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TRIZ Evolutionary Approach: Didactics
Available online at www.sciencedirect.com
ScienceDirect Procedia Engineering 131 (2015) 1105 – 1112
World Conference: TRIZ FUTURE, TF 2011-2014
TRIZ Evolutionary Approach: Didactics *
Victor D. Berdonosova , Elena V. Redkolisb a b
Komsomolsk-on-Amur State Technical University, Komsomolsk-on-Amur, 681024, Russia Komsomolsk-on-Amur State Technical University, Komsomolsk-on-Amur, 681000, Russia
Abstract The main points and details of usage of the TRIZ evolutionary approach were considered at some TFC conferences. For successful implementation of this approach to the educational process special didactics skills are required; they differ a little from the normal TRIZ didactics. First, particular attention is paid to the subject “Creative Imagination Development”. Secondly it is necessary to have special teaching skills as students learn the main TRIZ concepts (Laws of technical systems evolution and TRIZ tools).Thirdly, successful implementation of the TRIZ evolutionary approach is possible if TRIZ evolutionary maps are created scrupulously and they present development of systems which are related to the students’ specialty. In the report we review each of these details, consider the challenges teachers and students face and present solutions for these challenges. © Published by by Elsevier Ltd.Ltd. This is an open access article under the CC BY-NC-ND license © 2015 2015The TheAuthors. Authors. Published Elsevier (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the Scientific Committee of TFC 2011, TFC 2012, TFC 2013 and TFC 2014 – GIC. Peer-review under responsibility of the Scientific Committee of TFC 2011, TFC 2012, TFC 2013 and TFC 2014 – GIC Keywords: TRIZ; TRIZ evolutionary approach; TRIZ evolutionary maps; Evolution; Didactics; System evolution
1. Introduction The TRIZ evolutionary approach was presented and discussed at some conferences [1, 2, 3, 4]. Great attention was paid to the vision and the application of the methodology. But implementation of didactics on this topic is a significant element too. Using the approach presented in this paper TRIZ will become an educational subject at the level of Information Technologies, Mathematics, Physics and Chemistry. Special requirements emerge for the didactics of TRIZ
* Corresponding author. Tel.: +7-962-287-5141; E-mail address:[email protected].
1877-7058 © 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the Scientific Committee of TFC 2011, TFC 2012, TFC 2013 and TFC 2014 – GIC
doi:10.1016/j.proeng.2015.12.428
1106
Victor D. Berdonosov and Elena V. Redkolis / Procedia Engineering 131 (2015) 1105 – 1112
sections, the Creative Imagination Development (CID), the Laws of Systems Evolution and TRIZ tools. Teachers must experience TRIZ if they want to use TRIZ evolutionary approach as a tool of knowledge systematization and forecasting of artificial systems development. Key statements of the approach, main didactics elements and methods for learning of these elements are described in the report presented. 2. TRIZ Evolutionism: Main Statements TRIZ evolutionary approach in education is characterized with the following statements: The first statement. The evolution of a system starts from a base element (a system) [5]. This may be an incipient element or a prominent part, a stage of development of an incipient element. The examples of incipient elements are a wheel, a computer programming language, etc (Fig. 1). The first wheel was probably a tree saw cut. The first programming language is defined as direct programming language [6].
Fig. 1. (a) a tree saw cut; (b) direct programming
A system that heralded a prominent stage of the wheel development was a spoke wheel. A system in its turn that heralded a prominent stage of development of modern programming languages was the first representative of object oriented programming languages Simula-67 (Fig. 2). The second statement. The motivation forces of evolution is a contradiction between growing requirements of the society to a system and limited capacity of this system. The owner of a wheel would like the wheel to work longer but here it was required to make the wheel rim thicker. Wheels became heavy and horses drawing a cart were tired quicker.
Fig. 2. (ɚ) a spoke wheel; (b) the Structure of language Simula-67
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The contradiction appeared: if durability of a wheel increases then the weight of the wheel increases UNACCEPTABLY. The same happens with object oriented programming. A programmer works out more and more difficult programs. While debugging difficult programs he spends more time to find causes of errors. Here the contradiction appears: if difficulty of a program increases then the time of debugging increases UNACCEPTABLY. De facto, there appear not one but a variety of contradictions [6]. In case of object-oriented programming languages (OOPL) more contradictions appear: if the size of a program increases then reliability of the program decreases UNACCEPTABLY; if the quantity of hardware platforms increases then working efficiency of the program decreases UNACCEPTABLY. The third statement. A system passes to the following stage of evolution when contradictions are resolved. It is always possible to reveal those TRIZ tools which helped to solve the contradictions (inventive principle of contradictions solution; standards of sufield transformation; tool parts of laws of systems development, etc.). In case of the wheel “Local quality” and “Intermediary” were used as the inventive principles. The wooden wheel is covered with a metal rim, the weight of the wheel decreases and durability of the wheel increases. In case of the OOPL a part of contradictions is solved in the Smalltalk language: a software development environment was created with the law of transition to a super-system. It had a user interface and provided debugging facilities. With the “Intermediary” principle the sequence of program compilation was changed: programs are transferred to an intermediate representation by means of byte-codes and compiled into a machine language code. It allows initializing them at different hardware platforms [6]. In the C++ language it became possible to process handling exceptions with the “Self-service” inventive principle. This process is used to monitor program behavior to look for errors [6]. A tool “Design by contract” was worked out with the “Preliminary action” inventive principle in the Eiffel language. This tool allowed assigning different types of conditions (contracts) which are being checked during execution of the program [6]. The forth statement. All stages of a base element (system) evolution are visualized with the TRIZ evolutionary map. This map is revealed as a matrix in which the top line presents a common line of evolution of the base element and column presents evolution of separate system groups (classes) that have been developed from the base element. As for the OOPL the initial part of the TRIZ evolutionary map is presented at Figure 3
Fig. 3 The first iteration of the OOPL TRIZ evolution.
