Phương pháp nghiên cứu khoa học: applying triz and the theory of ideal supersmart learning to computing systems ultimate ideal autonomous objects, strategic problem solving, and product innovation

[ Previous ] [ Home Page ] [ Up Level ] [ Next ] Applying TRIZ and the Theory of Ideal SuperSmart Learning to Computing Systems: Ultimate Ideal Autonomous Objects, Strategic Problem Solving, and Product Innovation By Dr Rodney K King r.k.king@supersmartnetwork.com Introduction About a month ago, I received an e-mail regarding OOPSLA’s task of “seeking new paradigms and new thinking.” I was interested as a few weeks earlier I had published, on the Internet, my Theory of Ideal SuperSmart Learning1 I had described the Theory of Ideal SuperSmart Learning as similar to a “theory of everything for product, personal, business, and institutional development.” The goal of the theory is “to know and understand everything from nothing and in no time.” This goal is based on utopic ideality The Theory of Ideal SuperSmart Learning uses concepts from both utopic and practical ideality The theory encompasses Versatile Thinking™, part of which is published in the second edition of the multi-author book, Research Methods for Postgraduates; this book is edited by Dr Tony Greenfield The Theory of Ideal SuperSmart Learning is applicable to many domains The theory presents a multi-methodology framework for pattern thinking and especially draws on ideas from Christopher Alexander’s pattern language, software design patterns, the Theory of Inventive Problem Solving (otherwise known as “TRIZ”2), Creative Problem Solving (CPS), mind mapping, and concept mapping The theory therefore covers creativity, problem solving, and ideas management The Theory of Ideal SuperSmart Learning in combination with TRIZ could be used as a resource for developing the following: new paradigms for computing systems; new thinking about objects; new framings for apparently unsolvable problems; new approaches to organizing ideas for strategic problem solving and innovation This paper presents the conceptual framework and tools of the theory as they relate to computing systems Major concepts such as IBM’s “autonomic computing systems” and Bill Gates’s “digital nervous system” are shown to be retrospectively governed by key concepts in TRIZ and the Theory of Ideal SuperSmart Learning Both theories are briefly applied in the area of forecasting states in the evolution of technological systems Finally, some of the major problems, which are facing the computing industry, are framed and then strategic options proposed using tools of TRIZ and the Theory of Ideal SuperSmart Learning The IVY-Paradigm for Computing Systems 2.1 Elements of the IVY-Paradigm The IVY-paradigm is the conceptual framework on which the Theory of Ideal SuperSmart Learning rests This paradigm could be applied to computing objects and systems The acronym, IVY, stands for “IVYality” (ultimate ideality), Versatility, and “Ympossibility.” The IVY-paradigm is a triangle of paradigms, i.e., a meta-paradigm Its interdependent elements are as follows: Paradigm of IVYality3 (Ultimate Ideality): “Infinity at nothingness” Paradigm of Versatility: “Multi-polarity” or “Infinity in all directions” Paradigm of “Ympossibility”: “Unforeseeable (unpredictable) excellence” The first of the IVY-triangle of paradigms, i.e., the paradigm of IVYality focuses on ultimate ideality, which is a combination of technical ideality and emotional ideality As a concept, ultimate ideality, in particular technical ideality, has a long history and is used in many domains Technical ideality is a central feature of TRIZ and directly related to the concept of Ideal Final Result (IFR) Technical ideality also plays a central role in TRIZs approach to forecasting the evolution of technical systems, discovering inventive principles, and resolving contradictions4 Ultimate deality is an extension of technical ideality and could be linked with the following concepts: evolution by natural selection (“survival of the fittest”) in biology; perfect information in market economics; ideal objects such as ideal gases in chemistry; ideal or utopic society in literature; ideal number of defects in quality management of products; ideal time (period) for product delivery; ideal technological and information systems in product development The focus in this paper is on ultimate ideal computing objects But, what is meant by an “ultimate ideal object”? In the Theory of Ideal SuperSmart Learning, an ultimate ideal object is a multi-level concept that is defined at three levels: Macro-level: A system that either infinitely demonstrates its potential functions and properties or infinitely attains its objectives under (internal) conditions of utopic ideality, e.g., using no external (additional) resources or CuuDuongThanCong.com https://fb.com/tailieudientucntt “freely” available resource, and without causing any disadvantage or negative (harmful/undesirable) side effect Meso-level: A closed (self-contained), self-organising, “self-informative”, and self-regulating system that has infinite efficiency and versatility but may not materially exist The system could be a field, wave, or void Micro-level: An autonomous system that carries out its functions or achieves its objectives under conditions of practical ideality or in the real (physical) world The above definitions of an ultimate ideal object are strongly related to TRIZs concepts of ideality However, TRIZ focuses on an ideal object at the macro-level The multi-level definition of an ultimate ideal object is especially suitable for developing paradigms or visions for the innovation and design of computing objects Once the function of an object is ascertained or specified, the object could be reframed as an ultimate ideal object Another advantage in using the concept of ultimate ideal objects such as in strategic system innovation and design is that it encourages “out-of-the-box” thinking, the development of breakthrough insights, and innovative design that satisfy end-users or customers Within the framework of an ultimate ideal object, a problem-solver’s mindset is to go for ultimate ideality (“win-win”/”no compromise”) solutions rather than trade-off or optimisation (“lose-lose”/”win-lose”) solutions Also, the macro- and meso-definitions of an ultimate ideal object indicate the evolutionary tendencies or states of objects that have enduring competitive advantages The above definitions indicate that ultimate ideal objects including ultimate ideal computing (hardware/software/network) objects as well as ultimate ideal “human” objects should, among others, satisfy the following set of interrelated criteria: i infinite functions or functionalities: ultimate ideal (computing) objects should perform their core, peripheral, and remote functions anywhere, at any time, and eternally; the functions could be technical and/or emotional ii conditions of ideality: ultimate ideal (computing) objects should satisfy the following conditions of ideality5: ideal (“functional”) nothingness; ideal infinity; ideal efficiency & “automaticity”6; ideal conflict resolution & unity; ideal simplicity, variety, & beauty; ideal identification, detection, & branding iii no external (additional) resources: ultimate ideal (computing) objects should, when responding to perturbations or resolving problems, not use external or additional resources; such objects should exhaustively exploit not only “freely” available or redundant existing resources7 but also existing internal constraints iv no disadvantage or negative (harmful/undesirable) side effect: ultimate ideal (computing) objects should neither have any disadvantages nor cause negative (harmful/undesirable) side effects v closed (self-contained) system: ultimate ideal (computing) objects should be autonomous, self-problem solving, self-analysing, self-maintaining, self-healing/repairing, and self-sustaining vi self-organisation; “self-informativeness”; self-regulation: ultimate ideal (computing) objects should be selforganising, self-informative, anticipatory, self-monitoring, and self-regulating vii infinite versatility (multi-polarity): ultimate ideal (computing) objects should be infinitely versatile, adaptive or multi-polar viii instantaneous as well as versatile learning and knowledge: ultimate ideal (computing) objects should know and understand everything from nothing and in no time ix ideal problem solvers: ultimate ideal (computing) objects should identify, frame, analyse, manage, and solve all type of problems without using external resources x no material size: ultimate ideal (computing) objects should - as in an electromagnetic field and wave or a void not occupy physical space8 The 10 criteria above could be said to constitute the general operational elements of the IVY-paradigm, especially for computing systems The set of criteria may also be regarded as the features of an “ultimate ideal autonomous object.” The criteria also provide stable “yardsticks” for not only ascertaining the level and degree of ultimate ideality (IVYality) of existing computing systems but also anticipating and designing future computing systems The criteria of the IVY-paradigm could be variously combined to form other paradigms9 For instance and in retrospect, the paradigm of autonomic computing could be said to relate to the following IVY-criteria: (ii) conditions of ideality ideal efficiency & “automaticity”; (vi) self-regulation; (viii) (instantaneous as well as versatile) learning and knowledge; (ix) ideal problem solvers It is important to note that autonomous computing contains some criteria not directly stated in the set of IVY-criteria 2.2 Autonomic Computing Systems, the Digital Nervous System, and IVY-Paradigm for Computing Systems As indicated above, the list of criteria in the IVY-paradigm for computing systems could be related to IBM’s (Paul Horn’s) vision of autonomic computing systems The main criteria to be satisfied by autonomic computing systems and their links with criteria of the IVY-paradigm could be summarised as follows: self-identification; self-knowing: IVY-criterion (viii) CuuDuongThanCong.com https://fb.com/tailieudientucntt self-optimization: [IVY-criterion (ii)10] self-(re)configuration: IVY-criterion (vii) self-recovery (from perturbations): IVY-criterion (vi) self-protection (security) self-learning (including from errors): IVY-criterion (viii) self-regulating (to open standards): IVY-criterion (vi) self-resource-allocation: IVY-criterion (ix) The criterion of self-protection (security) is unique to autonomic computing systems The similarity between the criteria of autonomic computing and the IVY-paradigm is mainly due to the assumption - inherent in Paul Horn’s paper but explicit in TRIZ and the Theory of Ideal SuperSmart Learning - that technological and information systems evolve towards ultimate ideality (IVYality) Although the set of 10 criteria in the IVY-paradigm was developed after reading Paul Horn’s paper, Autonomic Computing: IBMs Perspective on the State of Information Technology, nearly all criteria in the IVY-paradigm could be traced to the multi-level definition of an ultimate ideal object that is contained in the Theory of Ideal SuperSmart Learning Despite the strong similarities between the paradigm of autonomic computing and the IVY-paradigm, there are some important differences The IVY-paradigm is explicitly rooted in TRIZ as well as ultimate ideality and is conceived not only for technological systems but also for human-activity and learning environments Thus, the IVY-paradigm could be applied to computing as well as domains outside of computing According to concepts in the Theory of Ideal SuperSmart Learning, the paradigm of autonomic computing deals with practical ideality; the criteria are meant to be achieved, however long the time frame In contrast, criteria in the IVY-paradigm deal with utopic ideality The list of 10 criteria is therefore normative Some criteria are not meant to be achieved in the foreseeable future Although some criteria may not be achieved in generations to come, the 10 criteria provide a means for benchmarking existing products as well as evaluating future designs Finally, the paradigm of autonomic computing focuses on what is referred to as “ideal automaticity” in the Theory of Ideal SuperSmart Learning Ideal automaticity is one of conditions of ideality in the Theory of Ideal SuperSmart Learning The paradigm of autonomic computing does not directly focus on conditions such as ideal (“functional”) nothingness; ideal infinity; ideal conflict resolution & unity As in TRIZ, the latest condition emphasises the concept of “win-win” or “no compromise” solutions, while the paradigm of autonomic computing explicitly deals with “self-optimization.” It may be noted that a system that continually self-optimizes will steadily progress towards technical ideality The paradigm of autonomic computing is based on an analogy of the human nervous system So also, is Bill Gates’s concept of a digital nervous system While the concept of autonomic computing focuses