Image Image Image Image Image Image Image Image Image Image
Scroll to top

Top

Structural Scheme For Solving a Problem Using TRIZ

| On 10, Jan 2002

Structural Scheme For Solving a Problem Using TRIZ

Samsung Advanced Institute of Techology

N. Shpakovsky, PhD, TRIZ consultant of SAMSUNG (South Korea). nick_sh2000@mail.ru
V. Lenjashin, TRIZ consultant of SAMSUNG (South Korea). vassili@samsung.com
Hyo June Kim, TRIZ specialists of SAMSUNG (South Korea). hjkim@sait.samsung.co.kr

An earlier version of this paper was presented at the European TRIZ Association meeting, “TRIZ Future 2001,” November 2001.

Abstract: TRIZ /1/ gives main attention to the methods of revealing and resolving contradictions. For this purpose a sufficiently wide tool basis was elaborated, which includes ARIZ and its different modifications. However, the experience in solving real production problems proves that the greatest difficulties occur at the initial stage of work with a problem proposed by a customer. In the inextricable tangle of problems, the formulation of which is not always clear enough, it is sometimes difficult to see the possibilities to use the tool basis of TRIZ and, moreover, of ARIZ that starts immediately from formulating a mini-problem. If the real causes of a problem are discerned, the problem is often solved by simple TRIZ tools and sometimes it is just removed. The initial situation analysis, characteristic of the early versions of ARIZ, was forced out of TRIZ and became a kind of independent direction, which, in a certain sense, loses connection with the further problem-solving process. Obviously, certain steps are taken in this direction /2/, but they still do not constitute a self-contained problem-solving technology.

This work presents a scheme of problem solving that starts from the analysis of the initial situation and ends in solving a mini- or a maxi-problem. The scheme was developed on the basis of practical use of TRIZ and is used by the authors in their work for the company SAMSUNG.

Actions in a monitoring area.

Attempts to solve a problem are generally made by the customer’s specialists before applying to TRIZ experts. The customer’s experts try to solve the problem at a required level but are not successful. However, owing to their attempts to do this, a comparatively well-explored information area is formed around the initial problem. We call it a “monitoring area” (Fig.1). In the analysis of the initial situation, it is useful to thoroughly investigate this area by employing the knowledge of experts and analyzing the previous experience in solving this problem and the obtained concrete proposals. Special attention should be paid to the proposals rejected by the customer due to their obvious impracticability.

The use of G.S.Altshuller’s multi-screen scheme that allows determining subsystems of a technical system (TS) under analysis and the supersystem to which this TS belongs, also yields good results while working in the monitoring zone. Besides, it is useful to establish the entire chain of evolution of the analyzed TS, at least its closest prototypes. This allows a better understanding of the logic of transformations preceding the appearance of the analyzed TS. It often happens that defects existing at one stage of its development transfer to a next stage. Moreover, improvements introduced at some stage can also cause undesirable effects in future.

An important tool of investigating the monitoring area is the analysis of interacting technical systems. For this purpose V.Lenyashin and L.Chechurin /3/ propose to determine a “harmful” and a “useful” technical system and to establish peculiarities of their interaction by acting according to the following scheme:

  • determining the “useful” product of a TS in which a problem occurs;

  • determining all constituent parts of the TS that produces this product and the character of interaction between them (with a compulsory inclusion of an energy source and an object worked);

  • determining the “harmful” product that occurs spontaneously during the operation of the “useful” TS and causes a removable disadvantage;

  • determining all the constituent parts of the harmful TS that produces this “harmful” product, and the character of interaction between them (similarly to the “useful” TS);

  • Finding elements common for the “useful” and “harmful” technical systems.

Figure. 1: Full structure scheme of the problem resolving system.

Then it is necessary to remove the action of the “harmful” TS while preserving to the maximum the action of the “useful” one. Using the effects of G.S.Altshuller’s laws of technical system evolution can do this.

  1. To terminate the action of “harmful” TS, it is necessary and sufficient to remove any of its parts (engine, transmission, working component or control unit) determined in accordance with the law of technical system completeness. As a rule, it is most convenient to remove the transmission of the “harmful” TS. It often happens that some elements of the “harmful” TS do not participate or play a very insignificant role in the operation of the “useful” TS (normally they come from the previous system due to the psychological inertia). In this case they can be relatively easily removed by eliminating the “useful” TS’s disadvantage itself.

  2. As stated by the law of energy conductivity, to prevent the action of the “harmful” TS, it is necessary and sufficient to break the passing of energy through all of its parts. In this case the system parts themselves can remain unchanged.

