A Comparison of the Global Process and TRIZ by liaoqinmei

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									           A Comparison of the Global-8D-Process and TRIZ
                                          Ina Bauer-Kurz
                 College of Textiles, North Carolina State University, Raleigh, USA
                       Fax: +1 (919) 515-3733; E-mail: ikurz@unity.ncsu.edu
 KEYWORDS: TRIZ, Global-8D, problem solving, innovation
ABSTRACT
Global-8D is a problem-solving methodology applied worldwide in industrial practice to improve
the product development process. This study compares Global-8D to the Theory of Inventive
Problem Solving (TRIZ) and evaluates how both tools may be combined. With an industrial
example, it is demon-strated how the implementation of TRIZ into Global-8D can enhance problem
solving, process and product quality.

WHAT IS GLOBAL-8D?
Global-8D is a problem-solving methodology for product and process improvement. It is structured
into eight disciplines, emphasizing team synergy. The team as whole is better and smarter than the
quality sum of the individuals. Each discipline of G8D is supported by a checklist of assessment
questions, such as “what is wrong with what”, “what, when, where, how much” for D2, problem
description. Throughout the problem solving process, achievements of each discipline are
summarized and recorded in a G8D spreadsheet.
                D0 - Prepare for Global-8D Process
                D1 - Establish a Team
                D2 - Describe the Problem
                D3 - Develop Interim Containment Action (ICA)
                D4 - Define & Verify Root Cause and Escape Point
                D5 -  Choose & Verify Permanent Corrective Actions (PCAs)
                           for Root Cause & Escape Point
                D6 - Implement & Validate Permanent Corrective Actions (PCAs)
                D7 - Prevent Recurrence
                D8 - Recognize Team & Individual Contributions
                         Figure 1: Overview of Global-8D Disciplines [4]

WHAT IS TRIZ?
TRIZ is the Russian acronym for “Theory of Inventive Problem Solving”. The inventor Genrich
Altshuller analyzed more than 200,000 patents and discovered that problems, solutions and patterns
of evolution were repeated across industries and sciences. Based on the empirical evidence of this
patent analysis, Altshuller built the theoretical superstructure TRIZ.
TRIZ is a system of several powerful tools for problem analysis, understanding and solution in any
scientific, technological or administrative field. ARIZ, the algorithm of inventive problem solving,
may be used as a guide through a problem solving process showing how and when to apply the
TRIZ tools. However, each tool can be applied separately according to the problem situation.
                                 Overcome psychological inertia
                                 Use of resources
                                 Ideality
                                 Physical contradictions
                                 Technical contradictions
                                 Su-Field analysis
                                 System approach
                                 Smart little people modeling
                                 Directed evolution & maturity mapping
            Figure 2: Some TRIZ Tools for Problem Analysis and Solution [1], [5], [6]
One essential feature of TRIZ is the overcome of psychological inertia, improving and accelerating
problem solving by forcing the engineer to think “out of the box”. TRIZ triggers the awareness of
resources, and thus the use of what is already available. Ideality helps to think at a functional level
and overcome psychological inertia, by identifying the real problem and its ideal solution. The
solution mechanism for physical contradictions in a problem helps finding potential solutions by
separating the needed functions in time, space, scale or upon condition. Redefining a problem in
terms of standardized technical contradictions generates general solution principles that may then
be specified for the initial problem. Substance-Field analysis creates a functional awareness of the
problem by taking it apart into essential substances and necessary force fields. For the solution of
ineffective or harmful Su-field models, a set of 76 standards solutions is provided. With the system
approach, different aspects of a problem are pointed out on a micro and macro level and in past,
present and future. Smart little people modeling focuses on the very bottom of the problem, by
analyzing the problem situation at a micro level. Finally, maturity mapping is a powerful tool for
technological forecasting by fitting a product or process to empirical trends of evolution.

CASE STUDY: VARNISH OF COMMERCIAL HEATERS
A company is manufacturing commercial heaters according to the production flow depicted below.