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Thus after reviewing the main statements of the TRIZ evolutionary approach in education it is possible to reveal the following advantages of this approach: x The knowledge system is similar for all subjects; x The knowledge system of a student and knowledge system of a teacher coincide; x The knowledge system has cast-iron logic: each new element within applied science appears as the result of contradiction resolution of the previous element; x It is easy to remember the transition mechanisms from element to element as there are only a few TRIZ tools; x To present the full picture of system evolution it is not required to remember all elements studied. It is enough to remember a base element (system) and to know the way to use transition mechanism; x Students have to study intensively as they move from element to element. They have to move from conceiving an inventive principle of contradiction to resolution of the concrete result (that is a new element of knowledge); x Moving from studying one element to another the students practice TRIZ tools and show positive results in untypical problems solving. 3. TRIZ Evolutionary: Didactics Based on the main statements of the TRIZ evolutionary approach the didactics of studying of the new knowledge field is the following: x A base element is chosen; x Knowledge and skills required to work with information about the base element are examined in detail; x For this base element the implementation area, its users and their common requirements are defined; x Users toughen the requirements for this element until the element does not cope with it; x Contradictions that appear in the base element due to increasing requirements are determined; x TRIZ tools that allow solving the contradictions are defined; x Ideas of transformation of the base element into a new system are proposed (a tutor improves the students’ ideas to pass to new correct systems); x Knowledge and skills required to work with information about new systems are considered in detail; x Users toughen the requirements for the systems; x The cycle is repeated until the required numbers of new elements (systems) will not be studied. Now we will consider which skill sets the students should have to learn to master each stage efficiently (Table 1). Table 1. Required skills set Stage
Skills set
Subject
1. Choosing a base element
Examined by a tutor
Applied practical disciplines
2. Transferring knowledge and skills in relation to the base element
Skills set of application knowledge area
Applied one of corresponding field of knowledge
3. Definition of an implementation area of the Skills set of application knowledge area base element, its users and their requirements
Applied one of corresponding field of knowledge
4. Toughening the requirements
Skills set of application knowledge area; propensity for unconventional creative thinking
Applied one of corresponding field of knowledge;
5. Revealing contradictions
The ability to logic thinking; knowing methods of Creative Imagination Development; contradictions definition TRIZ tools
6. Determining TRIZ tools
The ability to logic thinking; knowing TRIZ tools Creative Imagination Development;
Creative Imagination Development
TRIZ tools
Victor D. Berdonosov and Elena V. Redkolis / Procedia Engineering 131 (2015) 1105 – 1112 Stage
Skills set
Subject
7. Proposing ideas of transformation of the base element
The ability to unconventional creative thinking;
Creative Imagination Development;
Knowing laws of artificial systems development; unusual problem solving skills
Laws of artificial systems development;
8. Transferring knowledge and skills in relation to the base element (system)
Skills set of application knowledge area
Applied one of corresponding field of knowledge
9. Toughening the requirements to a new element (system)
Skills set of application knowledge area; propensity for unconventional creative thinking
Applied one of corresponding field of knowledge;
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TRIZ tools
Creative Imagination Development 10. Previous stages repeats referring to the new element(s)
See items 5-9
See items 5-9
After analyzing Table 1 it can be seen that the following subjects are required to realize the TRIZ evolutionary approach successfully: applied practical disciplines; the CID; laws of artificial systems development; TRIZ tools. The last three subjects are part of TRIZ. Our next step is to consider didactics for these subjects. 3.1. Didactics of Creative Imagination Development The CID is a multistep process. Table 2 presents the most efficient distribution of CID methods and techniques over stages in terms of the TRIZ evolutionary approach. Table 2. CID tools for implementation of the TRIZ evolutionary approach Distribution tools in stages STAGE 1. Activation of creative thinking processes Stage 1.1. Thought-provoking methods
Stage 1.2. Development of different types of thinking
PreTRIZ methods
Dialectic
brainstorming
Logic
morphological analysis
Creative
method of focal objects
Associated
synectics [7]
Algorithmic
...
Abstract
TRIZ methods [8]
Intuitive
system operator
Analytic
ideal Final result
Irrational
smart little people
Deductive
operator “size-time-price”
Inductive
...
Controlled Positive
STAGE 2. Using CID skills for implementation of items 4, 5 of the TRIZ evolutionary approach didactics. STAGE 3. Using CID skills in passing from inventive principles to a real engineering solution, item 7 of the TRIZ evolutionary approach didactics.