on computing objects (networks, hardware, and software), the concept of a digital nervous system deals with designing a business or enterprise information system with a view to “instantaneous as well as versatile learning and knowledge”; this is IVY-criterion (viii) The target of the vision of autonomic computing ranges from level of the computing industry to product design, while the target of a digital nervous system is an enterprise that may be at local or global level A digital nervous system may be said to focus on practically ideal information gathering, processing, and distribution (flow) The paradigm of a digital nervous system deals with an operational rather than an abstract framework The digital network paradigm may therefore be expanded using the listed criteria of the IVY-paradigm Applying Tools of TRIZ and the Theory of Ideal SuperSmart Learning to Computing Systems Combined with TRIZ, the Theory of Ideal SuperSmart Learning contains a menu of tools that assists in generating ideas, obtaining breakthrough insights and innovative products, (personally) managing ideas, solving problems, and planning scenarios In this paper, only a selection of tools is presented On the one hand, there are tools that could be used for anticipating patterns in the evolution of computing systems (hardware/ software/networks) On the other hand, tools exist for framing and solving emerging problems in computing The tools could also be used to obtain multiple perspectives on a given problem 3.1 Anticipating Patterns in the Evolution of Computing Systems 3.11 The “Laws” of IVYality (Ultimate Ideality) & IVY- Matrix of Bipolar Variables The “laws” of IVYality are in fact, hypotheses11 They are interdependent and applicable to designing objects in computing as well as other domains The hypotheses are as follows: i “Law” of Infinite IVYality Technological and information objects (systems), which acquire and maintain high competitive advantages, develop towards infinite IVYality (Note that: Level of IVYality = Advantages - Disadvantages CuuDuongThanCong.com https://fb.com/tailieudientucntt & Degree of IVYality12 = Advantages/Disadvantages) ii “Law” of Infinite Versatility Technological and information objects (systems), which acquire and maintain high competitive advantages, develop towards infinite versatility (multi-polarity or adaptiveness) iii “Law” of “Ympossibility” Technological and information objects (systems), which acquire and maintain high competitive advantages, develop towards “ympossibility”, i.e., apparently impossible (unpredictable) states with excellent “emergent” properties The laws of IVality (ultimate ideality) seem like truisms And indeed, they may well be The laws would be true whether one takes the viewpoint of a consumer or producer The laws of IVyality could be regarded as the “invisible hand” that guides the choice of consumers and is increasingly driving the business of suppliers According to the law of infinite IVYality, computing systems, which are likely to have great competitive advantage, will be those that have the highest level or degree of IVYality Products that violate the law of IVYality are likely to suffer “death.” Examples of some variables or resources, which could be maximized, are presented in the IVY- Matrix of Bipolar Variables in table 113 In the compilation of information in table 1, TRIZs patterns of evolution as well as literature on the evolution of technical systems were used14 Table 1: IVY-Matrix of Bipolar Variables (Resources) Name of system (“object”): Main function(s)/objective(s): Supersystem(s): No Bipolar Variable Anti[Dimension]: Nothing: Neutral/ -∞ [Dimension]: + ∞ Low Medium High/ Extreme Quantity (Number/ Amount): bidirectional Negative; indebted None; no One; mono-; bi-; few Several; multi- Multitude; multi-; poly-; ubiquitous; myriad Size (3DSpace/ Scale): bidirectional Anti-matter Nothing; invisible; void Micro-; nano-; atomic; molecular Meso-; average Macro-; mega-; giga-; galactical Efficiency Antiefficiency No value added; 100% waste Low efficiency; high waste Moderate or average efficiency High/infinite efficiency; closed (selfcontained); complete recyclability; 0% waste Anti“Automaticity” automaticity Human-operated/ contact Mechanization Moderately mecha-nized; semiautomatic Fully automatic; machine-operated; selfoperating; self-working; no contact Conflict/ Contradiction Anti-conflict/ Friction-less; no conflict; contradiction Peace Minor conflict, contradiction, or dilemma Moderate conflict, Major conflict; all-out or perpetual war contradic-tion, or dilemma Unity/ Integration/ Structure Anti-unity/ integration/ structure Stone-heap-unity; separated; discrete Chain-unity; linear; open; weak integration Tree-unity; non-linear; nested; stacked; hierarchical Web- or network-unity; closed; networked; total integration Simplicity Absolutely complex Complex; convoluted Barely simple Moderately simple Absolutely simple Variety: bidirectional Completely homoge-neous or symmetri-cal; rigid; complete Low degree of Moderate freedom; High degree of Anti-variety CuuDuongThanCong.com Completely heterogeneous or asymmetrical; absolute degree of freedom or https://fb.com/tailieudientucntt standardi-sation; no degree of freedom; Oblique standardisation freedom or variation variation; No standardisa-tion; extremely modularised or flexible Plain; unadorned Mono-chrome Modera-tely beautiful Multi-coloured; awesome Beauty/ Ergonomics Ugly; shocking 10 Identification/ Detection/ Branding: bidirectional Anti-identification/ Incognito; invisible; transparent Plain detection/ branding 11 Versatility Antiversatility Nowhere; punctiform 1-D; 2-D; uni-, bilateral 3-D; multilateral Multi-lateral; ubiquitous 12 Time (Speed): bidirectional Reversal of time; past Instanta-neous; stationary; present Momentary; Slow; birth Fast; growth Speed of light; future; maturity 13 Function Antifunctional Dys-functional Mono-, bifunctional Multifunctional Multi-, poly-functional 14 Material/ Substance/ Physical State Anti-matter Liquid; soft; Gas; vacuum; field; void; wave foam Elastic; plastic; porous; gel powder Solid; hard 15 Orderlinesss: bidirectional Perfect chaos; high entropy or asymmetry Chaos; entropy Low order Interme-diate order Perfect order; no entropy; perfect symmetry 16 Flexibility Antiflexibility Monolithic; rigid; jointless; No joint Soft; Softer; MultiSingle/doublejointed jointed Extremely flexible or mobile; fluid 17 Vibration: bidirectional Antiresonance No frequency or periodicity Pulsating; small amplitude or oscillation Average