The problem is, that the quality inspection detects 6% defects in varnish coating, while the “normal,
acceptable” rate of defects is 1.5%. When the company was previously facing similar problems, it
turned out that some workers were using silicone hand crème, which obviously stuck to the heater
parts and prevented adhesion of the electro-statically sprayed varnish. A temporarily effective
solution to the problem at that time was the restriction and strict control of hand crème use.

STEP-BY-STEP COMPARISON OF G8D AND TRIZ
A G8D analysis was applied to solve the problem of VARNISH DEFECTS in industrial heaters.
Below, each step and the results of the analysis are explained in detail and compared to a TRIZ
analysis of the problem.
D0 – Preparation for the Global-8D Process
The purpose of this preliminary step in the G8D analysis is the quantitative identification of the
problem and its consequences for customers, the determination of an immediate action to contain
the consequences, if necessary, and the agreement of the problem situation with the G8D criteria.
             Symptoms defined
             Customers / consequences identified
             Symptom quantified with measurements
             Cause unknown
             Resources for problem solution & recurrence prevention management-approved
             Single-person capacity for problem-solving exceeded
                         Figure 3: Global-8D Criteria for the Preparation Step D0
There is no comparable explicit step or tool to D0 in the TRIZ methodology. Due to its variety of
tools, TRIZ can be applied to any problem and thus does not require a crosscheck with application
criteria. However, its effectiveness and the practicability of the TRIZ generated solutions depend
essentially on the background of the problem, which include data on the symptom, resources,
personal capacities and knowledge available. Thus, the step D0 is a useful and important step to
assure the effectiveness and success of both, a G8D
D1 – Team Building
Based on the G8D criteria that a single person is not capable of solving the problem alone, a
suitable team with defined team roles needs to be established. G8D relies on team synergy. The
whole is more than the sum of its parts. There is no equivalent to D1 in TRIZ. By providing suitable
human and intellectual resources, D1 team building, complementary to step D0, sets the frame for a
successful problem analysis and solution with both, G8D and TRIZ.
In the case of the VARNISH DEFECTS, a team of 10 people was established, with the production
manager as champion and a production engineer as team leader. The team members come from
various divisions like maintenance, finance, material lab, quality insurance and production, insuring
a wide knowledge and experience base.
D2 – Problem Description
In the G8D process, the problem description is supported by an extensive list of assessment
questions such as
          What is wrong with what?
          How can the problem be quantified?
          What? When? Where? How much?
          Has a cause & effect diagram been completed?
          Does problem describe a „something changed‟ or a „never been successful‟ situation?
          Should financial reserves be set aside?
The resulting problem description recorded in the G8D report for the case of the VARNISH
DEFECTS is: At final quality control, spots without varnish are detected in heaters, easily visible
on the metal surface. They appear regularly & lot-wise.
In the TRIZ methodology as well, a comprehensive problem description is considered as the
preliminary requirement for any problem analysis and solution. Thus, several TRIZ tools may be
used to understand and describe the problem. For the case study of VARNISH DEFECTS, the
useful- and effectiveness of some TRIZ tools for problem description complementary to the G8D
step D2 can easily be demonstrated:
Ideality
The formulation of the ideal final result for the case study is:
Every heater is evenly coated with varnish all by itself.
This statement makes clear that there are actually three aspects of the problem. The first problem, as
also stated with the G8D analysis, is that the heaters are not coated evenly with varnish, but there
are defects in the varnish.
However, ideality also points out that not every heater is perfectly coated. The company obviously
accepted a rate of defects of 1.5% as normal before, but does this really have to be normal? For
process and product improvement, any defect needs to be considered as a problem and thus as a
challenge for optimization. Wouldn‟t it be better to build some control mechanism in the process to
not deliver any defective heaters to the customers at all?
The third problem the ideal final result statement shows, is that the coating does not happen all by
itself. Obviously, the varnish coating is a process requiring fairly complex preparation: The parts
need to be cleaned and assembled. They need to stay clean during assembly. They need to be
transported and mounted in an appropriate way for spraying. If it is acknowledged as a problem,
that the coating process is not simple enough and depends on too many parameters potentially
causing defects, process and product improvement to simplify the coating action can be a challenge.