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At first students should learn some pre-TRIZ thought- provoking methods. The main students’ task is to extend the scope of the search at the first stages of TRIZ evolutionary approach. To use pre-TRIZ methods here is the best decision. TRIZ commenced to be trained in Komsomolsk-on-Amur State Technical University (KnASTU) in 1984. The following pre-TRIZ methods are usually used here: brainstorming [9], method of focal objects [10] and morphological analysis [11]. Some peculiarities need to be taken into account when choosing primary methods. Iouri Belski [12, 13] researched the perceptivity of different thought-provoking methods based on students using different thinking styles. Here, Harrison and Bramson defined thinking styles as follows [14]: synthesists, idealists, pragmatists, analysts and realists. But that is a separate topic. At the first stage students become familiar with forms of thinking: logic, dialectic, creative, etc. This familiarity is not so much theoretical as more a practical one. Different training games are used at this stage. These games amplify thought- provoking methods and prepare students for learning the elements of TRIZ: x Dialectical thinking, together with such games as “good- good”, “bad-bad” and “good-bad” [15] prepares them to learn and understand technical and physical contradiction concepts. x Logical thinking is always required to solve problems, starting with clarifying the descriptions and definitions (according to the law of identity) and moving on to the process of carrying out subsequent actions while rigidly adhering to logic (according to the law of reasonable grounds). This knowledge is required to learn the Algorithm for Inventive Problem Solving (ARIZ) successfully. x Creative thinking has also been shown to develop efficiently the right hemisphere of the brain. After learning the pre-TRIZ methods and becoming familiar with some thinking forms, students then study the thought-provoking methods created by Altshuller: the system operator, the ideal final result (IFR), modeling with “smart little people”, and others (Table 2) [16, 8]. Students have already been prepared for system thinking by these inventive principles. For example, the twenty-seven screen scheme of system operators trains students on the unity of opposites (aside from the 9 screens of the system itself, it is proposed to have 9 anti-system screens and 9 screens featuring a combination of a system and an anti-system). Pre-TRIZ methods do not focus on an ideal result, whereas Altshuller’s inventive principles [17] are free of this disadvantage. Each pre-TRIZ method only enlarges the field of problem solving and does not propose a procedure for narrowing it. At the end of the first stage of learning CID students must get the hang of free idea generation, the ideal final result formulation and presentation of a system in a multi-screen form. A student-centered approach is very important otherwise the efficiency of the first stage falls down. By the end of the first stage of learning CID, students should have mastered free idea generation, IFR formulation and the presentation of a system in multi-screen form. A student-centered approach is vital in order for the first stage to be completed efficiently. The following CID stages are embedded in the laws of system development and the main TRIZ tools. The above-mentioned didactics has been being used in teaching CID at KnASTU since 1995. During this time thousands of students of almost all KnASTU Departments have been trained. Teaching hours ranges from 34 to 51 depending on the fields of study and specialties. The subject is trained during one term. There have been investigations of CID training efficiency in KnASTU [15]. IQ level was estimated before and after lessons. Totally, 145 people from 11 groups of the first, second and fourth year students took part in the research. The average IQ level increased 10 points that corresponds to the number of correct tests done to be up by 24 %. Thereby the first stage of CID develops thinking and prepares students to learn and understand the basic concepts of TRIZ. 3.2. Didactics of Problem Solving After the first stage of learning CID, finished students carries out the 3d and the 4th stages of the TRIZ evolutionary didactics. Then they should use TRIZ tools to lie down and resolve contradictions (items 5-7 of the didactics). In general the above-mentioned items correspond to the method of problems solving so hereafter we will consider the didactics of this method.
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The didactics of problem solving is one of the most investigated subjects of the current day research on TRIZ. It is reviewed in the works of I. Belski [12, 13], D. Cavallucci [18, 19], G. Cascini [20], T. Nakagawa [21] and others. We will concentrate on some aspects of problem solving below. All problems can be divided into three groups depending on the related time tag: operational, tactical or strategic. Each problem type should use its own set of didactics. Engineering issues are an example of an operational problem. To solve such a problem, the inventive principles of contradiction (technical and physical) resolution [17] and sufield transformation can be used in some cases, and in most difficult cases ARIZ may be applied. But it is not possible to solve problems using only knowledge of inventive principles and sufield transformations. This is where the elements of CID come in. In order to solve problems fully, students must learn a technique for combining resource determination and the indices of effects (physical, geometrical, chemical, etc.). Tactical problems require skills that enable us to see possibilities. For this to happen, it is necessary to know the laws of system development. It is important to identify the system correctly. The Law of system completeness helps to complete this task. This Law reveals system attributes (the main useful function, target object, etc). Then it is defined the guide line of the system development via the laws of S-shaped development of the system and increase of system ideality. The next step, according to Litvin’s and Lubomirski’s approach [22], should be to train in the next set of laws that correlate with the stages of system development in line with the S-shaped curve. Solving strategic problems opens new doors to science and technology. To implement these solutions, both classical and modern TRIZ tools are required. However, it is too soon to teach students all of the tools at this stage. Active engineers who have a set of unsolved problems should become familiar with these tools. An extended didactic scheme of problem solution is presented in Table 3. Table 3. The main didactic points. Laws of systems evolution
TRIZ tools
Law of completeness
Inventive principles
Law of changing degree of system ideality
Resource analysis
Law of evolution along the S-shaped curve
Indexes of effects
Law of non-uniform evolution of sub-systems
Sufield analysis
Law of roll out – roll in
Standard on sufield tranformations
Law of coordination – disagreement
ARIZ
Law of changing degree of controllability and dynamism
Function analysis
Law of transition to a macro-level or a micro-level
Flow analysis
Law of transition to a super-system or a sub-system.