periodicity High resonance; large frequencies 18 Weight Counter- or anti-gravity Weight-less (Ultra) light Heavy Quasar-like 19 Energy (Power):input Potential None Least; Average Maximum 20 Cost Loss; debt Free Inexpensive; cheap Expensive; cosly Astronomical cost 21 Safety Dangerous; risky None Low Moderate High 22 Length (Width/thickness/ Height) Anti-linear dimension None Low Average Maximum 23 Quality/ Advantages Anti-quality None Low Moderate Total 24 Emotion: bidirectional Anti-emotion None Low Moderate Total 25 Colour Anti-colour None; invisible Plain; mono-; Multibi- 26 Reality: bidirectional Anti-reality None Fictitious Virtual; artificial Physical; visceral 27 Coordinates (Position) Anticoordinates None 1-D; 2-D 3-D Multi-/poly-dimensional 28 Environment: bidirectional Fictitious Virtual Inert Quasiphysical Physical 29 Temperature: bidirectional Absolute zero Zero; freez-ing point Cold; room temperature Hot Extremely hot 30 Form/Shape: bidirectional Antiform/shape Linear; geons; simple; 1D;2D Hierarch-ical; Web; network; 2D; 3D 2D; 3D Amorphous Conspi-cuous; selectively Globally recognised; glaring recognised Whole colour spectrum Cells, the contents of which are embolded in table reflect ultimate ideal states in systems For instance, the row for efficiency (variable #3) indicates that objects with a tendency towards ultimate ideality would overwhelmingly display CuuDuongThanCong.com https://fb.com/tailieudientucntt very high efficiency Other variables in table are “bi-directional”; this means that there is no unique direction for ultimate ideality By vertically profiling, i.e., vertically plotting the characteristics of a given computing system, one could see possible states that the system, subsystem, or supersystem could adopt in the future Scenarios for the evolution of systems could therefore be facilitated using the laws of ultimate ideality and the IVY-matrix of bipolar variables As an example of the use of table 1, a list of highly probable states in the evolution of the personal computer is presented below “Efficiency” state: extremely highly efficient and recycleable “Automaticity” state: extremely high degree of automation; minimal manual operations “Unity/Integration/Structure” state: extremely networked and largely integrated system “Simplicity” state: absolutely simple to use “Beauty/Ergonomics” state: multi-colored; awesome beauty; easy to handle “Versatility” state: ubiquitous; adaptive; responsive to needs of user “Function” state: multi-functional; integrated with other systems in core, peripheral, and remote domains “Material/Substance/Physical” state: predominance of “invisible materials” such as fields and waves; also, the use of liquid-like materials “Flexibility” state: extremely flexible or mobile; foldable; nestable; wearable “Weight” state: almost weightless “Energy (Power) Required” state: minimal energy; self-powered “Cost” state: minimal (readily affordable) cost; almost free “Safety” state: extremely high “Length” state: miniature length; tending to invisibility “Quality/Advantages” state: total quality; enormous advantages to consumer as well as high constumer satisfaction “Colour” state: offered in colors covering the range of the color spectrum “Coordinates (Position)” states: multi-dimensional; could be placed in any position and place at any time It is possible that the personal computing industry may have recognised some of the above pathways, but not all of them Not-yet-recognised or unused pathways indicate directions as well as opportunities for further development of the personal computer The laws of versatility and “ympossibility” are not separately discussed since they are subsumed in table and consequently in the above example 3.12 The IVY-Pyramid of Innovation Although the primary use of the IVY-pyramid of innovation is to rapidly evaluate and classify alternative innovations, it could be used to anticipate patterns in the evolution of computing systems The IVY-pyramid of innovation is shown below in table It is important to note that the IVY-pyramid of innovation is based on TRIZs five levels of invention (solutions15) In contrast to the focus of TRIZ on inventions or highly inventive solutions, especially in the manufacturing sector, the IVY-pyramid of innovation presents a general framework for categorising and evaluating innovations Like in TRIZs level of invention, the IVY-pyramid of innovation shows five levels of innovation In terms of the number of innovations that could be found at each level, the pyramid could be visualised as an inverted pyramid The large majority of innovations occur at level and gradually reduce until level 5, which contains the least number of innovations The evolution of an enduring system is like a series of spirals or S-curves moving from levels to Computing networks are currently considered to be moving towards the peak of level in the IVY-pyramid of innovation Thus, computing networks will - in the not too distant future- possess “matured” mega-problems When mega-problems emerge in computing networks, the circle of resources required for solving such problems will include professionals from peripheral domains as well as technology being used in more advanced systems Tools, technology, and resources in apparently disparate domains would have to be combined in order to resolve megaproblems Also, solution of such mega-problems would need international cooperation The IVY-pyramid of innovation indicates progressive scalability of problems Thus, after mega-problems have been solved, computing networks would perform first with increasing IVYality and then with decreasing IVYality, probably due to increased complexity as the functionality of networks increase The next generation of problems will therefore be “giga-problems”, i.e., problems of a global order of magnitude Solving such giga-problems would require global cooperation as well as a paradigm shift (e.g., as in ultimate ideal autonomous objects) combined with the discovery or application of new (“original”) technology Hitherto remote disciplines could be valuable resources for knowledge The result of solving giga-problems will be a new system (supersystem) with completely unforeseen (“emergent”) properties CuuDuongThanCong.com https://fb.com/tailieudientucntt This supersystem will form a new genus at level and the spiral of increasing IVYality, problems (decreasing IVYality), and innovation would continue down the pyramid Table 2: IVY-Pyramid of Innovation Name of system (“object”): Main function(s): Supersystem (Family of