Resources
A systematic analysis of resources helps to understand the environment of the problem and identify
complementary problems in the process. As guideline, the resources in TRIZ are divided into 6
groups:
        1. Substance
        2. Field
        3. Space
        4. Time
        5. Information
        6. Functional Resources
In addition to raw materials and system elements as substances, the production process for
industrial heaters also contains waste such as metal pieces and chemical waste from the cleaning
bath. The analysis of the field resources provokes the question, why this waste is not being reused
as system energy. Considering space resources, it appears that there is a bathroom available. Why is
this bathroom not used for regular hand cleaning, through which varnish defects could obviously be
reduced previously? Time analysis shows that 4 cleaning baths may be used at the same time. Is it
possible to shift parts from one production line to the baths of the other production line if
necessary? The visibility of varnish and its defects can be used as informational resource. Why does
the process not include a detection device for varnish faults coupled as feedback to a device that
does something in the process to prevent further faults? Functional resources include e.g. the
moving of the parts and the assembled heaters for transportation. Can this motion be used to make
cleaning or varnish spraying more even?
In summary, the above considerations of resources suggest that there are plenty of problems and
insufficiencies in the process contributing to the one apparent problem VARNISH DEFECTS. The
solution of these hidden problems may solve the apparent problem automatically and improve the
production process: If the chemical waste of the cleaning bath can be reused and the bath can be
recycled continuously, the parts could be kept clean constantly and less varnish defects would
occur. If the process would contain a feedback loop activating a cleaning action whenever varnish
faults occur, these defects would also be reduced.
Smart Little People Modeling
SLP is helpful to understand the problem on a micro-level and to identify the zone of conflict. In the
case study of the VARNISH DEFECTS, a close look, as provoked by the SLP modeling in Figure
6, explains the question „Why does the varnish not cover heater parts at certain spots?‟. The
knowledgeable engineer may answer: „The varnish does not stick to the metal surface if the surface
is dirty. This is a sign that the cleaning bath is not effective.‟ This aspect leads to a redefinition of
the problem: „The bath for cleaning heaters before coating becomes dirty and ineffective‟, instead
of „the quality control shows defects in varnish of heaters‟. Figure 6 may also suggest that an
imperfect surface structure is partially responsible for the varnish defects.

D3 – Development of Interim Containment Action
This G8D step instructs the definition, verification and implementation of the temporary preventive
measure ICA to isolate the harmful effects of the problem from the internal / external customer
until the problem is solved and Permanent Corrective Actions are taken. For the case study, the
temporary measure implemented with the G8D study is a 100% visual control of the heaters instead
of the quality control by representative sampling. Once it was observed that the high rate of defects
only occurred with the model EC25, the 100% visual control was reduced to only this model, while
the other heaters were checked like usual with representative sampling.
This G8D step is an effective short-term measure to restrict damage resulting from a process
problem and thus very useful for industrial practice. TRIZ cannot contribute to this step. Since
TRIZ focuses on problem solving from an analytical standpoint, it does not provide any help for
„quick fixes‟.

D4 - Definition and Verification of Root Cause and Escape Point
The task of the G8D discipline D4 is defined as „the isolation and verification of the root cause by
testing each possible cause against the problem description and the data, and the isolation and
verification of the place in process where the effect of the root cause should have been detected and
contained‟. G8D suggestions, how to find the root cause and the escape point, are a time-wise
analysis of the discrepancy between “should be” and “is”, the use of a cause-effect diagram, and a
list of assessment questions. However, the G8D process is designed very flexible and open and
allows the incorporation of additional problem solving tools. Especially for problems, that have
never been solved satisfactory and that seem to require a major process change, G8D suggests tools
like robust design and benchmarking.
Analyzing a “should be/is” comparison and a cause-effect diagram, the root cause in the case study
VARNISH DEFECTS is identified as the cleaning bath loosing its effectiveness. It is detected that
the last five heaters being cleaned before the bath is changed show varnish defects. The escape
point is the cleaning bath itself.
