tremendous
information can be extracted. Figure
4 is a record example from this database.
Figure
4: One
patent record from the MS Access application.
2.2
Part Codes
The
part codes were assigned by spinning
experts based on the part or system that was improved by the patent.
They identified the major system (rotor or friction or air jet or vortex) and
the subsystems involved. For
example, codes such as: RS for Rotor Spinning, SB for Spinbox, AC for Cleaning
Belt and BG for Box Geometry were used.
Applicants of patents were also coded: Sc stands for Schlafhorst.
It is important that experts do this task because the analysis is based
on the quality of the coded information in the database.
2.3
Rotor Spinning Maturity
There
is a total of 238 patents related to rotor spinning.
Each of them has been carefully examined and summarized in the database.
A level of innovation was also assigned following the guidelines
explained in Appendix 1. Patents were grouped by decades.
Performance was assessed with the achievable rotor speed.
There is a theoretical limit due to the ratio of fiber length and rotor
diameter. Profitability was
difficult to appraise; therefore, the number of rotor spinning machines sold in
the world was the best estimate. Figures
5 to 12 are the four descriptor curves and their corresponding TRIZ descriptor
curves. Boxes on the TRIZ curves
suggest the achieved maturity between experimental data and TRIZ.

Figures
5 and 6:
Patents per 10-year-period for rotor spinning technology
and
the TRIZ benchmark’s graph

Level
of Innovation:
Figures
7 and 8:
Level of innovation for rotor spinning technology from 1940 to 2000
and
the TRIZ benchmark’s graph

Figures
9 and 10:
Rotor speed [9, 10] and the TRIZ benchmark’s graph
Profitability:

Figure
11 and 12:
Number of shipments of rotor spindles [11] and the TRIZ benchmark’s graph

Figure
13: Four
maturity descriptors for rotor spinning and their achievements
Figure
13 shows that rotor spinning technology is in the mature stage.
The conclusion is that there is a need for a new core technology.
The system has reached a threshold and recommendations are to use the
patterns of evolution with a focus on a change of the core technology. Applying the trends to auxiliary, secondary or harmful
functions will result in optimizations but it will not allow the company to stay
competitive for the long run. Actions
should be taken now to insure a profitable future.
Yarn rotor spinning has reached a maturity.
A dramatic change (to the core itself) is strongly recommended.
The trends should be applied with the strong focus on the core
technology.
3.
Patterns of Evolution: Ideality
Ideality
is a very useful trend because it helps to visualize potential improvements
while striving for the best. Sometimes
it also identified steps that are already accomplished.
Figure 14 represents the trend of ideality for Rotor spinning.