Cause-consequence analysis Roll-out …
KnASTU students learn the techniques of problems solving at engineering departments: Mechanical Engineering, Electrical Engineering, Shipbuilding, Aircraft Constructing, and Computer Technology Departments since 2002. Usually, TRIZ course consists of two subjects. The first subject is the laws of technical systems evolution. Teaching hours varies from 34 to 51 here. The second subject is the technology of creativity, which describes the basic tools of TRIZ. Teaching hours of this subject also varies from 34 to 51. Thereby students are required to learn classical TRIZ tools for revealing and laying down the contradictions (item 5 of didactics) and for proposing meaningful ideas of the base element transformation (i. e. solving problems that society want to be solved by the base element). Students also need to learn the laws of system evolution for choosing the correct way of problem solving.
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4. Summary Based on the report above we may summarize the following: Usage of the TRIZ evolutionary approach in the educational process extends TRIZ application considerably, and transforms it from a special subject to a general one. The TRIZ evolutionary approach allows structuring knowledge of any field efficiently because it provides common systematized base and considers increasing demands and contradictions solution as the primary factor of a system evolution. Presentation of systems evolution as a sequence of appeared and eventually resolved contradictions may be applied not only to systematize and study the variety of information about systems of particular subject area, but can also serve as a basis for proposals of new systems implementations. Thus, the TRIZ evolutionary approach we adapt to stages of demands analysis of future systems configurations development and of the functioning concept development of such systems. Usage of approaches and methods of the creative imagination (thinking) development improves the efficiency of predictions of future systems configurations. Usage of the TRIZ evolutionary approach produces a synergetic effect both in applied sciences and in TRIZ. References [1] Berdonosov V. Fractality of knowledge and TRIZ. Procedia Engineering, 2011. Vol. 09. pp. 659-664. [2] Berdonosov V, Redkolis E. TRIZ-Fractality of mathematics. Procedia Engineering, 2011. Vol. 09. pp. 461-472. [3] Berdonosov V, Redkolis E. TRIZ-fractality of computer-aided software engineering systems. Procedia Engineering, 2011. Vol. 9, pp. 199213. [4] Berdonosov V, Sycheva T. TRIZ-evolution of Programming System. Proceedings of the ETRIA TRIZ Future Conference, Dublin, 2-4 November 2011. Published by Institute of Technology Tallaght, 2011. ISBN 978-0-9551218-2-1. [5] Shpakovsky N. Trees of evolution. The analysis of engineering information and generation of new ideas. Moscow: TRIZ-profi, 2006. ISBN 5-9348-6048-8. [6] Berdonosov V, Zhivotoa A, Sycheva T. TRIZ evolution of the Object-Oriented Programming Languages. Proceedings of the ETRIA TRIZ Future Conference, Lisbon, 24-26 October 2012. Published by University Nova de Lisboa, 2012. ISBN 978-989-95683-1-0. [7] Gordon WJJ. Synectics: the development of creative capacity. Harper&Row, New York, 1961. [8] Zlotin B, Zusman A, Altshuller G, Philatov V. Tools of classical TRIZ. Ideation International Inc., 1999. [9] Osborn AF. Applied Imagination. New York: Charles Scriber’s Sons, 1957. [10] Whiting CHS. Creative Thinking. Reinhold, New York, 1958. [11] Zwicky F. Discovery Invention, Research Through the Morphological Approach. McMillan, 1969. [12] Belski I. Teaching Thinking and Problem Solving at University: A Course on TRIZ. Creativity and Innovation Management, 2009. Vol. 18, Issue 2. pp. 101-108. [13] Belski I. TRIZ course enhances thinking and problem solving skills of engineering students Procedia Engineering, 2011. Vol. 09. pp. 450460. [14] Harrison A, Bramson R. The Art of Thinking, NY Fnchor Press, 1982. [15] Berdonosov V. IQ increase under the influence of TRIZ. The Third TRIZ Sympo-sium in Japan, Yokohama, Japan, 2007. [16] Altshuller G. Creativity As An Exact Science: The Theory of the Solution of Inventive Problems. Translated by Anthony Williams. Gordon and Breach Science Publishers, 1984. [17] Altshuller G. 40 Principles: TRIZ Keys to Technical Innovation. Worcester, Massachusetts. Technical Innovation Center, Inc. 1997. [18] Cavallucci D. World Wide status of TRIZ perceptions and uses a survey of results. Proceedings of the ETRIA TRIZ Future Conference, 4-6 November 2009, Timisoara – Romania. [19] Cavallucci D, Rousselot F, Zanni C. Linking Contradictions and Laws of Engineering System Evolution within the TRIZ Framework. Creativity and Innovation Management, 2009. Volume 18, Issue 2. pp. 71-80. [20] Becattini N, Cascini, G, Rotini F. Correlations between the evolution of contradictions and the law of identity increase Procedia Engineering, 2011. Vol. 09. pp. 236-250. [21] Nakagawa T. Education and training of creative problem solving thinking with TRIZ / USIT. Procedia Engineering, 2011. Vol. 09. pp. 582-595. [22] Litvin S, Lubomirski A. Laws of Technical System Evolution GEN3 Partners [Electronic resource]. February 2003. http://www.metodolog.ru/00767/00767.html.