TRIZ could help identifying the root cause of the problem in a quick and simple way. Alternatively
to the “should be/is” analysis, tracking all changes of the process during the last few months, the
root cause may be identified with TRIZ tools incorporated into the G8D structure at steps D2 and
D4. The use of TRIZ tools for the problem description under D2 already provoked the identification
of the “real” problem (heaters are not clean), which is equivalent to the root cause, instead of the
superficial apparent problem, the varnish defects. The effectiveness of TRIZ for identifying root
cause and escape point can be demonstrated as follows:
Resources
The informational resource „quality inspection‟ directly shows which model, from which production
line, at which times and time intervals the defects occur. The detected periodicity can immediately
be related to another periodicity of the same frequency in the process – the change of the cleaning
bath. Here, the systematic use of resources in the present system makes it possible to identify the
root cause and the escape point without analysis of the formerly satisfactory process in the past and
the appearance of the problem.
Ideality
The ideal final result to achieve perfect varnish coating in terms of cleanness of the heater can be
stated as: The heaters are clean by themselves. The question arises why the heaters are or become
dirty at all. If it could be prevented that the heater parts become dirty before varnish spraying, no
cleaning action would be necessary. Thus, the problem can be restated as „how can the parts stay
cleaner throughout the process‟ instead of making the repair action „cleaning bath‟ more effective.
Smart Little People Modeling
The identification of the zone of conflict at a micro level provokes the question “Where and why
does the varnish not cover heater parts?”, see Figure 6. The varnish molecules can not attach to the
heater surface if the surface is not appropriate – or if something is in the way, e.g. a dirt particle.
Thus, the root cause for the varnish defects can be identified as ineffective cleaning. Obviously, the
cleaning bath is not effective AT ALL TIMES. Thus, the root cause identified with SLP is not the
loss of effectiveness of the cleaning bath, but the lack of continuous effectiveness of the bath.
The substance-field analysis of the problem VARNISH DEFECTS is illustrated in Figure 7.
Initially, the substance S2, varnish, is acting insufficiently (dashed arrow) on the substance S1,
heater surface, via the mechanical force field FMe, spraying. In the 76 standard solutions for a TRIZ
Su-field analysis [7], the introduction of a double Su-field model is one suggestion to improve the
system. The substance S3, cleaning bath, is also acting on the heater surface, via the chemical force
field FCh, solving dirt, and thus improving the poorly controlled system of varnish spraying.
This Su-field analysis shows that the varnish coating would be satisfactory, if the heater surface was
cleaned sufficiently by a chemical action in the cleaning bath. It can thus be concluded that the
actual problem causing the varnish defects is the solution capacity of the cleaning bath.
D5 - Choice and Verification of Permanent Corrective Actions (PCAs)
This G8D step includes the generation of problem solutions and the selection of the best solution as
PCA to remove the root cause without causing undesirable effects. Based on the engineering
experience and the available knowledge of the team members, the following 8 alternative solution
concepts were generated for the case study of VARNISH DEFECTS:
         1. Installation of bigger cleaning tanks
             (slows down deterioration of cleaning solution)
         2. Automatic sensor to detect deterioration of cleaning solution, production is then
             automatically led to other tank while dirty tank is cleaned
         3. Slowing down production rate and weekend work
             (for having less throughput in the cleaning baths)
         4. Changing cleaning solution more often on a regular basis
         5. Redirecting part of the production of line 2 to line 1,
             to reduce the use and thus deterioration of cleaning solution in line 2
         6. Pre-cleaning of the heater parts with water
         7. Slowing down reduction rate
         8. Continuous filtering and cleaning of the cleaning solution
After quantitative evaluation of “must” and “should” criteria like
                              Elimination of root cause?
                              Implementation before peak season?
                              Costs?
                              Production stop?
                              Overtime work necessary for implementation?
                              Overtime work necessary for maintenance?