products): Level of innovation Reference Features of innovation Circle of resources Level 1: Local “unusuality” or improbability Closed-system solution(s)/ Miniproblems Non-structural change (basic “CreaLogical” substitution); “cosmetic” progression; small quantitative changes and improvements; use of common domain ideas, tools, and technology; low-order or linearly predictable (1-D) emergent properties Core domain; System Level 2: Regional Closed-system “unusuality” or solution(s)/ Midiimprobability problems Minor structural change (intermediate “creaLogical” substitution); significant quantitative Core domain; and qualitative changes; intermediate-order or surprising (2-D) emergent properties; System Intermediate (rarer) tools and technology “Extended” Level 3: National closed-system “unusuality” or solution(s)/ Maxiimprobability problems Major, radical, non-linear structural change (advanced “creaLogical” substitution); Advanced, little known, or rarest domain-technology; largely unforeseen (3-D) emergent properties “Extended” core domain; Extended system Level 4: International “unusuality” or improbability Open-system Emergent (bisociated/ hybrid/transition) system; cross-fertilisation or “bisociation” of solution(s)/ Megatools, technology, and resources in apparently disparate domains problems Peripheral domain(s); Super-system Level 5: Global “unusuality” or improbability Open-system solution(s)/ Gigaproblems Remote domain(s); New system Completely unforeseen (3-D) emergent properties; new invention or genus; paradigm shift; discovery or application of new (“original”) principle or technology 3.2 Framing and Solving Problems of Strategic System Design in Computing 3.21 Problem-, Opportunity, and Solution-Archetypes Problem-Archetypes In the Theory of Ideal SuperSmart Learning, the approach to solving problems of strategic system design is based on resource archetypes, in particular problem-, opportunity-, and solution-archetypes Problem-archetypes are universal patterns of problems in systems; opportunity-and solution-archetypes could be similarly defined An opportunity is regarded as being on the reverse side of a problem Problems and opportunities are therefore complementary With a view to facilitating creative problem finding and problem classification, the Theory of Ideal SuperSmart Learning distinguishes problem- archetypes as follows: Problem-archetype 1: Undesirable “largeness/presence” - What are undesirably large or present?16 Problem-archetype 2: Undesirable “smallness/absence” - What are undesirably small or absent? Problem-archetype 3: Undesirable inefficiency/sub-optimality/waste - What are undesirably inefficient, sub-optimal, or wasted? Problem-archetype 4: Undesirable conflicts/contradictions/ bipolarities/dilemmas/paradoxes/disunity/discontinuity - What are undesirably conflicting, contradictory, bipolar, paradoxical, disunited, or discontinuous? Problem-archetype 5: Undesirable complexity/sameness/ standardisation/symmetry - What are undesirably complex, uniform, standardised, or symmetrical? CuuDuongThanCong.com https://fb.com/tailieudientucntt Problem-archetype 6: Undesirable identification/detection/branding - What are undesirably identified, detected, or branded? Problem-archetype 7: Undesirable dimensions/parameters/ attributes - What are undesirable dimensions, properties, parameters, or attributes? Problem-archetype 8: Undesirable situations/side effects/consequences/ systems/elements/super-systems - What are undesirable situations, side effects/consequences/ systems, elements, or super-systems? The above problem-archetypes constitute a system for classifying and organizing (design) problems in a domain Problem archetypes could provide different perspectives as well as obtain an array of inventive problems in a system The classification of problems as archetypes facilitates analogical problem solving This implies that families of solutions could be accessed and used as a resource for solving particular problem-archetypes, especially in strategic system design of computing systems Problem-archetypes also indicate a need for having a catalogue of tools and multiple mindsets for tackling multifarious problems Although problem-archetype is recognised in computing systems, there seems to be inadequate formal tools for dealing with this type of problems; examples include apparently impossible conflicts, contradictions, bipolarities, dilemmas, paradoxes, and discontinuities The prevailing mind set for example when dealing with technical conflicts is to go for trade-off or optimization Why not go all out for a win-win solution, in the first instance? According to TRIZ, inventive or “patentable” solutions emerge when hitherto technical contradictions are resolved.17 TRIZ has documented 40 “Inventive Principles” that are inherent in highly innovative product solutions These 40 Inventive Principles have recently been adapted for software systems18 According to TRIZ, “inventive problems”, i.e., apparently impossible problems that involve technical and physical contradictions, constitute the most difficult category of problems in design Within the framework of problemarchetypes, inventive problems belong to problem-archetype Inventive problems in computing systems cover the following conflicts: Type I - Technical Conflicts (Contradictions) Speed vs Reliability Type II -Technical Conflicts (Contradictions) Automation vs Complexity Computing “Functionality” Power vs Storage Capacity Computing “Functionality” Power vs Sophistication of Computer Architecture (Lines of Code) Computing Power vs Power (Energy) Consumption A few questions come to mind when looking at the above conflicts For instance, what formal technical and thinking tools exist to deal with the technical conflicts?19 How are these inventive problems to be solved? Using ideas from TRIZ and the Theory of Ideal SuperSmart Learning, some of the above technical conflicts are illustrated in Fig These technical conflicts could be described as sub-archetypal problem The approach to dealing with problem-archetypes is outlined in the following sections Fig 1: Examples of Technical Conflicts (Contradictions) in Computing Systems A: Type I - Technical Conflict (Decreasing Pattern) CuuDuongThanCong.com https://fb.com/tailieudientucntt B: Type II - Technical Conflict (Increasing Pattern) The Theory of Ideal SuperSmart Learning proposes a Creative Web - ARIZ (Multi-methodology) Framework for solving problems, especially in strategic system innovation and design This framework is illustrated in Table and