ScienceDirect Procedia Engineering 131 (2015) 1105 – 1112
World Conference: TRIZ FUTURE, TF 2011-2014
TRIZ Evolutionary Approach: Didactics *
Victor D. Berdonosova , Elena V. Redkolisb a b
Komsomolsk-on-Amur State Technical University, Komsomolsk-on-Amur, 681024, Russia Komsomolsk-on-Amur State Technical University, Komsomolsk-on-Amur, 681000, Russia
Abstract The main points and details of usage of the TRIZ evolutionary approach were considered at some TFC conferences. For successful implementation of this approach to the educational process special didactics skills are required; they differ a little from the normal TRIZ didactics. First, particular attention is paid to the subject “Creative Imagination Development”. Secondly it is necessary to have special teaching skills as students learn the main TRIZ concepts (Laws of technical systems evolution and TRIZ tools).Thirdly, successful implementation of the TRIZ evolutionary approach is possible if TRIZ evolutionary maps are created scrupulously and they present development of systems which are related to the students’ specialty. In the report we review each of these details, consider the challenges teachers and students face and present solutions for these challenges. © Published by by Elsevier Ltd.Ltd. This is an open access article under the CC BY-NC-ND license © 2015 2015The TheAuthors. Authors. Published Elsevier (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the Scientific Committee of TFC 2011, TFC 2012, TFC 2013 and TFC 2014 – GIC. Peer-review under responsibility of the Scientific Committee of TFC 2011, TFC 2012, TFC 2013 and TFC 2014 – GIC Keywords: TRIZ; TRIZ evolutionary approach; TRIZ evolutionary maps; Evolution; Didactics; System evolution
1. Introduction The TRIZ evolutionary approach was presented and discussed at some conferences [1, 2, 3, 4]. Great attention was paid to the vision and the application of the methodology. But implementation of didactics on this topic is a significant element too. Using the approach presented in this paper TRIZ will become an educational subject at the level of Information Technologies, Mathematics, Physics and Chemistry. Special requirements emerge for the didactics of TRIZ
* Corresponding author. Tel.: +7-962-287-5141; E-mail address:[email protected].
1877-7058 © 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the Scientific Committee of TFC 2011, TFC 2012, TFC 2013 and TFC 2014 – GIC
doi:10.1016/j.proeng.2015.12.428
1106
Victor D. Berdonosov and Elena V. Redkolis / Procedia Engineering 131 (2015) 1105 – 1112
sections, the Creative Imagination Development (CID), the Laws of Systems Evolution and TRIZ tools. Teachers must experience TRIZ if they want to use TRIZ evolutionary approach as a tool of knowledge systematization and forecasting of artificial systems development. Key statements of the approach, main didactics elements and methods for learning of these elements are described in the report presented. 2. TRIZ Evolutionism: Main Statements TRIZ evolutionary approach in education is characterized with the following statements: The first statement. The evolution of a system starts from a base element (a system) [5]. This may be an incipient element or a prominent part, a stage of development of an incipient element. The examples of incipient elements are a wheel, a computer programming language, etc (Fig. 1). The first wheel was probably a tree saw cut. The first programming language is defined as direct programming language [6].
Fig. 1. (a) a tree saw cut; (b) direct programming
A system that heralded a prominent stage of the wheel development was a spoke wheel. A system in its turn that heralded a prominent stage of development of modern programming languages was the first representative of object oriented programming languages Simula-67 (Fig. 2). The second statement. The motivation forces of evolution is a contradiction between growing requirements of the society to a system and limited capacity of this system. The owner of a wheel would like the wheel to work longer but here it was required to make the wheel rim thicker. Wheels became heavy and horses drawing a cart were tired quicker.
Fig. 2. (ɚ) a spoke wheel; (b) the Structure of language Simula-67
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The contradiction appeared: if durability of a wheel increases then the weight of the wheel increases UNACCEPTABLY. The same happens with object oriented programming. A programmer works out more and more difficult programs. While debugging difficult programs he spends more time to find causes of errors. Here the contradiction appears: if difficulty of a program increases then the time of debugging increases UNACCEPTABLY. De facto, there appear not one but a variety of contradictions [6]. In case of object-oriented programming languages (OOPL) more contradictions appear: if the size of a program increases then reliability of the program decreases UNACCEPTABLY; if the quantity of hardware platforms increases then working efficiency of the program decreases UNACCEPTABLY. The third statement. A system passes to the following stage of evolution when contradictions are resolved. It is always possible to reveal those TRIZ tools which helped to solve the contradictions (inventive principle of contradictions solution; standards of sufield transformation; tool parts of laws of systems development, etc.). In case of the wheel “Local quality” and “Intermediary” were used as the inventive principles. The wooden wheel is covered with a metal rim, the weight of the wheel decreases and durability of the wheel increases. In case of the OOPL a part of contradictions is solved in the Smalltalk language: a software development environment was created with the law of transition to a super-system. It had a user interface and provided debugging facilities. With the “Intermediary” principle the sequence of program compilation was changed: programs are transferred to an intermediate representation by means of byte-codes and compiled into a machine language code. It allows initializing them at different hardware platforms [6]. In the C++ language it became possible to process handling exceptions with the “Self-service” inventive principle. This process is used to monitor program behavior to look for errors [6]. A tool “Design by contract” was worked out with the “Preliminary action” inventive principle in the Eiffel language. This tool allowed assigning different types of conditions (contracts) which are being checked during execution of the program [6]. The forth statement. All stages of a base element (system) evolution are visualized with the TRIZ evolutionary map. This map is revealed as a matrix in which the top line presents a common line of evolution of the base element and column presents evolution of separate system groups (classes) that have been developed from the base element. As for the OOPL the initial part of the TRIZ evolutionary map is presented at Figure 3
Fig. 3 The first iteration of the OOPL TRIZ evolution.