Alternative 4 was chosen as permanent corrective action, mainly because of its cost effectiveness
and its simplicity of implementation. Instead of every 30 minutes, the cleaning solution is now
being changed every 27 minutes. The disadvantage of increased use of cleaning solution is
mentioned.
For the determination of the permanent corrective action as a solution to the problem, generally all
TRIZ tools are applicable. The use of various TRIZ tools is demonstrated for the case study:
Ideality
For the case of VARNISH DEFECTS, the ideal final result can be stated in two different ways: 1.
The heater parts are clean all by themselves.
 2. The cleaning solution stays clean all by itself.
If the heater parts just stayed clean throughout the mounting process, the varnish problem would be
solved even without a cleaning step. There has even been previous experience with what makes the
heater parts dirty and how to reduce it: The restriction and control of hand crème use showed to be
an effective temporary measure to reduce varnish defects. The solution did not work permanently,
because the temporary change in hand crème use could not be turned into a permanent habit. Could
the workers be motivated to permanently change their hand crème habits if the company provided a
suitable alternative hand crème for free? The company could also offer part of the money being
saved on cleaning solution as a bonus to the workers, if the reduction of varnish defects is
successful. Could the use of hand crème be officially regulated in the company‟s rules like the use
of earplugs in loud machinery environment for safety reasons?
Within the huge variety of chemical solvents, can a solution be found that detaches the dirt from
metal surfaces without actually absorbing the dirt? In this case, the cleaning solution would act like
a transport medium that removes the dirt from the metal, transports it and deposits it somewhere
else (e.g. container wall), from where it can be discarded later.
Resources
The availability of four cleaning baths suggests the even distribution of the heaters to be cleaned
over all the baths in the two lines, in order to exhaust the cleaning capacity of all baths. This
suggestion leads to the alternative solution five generated with the G8D analysis.
Is the contamination of the cleaning solution causing the ineffectiveness visible and could it thus be
monitored? This thought produces G8D solution alternative 2.
Technical contradictions
The TRIZ contradiction theory can be used to formulate the problem in terms of a contradiction
between 39 standardized parameters [2]. The contradiction is that if one parameter is improved, the
other parameter deteriorates. For the solution of these contradictions, TRIZ offers 40 generalized
solution principles [3]. From empirical evidence and experience of Altshuller‟s patent analysis, the
contradiction matrix suggests a set of the most suitable solution principles for each set of
contradicting parameters. The contradiction situation in the case of VARNISH DEFECTS is
illustrated in Figure 4.
       Deteriorating                13 – Stability of 27 – Reliability           29 – Manufacturing
           Parameter                     the Object‟s (system‟s ability               Precision
       Improving                          Composition        to produce          (actual     varnish
       Parameter                    (integrity      of       perfect                  coating does
                                         varnish)           varnish)                 not     match
                                                                                      requirements)
       9 – Speed                    Solution Principles:   11, 35, 27, 28       10, 28, 32, 25
       (rate of process)            28, 33, 1, 18
       25 – Loss of Time            35, 3, 22, 5           10, 20, 4            24, 26, 28, 18
       (cycle time reduction)
       39     –     Productivity    35, 3, 22, 39          1, 35, 10, 38        18, 10, 32, 1
       (# of heaters / time unit)
              Figure 4: TRIZ Contradicting Features and Suggested Solution Principles [2], [3]
The solution principles from the 40 standard solutions, as suggested in the contradiction matrix, can
be used to generate specific solutions to the problem VARNISH DEFECTS. Below, they are listed
in the order of their magnitude of recurrence, since the principles recurring the most often are
considered most likely to solve the problem.
4 x #10: Preliminary Action
The preliminary action can be a preliminary cleaning step, or measures taken not to make the heater
parts dirty in the first place. If the parts are sandblasted or rinsed with pressurized water before the
chemical cleaning bath, the bath does not deteriorate as fast. To prevent the parts from getting dirty,
the workers should use only suitable hand crème or wear clean gloves when touching the parts.
4 x #28: Mechanics Substitution
Since the varnishing is done electrostatically, can the cleaning be done in a similar manner? Can the
cleaning solution be an electrolyte solution using charged particles to separate dirt particles from
metal surfaces, and transport and deposit the dirt to a waste deposit surface?