mainly refers to tools in TRIZ, the Theory of Constraints20, and the Theory of Ideal Supersmart Learning Details on the use of the Creative Web - ARIZ framework could be obtained from the booklet on the Theory of Ideal Supersmart Learning21 Briefly, the table provides a framework that links steps in ARIZ with more detailed tools in TRIZ, the Theory of Constraints, and the Theory of Ideal Supersmart Learning Within a particular “space” of the creative web, tools of TRIZ could be mixed and matched with “functionally equivalent” tools in other methodologies The section, “SolutionArchetypes,” reflects an application of the Creative Web-ARIZ framework but with an emphasis on tools from TRIZ and the Theory of Ideal Supersmart Learning Opportunity-Archetypes An important step in solving problems in strategic system design is to identify internal and external resources The concept of opportunity-archetypes facilitates the identification of resources that could be used in providing “closedsystem solutions” to design problems Opportunity-archetypes are perceived as problem anti-archetypes Consequently, the description and checklist of questions for opportunity archetypes are based on problem-archetypes A list of opportunity-archetypes is presented below Opportunity-archetype 1: Desirable “largeness/presence” - What are desirably large or present?22 Opportunity-archetype 2: Desirable “smallness/absence” CuuDuongThanCong.com https://fb.com/tailieudientucntt - What are desirably small or absent? Opportunity-archetype 3: Desirable inefficiency/sub-optimality/waste - What are desirably inefficient, sub-optimal, or wasted? Opportunity-archetype 4: Desirable conflicts/contradictions/ bipolarities/dilemmas/paradoxes/disunity/discontinuity - What are desirably conflicting, contradictory, bipolar, paradoxical, discontinuous, disunited, or discontinuous? Opportunity-archetype 5: Desirable complexity/sameness/ standardisation/symmetry - What are desirably complex, uniform, standardised, or symmetrical? Table 3: The creative web - ARIZ (multi-methodology) framework Creative web Main stages of ARIZ (“Extended”) tools of TRIZ PROBLEMDEFINITION Space Selection and description of problem (unitary space, including objective(s)) Determination of Ideal Final Result (IFR) and/or Technical/Physical/Admini-strative Contradictions Problem replacement (e.g., sub, mini-, or core problem) Problem-archetypes 39 Parameters; Contradiction matrix (Object-attributefunction diagram/ Object-matrix for unitary space) (Qualtiative change graphs/Evaporating cloud or Conflict resolution diagram) Ideal Final Result (IFR) (Multi-level objectives/IVY-Final Result/ IVY-object) Multi (9)-screen approach (Multi-temporal IVY-Template Thinksheet) (Conflict or operative zone/ Closed (problem) world/“Constraint” zone) METHODS-Space Analysis of the problem (model) and resources Substance-Field analysis Utilisation of TRIZs (“invention”/patent) knowledgebase: Inventive principles; Database of effects, e.g., scientific effects and principles; 76 Standard solutions, etc (Multi-level resource analysis/Opportunity-archetypes) Substance-Field analysis (Triads/IVY-template Thinksheet) (Object-function analysis/Closed-world diagram/Multi-level root-cause analysis/ Current reality tree) Database of physical effects (library of patents/”best practice” solutions) 76 Standard solutions (Prerequisite tree) Modelling of miniature dwarves (Smart little people/Magic particles method/Agents method/ObjectBots/ Scene-transformation matrix) (Versatile matrix) Size-Time-Cost (STC) operator (Extreme contingency scenarios) SOLUTIONS-Space Proposal as well as evaluation of solutions to technical/physical/admini-strative contradictions Evaluation as well as reflection on ARIZ and process of problem solving Ideality/IFR (Multi-criteria/Level and degree of IVYalityIIVY-object/Closed-system solutions/Future reality tree) Separation heuristics 40 Inventive principles (Qualitative change principle/ SCAMPER-DUTION matrix) Levels of inventions/solutions (IVY-pyramid of innovation) Subversion (failure anticipation) analysis Patterns (laws/trends) of technological evolution Expected Final Results (EFR) for evolution of technical systems IMPLEMENTATION- Application of solutions obtained Space (Generification of solutions/ Transition tree) Opportunity-archetype 6: Desirable identification/detection/branding - What are desirably identified, detected, or branded? Opportunity-archetype 7: Desirable dimensions/properties/parameters/ attributes - What are desirable dimensions, properties, parameters, or attributes? Opportunity-archetype 8: Desirable situations/side effects/ consequences/systems/elements/super-systems - What are desirable situations, side effects/consequences/ systems, elements, or super-systems? The search space for opportunity-archetypes could be further extended by replacing, in each archetype and question, “are” with “could be.” Thus, for opportunity-archetype 1, one could also ask: “What could be desirably large or present?” After identifying problem- and opportunity-archetypes, attention could be turned to resolving identified problems, especially using internal resources Solution-archetypes offer prompts for brainstorming on strategies and mechanisms for resolving more well-defined problems Solution-Archetypes Solution-archetypes are presented in table as the “SCAMPER-DUTION” matrix This matrix includes solutionpatterns from Osborne-Eberle’s SCAMPER23 as well as the 40 Inventive Principles and Separation Heuristics from CuuDuongThanCong.com https://fb.com/tailieudientucntt TRIZ Numbers in bracket in the table refer to TRIZs inventive principles Only patterns at level 1, i.e., keywords (idea prompter/trigger/hint) are shown in table In a software application, patterns at level could be hyperlinked to patterns at level 2, i.e., heuristics (descriptions or exemplars using phrases, sentences, paragraphs, diagrams, and/or multimedia) Software design patterns could be organized in the form of a SCAMPER-DUTION matrix If we are to consider the technical conflict that is illustrated in Fig 1A, i.e., speed vs reliability, we could say that our objectives for design should be as follows: Practical ideality-objective: to maintain the best available level of reliability while increasing the speed of computing systems Utopic ideality-objective: to increase the reliability of computing systems while increasing their speed Table 4: SCAMPER-DUTION matrix of patterns for solution-plots, properties, and devices Solution 1: Ideal Archetype nothingness Acronym