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Victor D. Berdonosov and Elena V. Redkolis / Procedia Engineering 131 (2015) 1105 – 1112
Thus after reviewing the main statements of the TRIZ evolutionary approach in education it is possible to reveal the following advantages of this approach: x The knowledge system is similar for all subjects; x The knowledge system of a student and knowledge system of a teacher coincide; x The knowledge system has cast-iron logic: each new element within applied science appears as the result of contradiction resolution of the previous element; x It is easy to remember the transition mechanisms from element to element as there are only a few TRIZ tools; x To present the full picture of system evolution it is not required to remember all elements studied. It is enough to remember a base element (system) and to know the way to use transition mechanism; x Students have to study intensively as they move from element to element. They have to move from conceiving an inventive principle of contradiction to resolution of the concrete result (that is a new element of knowledge); x Moving from studying one element to another the students practice TRIZ tools and show positive results in untypical problems solving. 3. TRIZ Evolutionary: Didactics Based on the main statements of the TRIZ evolutionary approach the didactics of studying of the new knowledge field is the following: x A base element is chosen; x Knowledge and skills required to work with information about the base element are examined in detail; x For this base element the implementation area, its users and their common requirements are defined; x Users toughen the requirements for this element until the element does not cope with it; x Contradictions that appear in the base element due to increasing requirements are determined; x TRIZ tools that allow solving the contradictions are defined; x Ideas of transformation of the base element into a new system are proposed (a tutor improves the students’ ideas to pass to new correct systems); x Knowledge and skills required to work with information about new systems are considered in detail; x Users toughen the requirements for the systems; x The cycle is repeated until the required numbers of new elements (systems) will not be studied. Now we will consider which skill sets the students should have to learn to master each stage efficiently (Table 1). Table 1. Required skills set Stage
Skills set
Subject
1. Choosing a base element
Examined by a tutor
Applied practical disciplines
2. Transferring knowledge and skills in relation to the base element
Skills set of application knowledge area
Applied one of corresponding field of knowledge
3. Definition of an implementation area of the Skills set of application knowledge area base element, its users and their requirements
Applied one of corresponding field of knowledge
4. Toughening the requirements
Skills set of application knowledge area; propensity for unconventional creative thinking
Applied one of corresponding field of knowledge;
5. Revealing contradictions
The ability to logic thinking; knowing methods of Creative Imagination Development; contradictions definition TRIZ tools
6. Determining TRIZ tools
The ability to logic thinking; knowing TRIZ tools Creative Imagination Development;
Creative Imagination Development
TRIZ tools
Victor D. Berdonosov and Elena V. Redkolis / Procedia Engineering 131 (2015) 1105 – 1112 Stage
Skills set
Subject
7. Proposing ideas of transformation of the base element
The ability to unconventional creative thinking;
Creative Imagination Development;
Knowing laws of artificial systems development; unusual problem solving skills
Laws of artificial systems development;
8. Transferring knowledge and skills in relation to the base element (system)
Skills set of application knowledge area
Applied one of corresponding field of knowledge
9. Toughening the requirements to a new element (system)
Skills set of application knowledge area; propensity for unconventional creative thinking
Applied one of corresponding field of knowledge;
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TRIZ tools
Creative Imagination Development 10. Previous stages repeats referring to the new element(s)
See items 5-9
See items 5-9
After analyzing Table 1 it can be seen that the following subjects are required to realize the TRIZ evolutionary approach successfully: applied practical disciplines; the CID; laws of artificial systems development; TRIZ tools. The last three subjects are part of TRIZ. Our next step is to consider didactics for these subjects. 3.1. Didactics of Creative Imagination Development The CID is a multistep process. Table 2 presents the most efficient distribution of CID methods and techniques over stages in terms of the TRIZ evolutionary approach. Table 2. CID tools for implementation of the TRIZ evolutionary approach Distribution tools in stages STAGE 1. Activation of creative thinking processes Stage 1.1. Thought-provoking methods
Stage 1.2. Development of different types of thinking
PreTRIZ methods
Dialectic
brainstorming
Logic
morphological analysis
Creative
method of focal objects
Associated
synectics [7]
Algorithmic
...
Abstract
TRIZ methods [8]
Intuitive
system operator
Analytic
ideal Final result
Irrational
smart little people
Deductive
operator “size-time-price”
Inductive
...
Controlled Positive
STAGE 2. Using CID skills for implementation of items 4, 5 of the TRIZ evolutionary approach didactics. STAGE 3. Using CID skills in passing from inventive principles to a real engineering solution, item 7 of the TRIZ evolutionary approach didactics.