4 x #35: Parameter Changes:
The cleaning solution would be easily recyclable if it evaporated after cleaning, leaving the dirt at
the vessel ground as solid residue. Is dirt, especially grease, more easily solvable at higher
temperatures? If so, it is well worth heating the metal parts or the cleaning bath.
3 x #1: Segmentation
The degree of fragmentation of the production process is increased by introducing a stage of pre-
cleaning of the heater parts. This solution leads to a similar action as suggested already with the
solution principle “Preliminary Action”, and also similar to the G8D solution alternative 6.
3 x #18: Mechanical Vibration
Can cleaning be done with ultrasonic devices? Can vibrational motion of the part or in the cleaning
bath enhance the efficiency of the bath?
2 x #22: Blessing in Disguise
Could the chemical waste of the cleaning process be used to produce something? Could the metal
pieces left over from the production of heater parts be recycled?
1 x #5: Merging
The cleaning action is performed immediately before the varnish spraying, and also by means of
spraying a solvent, if necessary with consecutive rinsing and blow drying before varnishing. This
solution has the advantage of reducing the risk that the parts get dirty during the transport between
cleaning and coating, and that spraying defined amounts of cleaning solvent is more economic than
a cleaning bath.
1 x #11: Beforehand Cushioning
A sensor detects when the solution is not effective anymore. If this happens, the parts are
immediately sent to another bath for cleaning (G8D solution #2).
1 x #20: Continuity of Useful Action
Instead of using one cleaning tank for 30 minutes, than emptying and cleaning it while switching
the parts‟ cleaning to the other tank of the line, the second tank could be connected to the first tank
and be used as a continuous filtering device for the cleaning solution. If it is not possible to actually
filter and recycle the old solution, a defined amount of the used solution could be drained
continuously while it is being replaced with fresh solution.
The simplest solution for the insufficient action of the cleaning molecules on the heater surface via
a chemical field is the replacement of the field with a different field and the cleaning molecules
with a different substance. Since the varnish spraying is done electrostatically, the question arises if
this electrostatic field (as resource) could also be used for cleaning the parts. The new cleaning
substance S3 would then be some electrically charged cleaning molecules.
D6 - Implementation and Validation of Permanent Corrective Actions (PCAs)
After determination of the PCA, it needs to be implemented and the ICA needs to be removed. The
long-term results need to be monitored. TRIZ does not give any guidelines how to monitor the
success of a problem solution. However, a new, separate TRIZ analysis could be conducted after
implementation of the permanent corrective action to insure process effectiveness and to solve the
problem “how to monitor the process”.
D7 - Prevention of Recurrence
Once the permanent corrective action is implemented, recurrence of the problem has to be
prevented by modifying all parts of the system including policies, practices and procedures. The
G8D analysis should also conclude with recommendations for systemic improvements in similar
problem cases.
TRIZ generated solutions for permanent corrective actions under D4 may already include features
to prevent recurrence of the problem, e.g. automated feedback control at the quality inspection of
the process. Since TRIZ relies essentially on the generalization of a problem, and the generation of
a general solution, it is very easy to extract improvement suggestions for similar processes from a
TRIZ analysis of a particular problem.
D8 – Recognition of Team and Individual Contributions
The final step in a G8D analysis is the completion of the team experience by recognizing team and
individual contributions. This action is certainly very useful and necessary to encourage and
motivate people and to keep the working efficiency at a high level. There is no equivalent tool to
D8 in TRIZ, but a separate TRIZ analysis about how to motivate workers could be conducted.

SUMMARY AND CONCLUSIONS
G8D and TRIZ are problem-solving tools at different levels. G8D can be considered as a
superstructure of guidelines how to face a problem in industrial practice, how to deal with people,
how to implement the solution and how to insure the improved process. TRIZ in contrast deals with
the problem in detail and targets the systematic generation of a specific solution from a wide set of
general solution principles. TRIZ tools can be implemented in the G8D steps „Problem description‟
and „Definition of root cause and escape point‟, and especially in the step D5 „Generation of a
permanent corrective action‟, which is basically the problem solving step.