patterns 2: Ideal infinity patterns 3: Ideal efficiency & automaticity patterns 4: Ideal conflict 5: Ideal simplicity, resolution & variety, & beauty unity patterns patterns 6: Ideal id., detection, & branding patterns Targeted variables (elements of unitary space) Spheroidality (14) Skipping (21) Selfservice/Selforganisation (25) Substitution (28) Shells (30) Separation: in space/time; Synthesising Synchronise Structuring Satisficing Stabilize Substitute Separate Simulate Store Screen Substances Space/Strata Shape/Structure Suppliers/Staff Solutions Systems/Strength Change Cartoon Calculate Controls/Casing/ Connections/ Constraints/Cost S Segmentation (1) Segmentation (1) Separation/Suction Separation Stretch Stacking/Smoking Serialization Share Squeezing/Subtract Subordinate Submerge/Siphon C Cease/Compress/ Compact/Cancel Counteract A Anti-weight (8) Add/Attract Anti-gravity/Adapt Aggravate/Attach M Minimize Miniaturize/Melt Maximize/Modula- Merging (5) Maxi-mini rise/Multiplication Mixing/Multiplex Mirroring Modify/Morph Manipulate Measure Move/Model Materials/Manpower/Methods P Periodicity (19) Porosity (31) Pluralization Production Put to other use Provocation Protect Picture Parts/Process/ Parameters E Extraction (2)/Equipotentiality (12) Exaggerate/Expand Expansion: Exploit/Extend thermal (37) Elegant/Echo Extreme/Escape Extract Experiment Elements/Equipt Expenses/Energy R Removal (2)/Repel Recovering (34) Reengineering Reduce/Reframe Reverse(13)/Random Replace Resources D Division (1) Discarding (34) Decrease/Decay Division (1) Dimensionality (17) Distribution Dynamism (15) Downsize Decentralize Displacement Differentiation Distance Distorting Differentiate Diversify Dimensions Devices/Deficits Disadvantages U Undermine Ubiquitous Universality (6) Unify Uniform/Uniqueness “Unusality” Unknowns T Trimming/Transfer: Tilt (17)/Transpose/ Transition: Function/Resource Telescopic phases (36) Transformation Transduction Twist/Tessellation Turn off/Tranquility Tools/Time/ Throughput I Inexpensive (27) Inert (39)/Inactivate Increase/Innovate Improve Invention Innovation Intermediary (24) Integrate Invert/Interrupt Introduce Inventory/Inputs Idealise/Interlocking Imitate/Invert IVY-matrix/Infra’ O Obliterate Orientation (17) Oxidant (38) Optimising Outline/Order Observe Objects/Organisn N Nesting (7)/Nullify Nebulous/Net Nesting (7) Negotiating Non-uniformity (3) Notice Nexus Miscellaneous Homogeneity (33)/ Fractal/ Galaxy Free/Heat Feedback (23) Lean Win-win/BATNA Vibration (18)/Field/ Vary/Freeze Hybridization Void/Bipolarity Undesirable inefficiency/ sub-optimality Undesirable conflicts/ contradictions Problem Undesirable Archetype presence/ “largeness” Symmetry Standardisation Simplify/Scale Shape/Structure Surprise/Serenity Specialisation Continuity (20) Combining (5) Cushion before- Change: colour Copying (26)/Clone Converting (22) hand (11)/Cen- (32); parameters Composites (40) tralize/Channel (35) Contrast Undesirable absence/ “smallness” Automate Accelerate (Anti-) action Asymmetry (4)/Adapt Assemble (9/10)/Alignment Adaptive/Abstraction Analyse/Add Pneumatics (29) Partial (16) Prunning/Pareto Preparation Eliminating Excessive (16) Undesirable complexity/ sameness Destroy Deduce Direct Transfer Transform Actions/Artefacts/ Attributes/Advant Functions/Links Forces/Fields Undesirable Causes/ causal identificafactors/ problems tion/detectn The IVY-paradigm and laws of IVYality would suggest that the designer focuses on the utopic ideality-objective Consequently, the SCAMPER-DUTION matrix would be consulted with a preference for “ideal infinity patterns.” From table 4, the following principles from TRIZ24 are recommended for resolving the conflict between speed and reliability: (1): Segmentation/Division - “Segment, divide, fragment, modularise, or “granularize” [object] and/or [functions and attributes of object] into parts”; especially using database of opportunity-archetypes CuuDuongThanCong.com https://fb.com/tailieudientucntt (17): Dimensionality/Orientation/Tilt - “Change orientation or dimensions of existing physical space that is occupied by [object] and [parts of object], e.g., from horizontal to vertical; from 2D to 3D; from inside to outside; from uni-lateral to bi-lateral to multi-lateral; from single layer to multiple layers ( vice versa)”; especially using database of opportunity-archetypes (20): Continuity - “To maximize continuity of operation as well as eliminate idle time, exhaustively use distributed, parallel (synchronised), multi-level, and/or “multi-polar” processing on [object] and/or [functions and attributes of object]”; especially using database of opportunity-archetypes (26): Copying - “Use simpler and inexpensive copies as replacement for unavailable, expensive, fragile [object]”; especially using database of opportunity-archetypes (34): Recovering - “Discard, modify, release, or eliminate (before or during main operation of system) portions of an [object] that have performed auxiliary functions”; especially using database of opportunity-archetypes The above list contains generic solution-patterns, pointers, or strategies that could be further developed in the specific context of the problem, for instance by asking “How? How?” or “In how many and different ways …?” It is important to note that the above strategies are derived from a small subset of the “ideal infinity patterns” of the SCAMPERDUTION matrix More ideas could be generated using ideal infinity patterns as well as other patterns Alternatively, relevant inventive principles could be obtained from TRIZs contradiction matrix in the cell for the engineering parameters: speed (+: increasing) and reliability (-: worsening) An advantage of the graphical approach using technical conflicts is that it is independent of TRIZs “39 engineering” parameters and consequently, could be more easily applied to problems in technical, administrative, and social systems 3.22 The IVY-Template for Strategic Problem Solving The IVY-template could be regarded as a dynamic and multi-level structural description of a system, including categories of its impacts The template could be used for documenting ideas and problems as well as solving problems, particularly those relating to strategic system design The Basic IVY-Template for Strategic Problem Solving is shown in Fig The technique of object mapping25 is recommended for recording information on the IVY-template The template facilitates holistic problem solving as it visually shows and integrates the problem-definition, methods, and solutions-space