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At first students should learn some pre-TRIZ thought- provoking methods. The main students’ task is to extend the scope of the search at the first stages of TRIZ evolutionary approach. To use pre-TRIZ methods here is the best decision. TRIZ commenced to be trained in Komsomolsk-on-Amur State Technical University (KnASTU) in 1984. The following pre-TRIZ methods are usually used here: brainstorming [9], method of focal objects [10] and morphological analysis [11]. Some peculiarities need to be taken into account when choosing primary methods. Iouri Belski [12, 13] researched the perceptivity of different thought-provoking methods based on students using different thinking styles. Here, Harrison and Bramson defined thinking styles as follows [14]: synthesists, idealists, pragmatists, analysts and realists. But that is a separate topic. At the first stage students become familiar with forms of thinking: logic, dialectic, creative, etc. This familiarity is not so much theoretical as more a practical one. Different training games are used at this stage. These games amplify thought- provoking methods and prepare students for learning the elements of TRIZ: x Dialectical thinking, together with such games as “good- good”, “bad-bad” and “good-bad” [15] prepares them to learn and understand technical and physical contradiction concepts. x Logical thinking is always required to solve problems, starting with clarifying the descriptions and definitions (according to the law of identity) and moving on to the process of carrying out subsequent actions while rigidly adhering to logic (according to the law of reasonable grounds). This knowledge is required to learn the Algorithm for Inventive Problem Solving (ARIZ) successfully. x Creative thinking has also been shown to develop efficiently the right hemisphere of the brain. After learning the pre-TRIZ methods and becoming familiar with some thinking forms, students then study the thought-provoking methods created by Altshuller: the system operator, the ideal final result (IFR), modeling with “smart little people”, and others (Table 2) [16, 8]. Students have already been prepared for system thinking by these inventive principles. For example, the twenty-seven screen scheme of system operators trains students on the unity of opposites (aside from the 9 screens of the system itself, it is proposed to have 9 anti-system screens and 9 screens featuring a combination of a system and an anti-system). Pre-TRIZ methods do not focus on an ideal result, whereas Altshuller’s inventive principles [17] are free of this disadvantage. Each pre-TRIZ method only enlarges the field of problem solving and does not propose a procedure for narrowing it. At the end of the first stage of learning CID students must get the hang of free idea generation, the ideal final result formulation and presentation of a system in a multi-screen form. A student-centered approach is very important otherwise the efficiency of the first stage falls down. By the end of the first stage of learning CID, students should have mastered free idea generation, IFR formulation and the presentation of a system in multi-screen form. A student-centered approach is vital in order for the first stage to be completed efficiently. The following CID stages are embedded in the laws of system development and the main TRIZ tools. The above-mentioned didactics has been being used in teaching CID at KnASTU since 1995. During this time thousands of students of almost all KnASTU Departments have been trained. Teaching hours ranges from 34 to 51 depending on the fields of study and specialties. The subject is trained during one term. There have been investigations of CID training efficiency in KnASTU [15]. IQ level was estimated before and after lessons. Totally, 145 people from 11 groups of the first, second and fourth year students took part in the research. The average IQ level increased 10 points that corresponds to the number of correct tests done to be up by 24 %. Thereby the first stage of CID develops thinking and prepares students to learn and understand the basic concepts of TRIZ. 3.2. Didactics of Problem Solving After the first stage of learning CID, finished students carries out the 3d and the 4th stages of the TRIZ evolutionary didactics. Then they should use TRIZ tools to lie down and resolve contradictions (items 5-7 of the didactics). In general the above-mentioned items correspond to the method of problems solving so hereafter we will consider the didactics of this method.
Victor D. Berdonosov and Elena V. Redkolis / Procedia Engineering 131 (2015) 1105 – 1112
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The didactics of problem solving is one of the most investigated subjects of the current day research on TRIZ. It is reviewed in the works of I. Belski [12, 13], D. Cavallucci [18, 19], G. Cascini [20], T. Nakagawa [21] and others. We will concentrate on some aspects of problem solving below. All problems can be divided into three groups depending on the related time tag: operational, tactical or strategic. Each problem type should use its own set of didactics. Engineering issues are an example of an operational problem. To solve such a problem, the inventive principles of contradiction (technical and physical) resolution [17] and sufield transformation can be used in some cases, and in most difficult cases ARIZ may be applied. But it is not possible to solve problems using only knowledge of inventive principles and sufield transformations. This is where the elements of CID come in. In order to solve problems fully, students must learn a technique for combining resource determination and the indices of effects (physical, geometrical, chemical, etc.). Tactical problems require skills that enable us to see possibilities. For this to happen, it is necessary to know the laws of system development. It is important to identify the system correctly. The Law of system completeness helps to complete this task. This Law reveals system attributes (the main useful function, target object, etc). Then it is defined the guide line of the system development via the laws of S-shaped development of the system and increase of system ideality. The next step, according to Litvin’s and Lubomirski’s approach [22], should be to train in the next set of laws that correlate with the stages of system development in line with the S-shaped curve. Solving strategic problems opens new doors to science and technology. To implement these solutions, both classical and modern TRIZ tools are required. However, it is too soon to teach students all of the tools at this stage. Active engineers who have a set of unsolved problems should become familiar with these tools. An extended didactic scheme of problem solution is presented in Table 3. Table 3. The main didactic points. Laws of systems evolution
TRIZ tools
Law of completeness
Inventive principles
Law of changing degree of system ideality
Resource analysis
Law of evolution along the S-shaped curve
Indexes of effects
Law of non-uniform evolution of sub-systems
Sufield analysis
Law of roll out – roll in
Standard on sufield tranformations
Law of coordination – disagreement
ARIZ
Law of changing degree of controllability and dynamism
Function analysis
Law of transition to a macro-level or a micro-level
Flow analysis
Law of transition to a super-system or a sub-system.