  3. To deactivate the “harmful” technical system, it is necessary and sufficient to cause mismatch in operation (operational periodicity) of parts of this system. The system parts themselves can remain unchanged. The law of harmonization of parts of a system requires that its parts operate in a certain sequence. Deliberate violation will inevitably cause deactivation of the “harmful” TS, just what we aimed to do.

The problem of search for and elimination of the action of the “harmful” TS is complicated by the fact that this system is normally an ideal TS. That is, the system does not exist (nobody did anything to organize it) while the product appears. This is just why it is difficult enough to see and to prevent its action.

When searching for possible ways of solving the problem thus treated, it is convenient to use the notion of “anti-system” introduced by G.S.Altshuller. The anti-system is a system that performs an action opposite to the “harmful” action. This approach also considerably simplifies the search for the elements of the “harmful” system while analyzing it, particularly in case it is not quite clear what is the cause of the “harmful” action. Something of the kind was done in developing the “analysis of inverse problem” /4/, but without linking it to the laws of technical system evolution – theoretical foundations of TRIZ. The proposals of the customer’s experts and the analysis of interaction between the useful and harmful system serve as a basis for specifying the initial problem and proposing a number of hypotheses of its solution.

Diagram “Christmas Tree”.

The diagram reflects the scheme of solving a single selected problem. It is used after the initial problem has been analyzed in the monitoring area and hypotheses of its solution have been propounded. In making the diagram (Fig.2.), the basic theses developed by N.Khomenko in OTSM-TRIZ /5/ were used. The use of this diagram implies permanent specification of the situation by passing from a given problem to its abstract model, constructing an abstract model of its solution, specifying this model and proposing one or several conceptual solutions on this basis.

Figure. 2: “Christmas tree” diagram. (The diagram was worked out with participation of E.Novitskaja).

Two axes are the basis of the diagram:

  • axis X is the axis of the degree of abstraction of the situation;

  • axis Y is the axis of ideality of obtained solution concepts.

The left part of the diagram is the object area where specific objects are considered and all actions are performed with these objects. The right part is the abstract area where all the considerations and actions are performed with abstract descriptions of objects.

The object and abstract areas are separated by a conventional line that is called the “concept axis”. Here conceptual descriptions of situations are situated in which both real objects and their parameters and abstract descriptions are mixed on equality with one another. At the apex of the diagram “Christmas Tree”, all the three situational levels – object, conceptual and abstract – merge. A special situation occurs. It is called IFR – an ideal final result.

The problem solving process illustrated by the diagram includes the following transitions:

1. Transition from the initial problem to its conceptual model.

In this case, the “skeleton” is singled out of the problem conditions. The problem is freed from redundant details. It is necessary to specify the conflicting objects and the peculiarities of their interaction in time and space, as well as the ideal final result for the considered situation.

2. Constructing a technical contradiction.

To do this, it is necessary to determine how we can improve the desired parameters, which characterize the performance of the main useful function, by means of a conventional method. Then we must check which parameter of the system worsens to an admissible extent. Then we construct one or several contradictions in accordance with the list of characteristic features by G.S.Altshuller. Having received several ideas of solving the technical contradiction, one can try to find intermediate concepts of solving the problem by using available resources.

3. Constructing an abstract model of a problem.

To do this, it is convenient to use the rules of su-field analysis and to draw a scheme of interaction of the elements in the form of a su-field model. All the objects participating in the conceptual model are replaced with abstract “substances”, while the forces and interactions are replaced with corresponding “fields” that characterize the interaction between the objects.

4. Constructing an abstract problem-solving model.

The solution model is constructed by transforming the abstract model of the problem by means of:

  1. Fundamental knowledge of the problem solver – the so-called “experience”.

  2. The use of analogous problems.

  3. The rules of standard solution of problems.

The abstract model solved, it is necessary to make an attempt to find preliminary problem- solving concepts by analyzing the available resources once again.

5. Determining the requirements for the X-elements.

This is a very important stage, which allows making a description of the X-element necessary for the search for a real object with available resources. The X-element can be conveniently described according to the following scheme:

“Element – Feature of Element – Value of Feature” proposed by N. Khomenko.

6. Constructing a physical contradiction.

A physical contradiction occurs when the requirements for the X-element or its part are physically mutually exclusive. Resolving this contradiction makes it possible to maximally specify the situation and to obtain a conceptual solution, the closest one to the ideal solution.

7. Constructing a final solution.

All the three concepts obtained in the process of solving, as well as the experiments are used to construct a final solution of the considered single mini-problem.

3. Solving a mini-problem.

A mini-problem implies the elimination of disadvantages without a considerable transformation of the initial problem, only by means of available or easy-to-introduce resources. With limited resources, the solution of such a problem is often more complicated than in case of a maxi-problem that allows considerable changes to be made in the initial system.

