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Application of TRIZ to Technology Forecasting - Case Study: Yarn Spinning Technology

| On 19, Jul 2000

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.

Number of inventions:

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

Performance:

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

Summary on rotor spinning:

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:

  1. Partial mobility of parts of object

  2. Increasing the degree of freedom

  3. Change to flexible object

  4. Change to molecular object

  5. 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.

(4) Mann D., Using S-curves and Trends of Evolution in R&D Strategy Planning, TRIZ Journal, July 1999.

(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.

(9) Schlafhorst, Autocoro automatic rotor spinning and winding machines-Profitable investment in modern machinery for production of high-quality rotor yarns, advertising book, p.13, viewed on September 1999.

(10) Personal discussion with Dr. Rust and Dr. Oxenham, North Carolina State University, September 1999.

(11) ITMF, Open-end Reports on “Shipment of spindles in the world” from years 1988 – 1998.

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…