The effectiveness of the use of TRIZ tools in the G8D process is demonstrated with the case study
of VARNISH DEFECTS. With TRIZ, additional „smart‟ potential solutions could be generated in
short time, for example cleaning the parts by means of spraying just before the varnish coating, as
generated by the contradiction solution principle „Merging‟ and the Su-Field analysis. Spraying is
economical in terms of chemical waste, and the risk of parts getting dirty between cleaning and
varnishing is reduced. Furthermore, available resources like the varnish-spraying set-up could be
used, possibly in an electrostatic field.
Organizing the team structure and setting up intellectual, financial and substantial resources, G8D is
an effective and flexible superstructure for problem solving in a company. In contrast, the strength
of TRIZ is the generation of solution ideas beyond psychological inertia. In this case study, without
TRIZ, the idea to drop the traditional cleaning bath completely and replace it with a spraying unit,
was never considered. TRIZ may be perfectly implemented into the G8D problem solving process.
G8D provides the resources, the positive environment, and a systematic step-by-step superstructure,
without which TRIZ would be difficult to apply. TRIZ provides systematic engineering tools in
addition to the engineering knowledge and experience already available in the team, which may
speed up the solution generation and produce additional innovative solution alternatives. Thus, the
combination of the G8D process and TRIZ is an effective synergy for problem solving.

ACKNOWLEDGEMENTS
I‟m greatly indebted to Ford Motor Company in Germany and the USA for their generous
contribution of G8-D information material. Without their help, this study would not have been
possible. I hope, in turn, my analysis may be of practical use for problem solving at Ford.
Furthermore, I especially want to thank Dr. Tim Clapp, professor at NCSU, for his inspiring and
motivating guidance throughout this project.

ABOUT THE AUTHOR
Ina Bauer-Kurz is currently a Ph. D. candidate in Fiber and Polymer Science, with a minor in
Mechanical Engineering, at the College of Textiles of North Carolina State University, USA. She
will be graduating in December 2000. In November 1997, Ms. Bauer-Kurz obtained the degree
“Diplom-Ingenieur” of Mechanical Engineering from the Rheinisch-Westfälische Technische
Hochschule Aachen, Germany. Her wide research interests include the analysis and modeling of
mechanical behavior of polymeric structures. After receiving her doctorate degree, Ms. Bauer-Kurz
is intending to work in the mechanical engineering or textiles related industry in Germany or the
USA.

REFERENCES
[1] Tim Clapp, Michael Slocum:TE589A, Spring 2000, Theory of Inventive Problem Solving, class
    lectured at North Carolina State University
[2] Ellen Domb: The 39 Features of Altshuller‟s Contradiction Matrix, email editor@triz-
    joournal.com, web page http://www.triz-journal.com/archives/1998/11/d/index.htm
[3] Ellen Domb: 40 Inventive Principles With Examples, web page http://triz-
    journal.com/archives/1997/07/b/index.html
[4] Ford Motor Company, Germany, Training-manual for the G-8D Process, 1999
[5] Yuri Salamatov: TRIZ: The Right Solution at the Right Time (A Guide To Innovative Problem
    Solving), 1999 Insytec B.V., The Netherlands, ISBN 90-804680-1-0, e-mail info@insytec.com,
    web page www.insytec.com
[6] John Terninko, Alla Zusman, Boris Zlotin: STEP-by-STEP TRIZ: Creating Innovative Solution
    Concepts, 1996 Responsible Management Inc., New Hampshire, USA, ISBN 1-882382-12-9, e-
    mail john@terninko.com, web page http://www.mv.com/ipusers/rm
[7] John Terninko, Ellen Domb, Joe Miller: The Seventy-six Standard Solutions, with Examples,
    Section One and Two, web pages http://www.triz-journal.com/archives/2000/02 and
    http://www.triz-journal.com/archives/2000/03

								
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