A mini-problem is solved after propounding several solution hypotheses obtained together with the customer’s experts by analyzing the monitoring area. A hypothesis is the main, general idea of eliminating a disadvantage. The entire problem-solving process consists in specifying separate hypotheses, constructing their object embodiment and specifying their applicability for solving the main problem in a given situation (Fig.3).

Figure. 3: Structure scheme of the mini-problem solution.

In the object realization of each hypothesis, the following situations may occur:

  1. No obstacles occur and the solution is produced automatically, by a direct application of known methods. No contradiction occurs.

  2. It is impossible to realize the hypothesis by the known methods. A contradiction occurs when using such methods. In this case, a solution is obtained using the diagram “Christmas Tree”.

  3. After solving one of the problems arising during the hypothesis realization, new problems occur and it is impossible to realize the solution of the previous problems without solving these new ones. In this case, a situation occurs which is very similar to the one described by N.Khomenko in the technology “A flow of problems”, when some partial solutions merge at the end to form a final solution to a problem.

After object realization of each hypothesis, a final solution of a mini-problem is constructed. To do this, the object realization most suitable for specific conditions is selected together with the customer’s experts. It is supplemented with other realizations or their useful properties. The method of constructing a final solution of a mini-problem has very much in common with the method of combining alternative systems /6/.

4. Solving a maxi-problem.

Solving a maxi-problem is implies considerable transformation of the initial technical system and its technological processes. The solution process is similar to the technological forecasting process. Often enough, after solving such a problem we obtain a number of patentable proposals concerning the development of the production process and the technical system itself.

A maxi-problem is solved by the following scheme:

“Desirable product – Production process – Process-realizing TS” /Fig.4/.

Figure. 4: Structure scheme of the maxi-problem solution.

First it is necessary to accurately determine the requirements for the product produced by the TS under consideration. We do it by using the information obtained through analyzing the monitoring area and solving mini-problems. Then, with the product specified, we construct a desired process of its production. This is in fact a set of operations to be fulfilled by some “desirable TS” which will realize this process. Thus, we fulfill the requirements of the law of harmonization of parts of a system.

Having specified the desirable process, it is necessary to construct the model of the “desirable TS”. This is done in accordance with the law of technical system completeness and the law of through energy conductivity. In this case, it is relatively easy to use the body of information obtained by analyzing the monitoring area and solving a mini-problem.

The distinctive feature of our approach is as follows. When obtaining each concept of a mini-problem solution, it is very useful to write out the principle idea of this concept. This may be both the type of transformation used in problem solving and substance and fields used for this purpose, or the combination of both. The situations thus obtained are analyzed with the aid of the trends of technical system development /7/ and their most ideal embodiment is selected, which is then used for constructing a model of a “desirable TS”.

For instance, if a transformed object was monolithic in an initial TS, and, to solve a mini-problem, we used liquid, it would be very useful to analyze how the problem could be solved by using other monolith transformations lying in the “Segmentation” axis. It is necessary to check he applicability of foam, gases, plasma, electric and magnetic fields and vacuum to constructing the model of a “desirable TS”.

If we use a principle, for instance, mono-bi-poly, we must check how our “desirable TS” can operate when an additional object or several objects are introduced, or when the object being transformed passes to a supersystem. Having received a conceptual model of the “desirable TS” (something close to the notion of the “ideal final result”), it is necessary to solve the problem occurring in transition from this model to its real embodiment. In TRIZ, there is a good say: To step back from the IFR.

By performing the above actions, we receive the maximum efficient transformations that solve the initial problem and point to the most efficient ways of development of the initial technical system.

List of References.

  1. Altshuller, Genrikh. “The Innovative Algorithm. TRIZ, Systematic Innovation and Technical Creativity.” Technical Innovation Center, INC. Worcester, MA. 1999.

  2. G.Ivanov, A. Bystritsky. “Formulating of Creative Problems”. MATRIZ. Cheljabinsk. 2000 (in Russian).

  3. TRIZ forum (in Russian). <http://www.geocities.com/cepreu4/MyTRIZ.html>
  4. G. Altshuller, B. Zlotin, A. Zusman, V. Filatov. “Search of the New Ideas: From Inspiration to Technology.” Kishinev. Karta Moldovenyaske, 1989 (in Russian).

  5. N. Knomenko. “TRIZ how General Theory of Strong Thinking (OTSM)”. (In Russian).
    <http://www.triz.minsk.by/e/prs/kho.htm>

  6. S.Litvin, V.Gerasimov. ‘’Development of Alternative Systems by their Association in Supersystem.“ TRIZ Journal. 1990. 1.1. (In Russian).

  7. TechOptimizer®/Prediction/ Trends of Technology Evolution.