Figure
14: Rotor
spinning and its trend of ideality representation
The
conclusion from Figure 14 is that the textile industry did not wait for Rotor
spinning to mature to build the next ideal generation.
Nonwovens have been successful for many years mainly in man-made fibers
and ideally
should replace (rotor) spinning in the long term. This conclusion here is not about market share or consumer
preferences but from a technological and innovation point of view.
It does not mean that rotor spinning has a short-term death coming.
It will stay in business for many more years, such as ring spinning,
although the technology was superceded. This
trend validates the conclusion found before about the maturity of rotor
spinning.
3D-Meltblowing
-- polymer chips are melted and then blown onto a screen mesh or substrate and
take the shape of its substrate-- is still at an early stage of research and is
not commercialized yet as a way to produce garments. However, fundamental research is done and applications are
investigated. There is no doubt
that this nonwoven process will have a future.
4.
Patterns of Evolution: dynamization
The
pattern of dynamization predicts five steps:
-
Partial mobility of parts of object
-
Increasing the degree of freedom
-
Change to flexible object
-
Change to molecular object
-
Change to field object
The
core of rotor spinning is the spin box and the rotor itself. From this point of
view, step
1 is done, with one rotation. Step
2 recommends to add a degree of freedom. A translation (front to
back) could be an additional degree of freedom. The translation could occur
during spinning or as a machine set up adjustement. By modifying the spinning
zone the yarn properties may change and wrapper fibers may be affected.
Step
3 proposes a flexible system. There
is no flexible rotor made of elastic or rubber and Step 4 seems not applicable.
However, Step
5 is interesting because use of a field has already been done.
Electrostatic spinning was tried and somehow not commercially as successful as
one predicted. Also, the early vortex spinning systems used air as a means to
spin the fibers. From a yarn structure point of view, it was an open end yarn.
However, the latest Vortex spinning machines (MVS) from Murata and some
Air-jet machines (Murata, Toray and Toyoda) also use air to spin but the yarn
produced is a fasciated yarn. The yarn structure is different. Some friction
spinning machines (by Feher, Rieter, Sussen and Schlaforst) also produce
fasciated yarns.
5.
Summary
Since
1) rotor spinning is mature, 2) the trend of dynamization recommends the use of
field as the ultimate devolpement and 3) early vortex machines were not
successful when the new vortex machines are, it is relevant to analyze the
maturity of fasciated yarns to forecast innovation in spinning. Note that vortex spinning is an example of a core technology
change and therefore would be qualified as an innovation, not an optimization of
a system.
The
other patterns of evolution can be applied to generate additional solution
directions to provide a complete picture of possible technological developments
in yarn formation. One can see that
even though the focus was on rotor spinning, the patterns clearly showed new
core technologies, such as nonwovens and fasciated assembly technologies to
replace the existing core technology. This
analysis provides the management team a much broader vision of possible
technological paths to pursue.
Acknowledgment:
The
author would like to acknowledge Dr. Tim Clapp, Dr. Michael Slocum, Dr. William
Oxenham, Dr. Jon Rust, and Jaime Hayden for their contributions to the case
study and editing the content for the paper.
References
(1)
Domb E., Strategic TRIZ and Tactical TRIZ: Using the Technology Evolution Tools,
TRIZ
Journal, January 2001.
(2)
Mueller G., Accurately and Rapidly Predicting Next-generation Product
Breakthroughs in the Medical-devices, Disposable Shaving Systems, and Cosmetics
Industries, TRIZ Journal, March
1999.
(3)
Altshuller G.S., Creativity
as an Exact Science, NY Gordon and Breach, 1988.
(5)
Zainiev D., Triz
in Progress, Ideation Research Group, p. 30 and p. 235, February
1999.
(6)
Fey V. and Rivin E., Guided Technology Evolution (TRIZ Technology Forecasting), TRIZ Journal, January
1999.
(7)
Kaplan S., An
Introduction to TRIZ The Russian Theory of Inventive Problem Solving,
Ideation International, 1996.
(8)
Terninko J., Zusman A., and Zlotin B., Step by Step TRIZ: Creating
Innovative Solution Concepts, Responsible Management Inc., 3rd
edition, 1996.
Appendix
1: Guidelines for assigning levels of innovation
Level
1: Standard solution:
·
32% of the solutions overall patents are a level
one.
·
Usually, it takes less than 10 trials to find the
right solution.
·
The solution resides within the discipline of
engineer. It is a narrow extension
or improvement of an existing system, which is not substantially changed
·
It has no influence (or consequence) on science.
·
EX: Use of a special lubricant in the spin box.
The solution already exists somewhere else.
It is not new. It is not
innovative, but it helped the process to run better.
Level
2: Change of a system
·
45% of type of solution
·
It takes less than 100 trials to be successful.
·
The solution requires trade off studies.
There are some improvement but with a compromise.
The existing system is slightly changed including new features that lead
to definite improvements.
·
EX: Geometry of the rotor.
It is an engineering type of solution, which improved the overall
spinning efficiency. There are
still some compromises but it is better than the old design.
Level
3: Innovation
·
18% of the patents, several hundreds of trials.
·
The solution is outside the box, in another field of
engineering. An inventive
contradiction is resolved within the existing system, often through the
introduction of some entirely new element.
·
EX: To improve rotor lifetime, it was found that it
could be coated with a thin layer of diamond.
There was a need to know about material science to solve this problem.
It required a special knowledge to find it.
Level
4: Invention
·
3.7% of the patents, several thousands of trials
before success.
·
The solution is found in science, not in technology,
among rarely used physical or chemical phenomena.
·
EX: Yarn packages are traditionally dyed in
water-bathes. Dying them with super
critical CO2
fluid is an invention. In this
case, the water is not the medium to carry the dye.
It is replaced with CO2 fluid, which is not commonly used due
to the high-pressure requirements to convert CO2
gas to CO2
liquid. This is a new scientific
application to solve an existing problem in the field of textile.
Level
5: Discovery
·
0.3% of the patents in the world.
·
The solution is based on a recently discovered
phenomenon.
·
It is unique. It will greatly influence science and will have thousands of
other patents after it.
·
EX: Laser, microwave, and transistors…