Cause-consequence analysis Roll-out …
KnASTU students learn the techniques of problems solving at engineering departments: Mechanical Engineering, Electrical Engineering, Shipbuilding, Aircraft Constructing, and Computer Technology Departments since 2002. Usually, TRIZ course consists of two subjects. The first subject is the laws of technical systems evolution. Teaching hours varies from 34 to 51 here. The second subject is the technology of creativity, which describes the basic tools of TRIZ. Teaching hours of this subject also varies from 34 to 51. Thereby students are required to learn classical TRIZ tools for revealing and laying down the contradictions (item 5 of didactics) and for proposing meaningful ideas of the base element transformation (i. e. solving problems that society want to be solved by the base element). Students also need to learn the laws of system evolution for choosing the correct way of problem solving.
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4. Summary Based on the report above we may summarize the following: Usage of the TRIZ evolutionary approach in the educational process extends TRIZ application considerably, and transforms it from a special subject to a general one. The TRIZ evolutionary approach allows structuring knowledge of any field efficiently because it provides common systematized base and considers increasing demands and contradictions solution as the primary factor of a system evolution. Presentation of systems evolution as a sequence of appeared and eventually resolved contradictions may be applied not only to systematize and study the variety of information about systems of particular subject area, but can also serve as a basis for proposals of new systems implementations. Thus, the TRIZ evolutionary approach we adapt to stages of demands analysis of future systems configurations development and of the functioning concept development of such systems. Usage of approaches and methods of the creative imagination (thinking) development improves the efficiency of predictions of future systems configurations. Usage of the TRIZ evolutionary approach produces a synergetic effect both in applied sciences and in TRIZ. References [1] Berdonosov V. Fractality of knowledge and TRIZ. Procedia Engineering, 2011. Vol. 09. pp. 659-664. [2] Berdonosov V, Redkolis E. TRIZ-Fractality of mathematics. Procedia Engineering, 2011. Vol. 09. pp. 461-472. [3] Berdonosov V, Redkolis E. TRIZ-fractality of computer-aided software engineering systems. Procedia Engineering, 2011. Vol. 9, pp. 199213. [4] Berdonosov V, Sycheva T. TRIZ-evolution of Programming System. Proceedings of the ETRIA TRIZ Future Conference, Dublin, 2-4 November 2011. Published by Institute of Technology Tallaght, 2011. ISBN 978-0-9551218-2-1. [5] Shpakovsky N. Trees of evolution. The analysis of engineering information and generation of new ideas. Moscow: TRIZ-profi, 2006. ISBN 5-9348-6048-8. [6] Berdonosov V, Zhivotoa A, Sycheva T. TRIZ evolution of the Object-Oriented Programming Languages. Proceedings of the ETRIA TRIZ Future Conference, Lisbon, 24-26 October 2012. Published by University Nova de Lisboa, 2012. ISBN 978-989-95683-1-0. [7] Gordon WJJ. Synectics: the development of creative capacity. Harper&Row, New York, 1961. [8] Zlotin B, Zusman A, Altshuller G, Philatov V. Tools of classical TRIZ. Ideation International Inc., 1999. [9] Osborn AF. Applied Imagination. New York: Charles Scriber’s Sons, 1957. [10] Whiting CHS. Creative Thinking. Reinhold, New York, 1958. [11] Zwicky F. Discovery Invention, Research Through the Morphological Approach. McMillan, 1969. [12] Belski I. Teaching Thinking and Problem Solving at University: A Course on TRIZ. Creativity and Innovation Management, 2009. Vol. 18, Issue 2. pp. 101-108. [13] Belski I. TRIZ course enhances thinking and problem solving skills of engineering students Procedia Engineering, 2011. Vol. 09. pp. 450460. [14] Harrison A, Bramson R. The Art of Thinking, NY Fnchor Press, 1982. [15] Berdonosov V. IQ increase under the influence of TRIZ. The Third TRIZ Sympo-sium in Japan, Yokohama, Japan, 2007. [16] Altshuller G. Creativity As An Exact Science: The Theory of the Solution of Inventive Problems. Translated by Anthony Williams. Gordon and Breach Science Publishers, 1984. [17] Altshuller G. 40 Principles: TRIZ Keys to Technical Innovation. Worcester, Massachusetts. Technical Innovation Center, Inc. 1997. [18] Cavallucci D. World Wide status of TRIZ perceptions and uses a survey of results. Proceedings of the ETRIA TRIZ Future Conference, 4-6 November 2009, Timisoara – Romania. [19] Cavallucci D, Rousselot F, Zanni C. Linking Contradictions and Laws of Engineering System Evolution within the TRIZ Framework. Creativity and Innovation Management, 2009. Volume 18, Issue 2. pp. 71-80. [20] Becattini N, Cascini, G, Rotini F. Correlations between the evolution of contradictions and the law of identity increase Procedia Engineering, 2011. Vol. 09. pp. 236-250. [21] Nakagawa T. Education and training of creative problem solving thinking with TRIZ / USIT. Procedia Engineering, 2011. Vol. 09. pp. 582-595. [22] Litvin S, Lubomirski A. Laws of Technical System Evolution GEN3 Partners [Electronic resource]. February 2003. http://www.metodolog.ru/00767/00767.html.