relating to a given task The template illustrates the fact that there are categories of solution-systems, i.e., open- and closed (self-contained)-system solutions and generic ways of solving any problem Each description on the IVY-template could be regarded as an “object.” Letters on the IVY-template could have the following interpretations: O: “Object” (in the sense that everything is an object) F: Factor(s); Field(s); Force(s); Function(s); Failure(s) P: (Solution-) Pattern(s); Principle(s); Procedure(s); Process(es); Properties; Parameter(s); Prompter(s); Paradigm(s) O1: Problem-archetype; Substance; Constraint; Weakest Link O2: Opportunity-archetype; Tool; Agent; Means O3: Given System; Super-agent; Super-system O4: (Ideal) Final Result O3.1: External elements O3.2: New (analogical/substitute/replacement) system O(-): Undesirable (harmful/negative/) effects; Disadvantages O(+): Desirable (useful/positive) effects; Advantages; Opportunities Fig 2: Basic IVY-Template for Strategic Problem Solving CuuDuongThanCong.com https://fb.com/tailieudientucntt The IVY-template is directly related to the concept of an ideal object, IVYality, and TRIZs ideality as well as resource (problem, opportunity, and solution)-archetypes, SCAMPER-DUTION matrix, and creative web (versatile map) The IVY-template could therefore be regarded as the embodiment of the IVY-paradigm However, the template is restricted to strategic problem solving 3.23 The Creative Web and Versatile Map The creative web is a tool that focuses on ideas management as well as holistic problem solving in any discipline The creative web26 consists of five spaces Generic activities in the spaces of the creative web are listed below: Problem-definition space Creative (“inventive”) Problem Finding Preparation and Immersion Methods-space Reengineering, Exploration, and Generation/Incubation (Unexpected) Synthesis/Illumination Solutions-space Execution (Experimentation) and Testing Evaluation and Verification Implementation-space Presentation, Acceptance, and/or Implementation Creative lifeSpace External or “environmental” interaction The numbers above are nominal rather than ordinal; their main purpose is to identify the activities as modules rather than elements in a chain Activities in the creative web are recursive and involve “trial-and-error” (feedback) The problem-definition, methods, and solutions-spaces constitute the versatile map; see Fig CuuDuongThanCong.com https://fb.com/tailieudientucntt Fig 3: Versatile Map Both the creative web and versatile map are especially useful for solving open-ended or “wicked” problems Using the creative web or versatile map, a designer could strategically plan a design project Another use of the creative web is as a framework for using multi-methodologies as is demonstrated in table Solving complex problems often requires the matching and mixing of methods from disparate disciplines and domains The creative web provides a platform for assembling a “menu” of tools from various disciplines To date, there is no standard template or structure for documenting software design patterns and anti-patterns Due to the level of abstraction of the creative web, it could be used for ordering various design patterns A scheme is presented below: Problem-definition space (Pattern) Name/Problem/Context/Forces Methods-space Rationale Solutions-space Solution Implementation-space Resulting Context (Consequences)/Known Uses/Examples/ Related Patterns Creative lifeSpace Not available The advantages of documenting patterns and anti-patterns are well described in the literature and are therefore not addressed in this paper Suffice it to say that a library of design patterns and anti-patterns could be linked with the SCAMPER-DUTION matrix and IVY-template Conclusions As a response to the task of finding new paradigms and new thinking for computing systems, this paper introduces many concepts including ultimate ideality, ultimate ideal object, IVY-paradigm, IVYality, and tools of the Theory of Ideal SuperSmart Learning The key proposals of this paper are more widespread use of the model of “ultimate ideal autonomous (autonomic) object” for computing systems as well as case study applications of tools of TRIZ and the Theory of Ideal Supersmart Learning in the area of computing IBM’s (Paul Horn’s) paradigm of autonomic computing systems and Bill Gates’s digital nervous system could be derived from the meta-paradigm of ultimate ideal autonomous (autonomic) object The 10 IVY-criteria for an ultimate ideal autonomous object could be regarded as an alphabet or the basic building blocks (DNA) for paradigms dealing with ultimate ideality, the zenith of which may be a holonic27 web of ultimate ideal autonomous objects In line with object-oriented thinking, the 10 IVY-criteria of an ultimate ideal autonomous object could be applied to the following objects: computer hardware, software, and networks Consequently, one could explore the concepts of “ultimate ideal autonomous (autonomic) hardware”; “ultimate ideal autonomous (autonomic) software”; “ultimate ideal autonomous (autonomic) networks.” These ideal objects could facilitate the innovation and design of products that CuuDuongThanCong.com https://fb.com/tailieudientucntt satisfy both vendors and customers No doubt, tools of TRIZ and the Theory of Ideal SuperSmart Learning would be valuable resources for strategically designing a holonic web of ultimate ideal objects Dr Rodney K King r.k.king@supersmartnetwork.com Executive Coach, Consultant, and Trainer in Versatile Product, Process, and Strategy Innovation Keswick Drive, Hamilton ML3 7HN, Britain/(0)1698-421611 August 2002 This article was originally published in March 2002 in the web site: http://www.supersmartnetwork.com/ Acknowledgement The author would like to thank Dr Ellen Domb for her editorial comments and suggestions, which mainly formed the basis of this revised paper References Alexander, C (1979) The Timeless Way of Building New York: Oxford University Press Altshuller, G (1996) And Suddenly the Inventor Appeared Massachusetts: Technical Innovation Center Belski, I (2000) I Wish the Work to be Completed by Itself, Without my Involvement: The Method of the Ideal Final Result http://www.triz-journal.com/archives/2000/04/a/index.htm Bowman, C.F (ed.) (1996) Wisdom of the Gurus: A vision for object technology New York: SIGS Fey, V.R.; Rivin, E.I (1999) Guided Technology Evolution (TRIZ Technological Forecasting) http://www.triz-journal.com/archives/1999/01/c/index.htm Gates, B (2000) Business @ the Speed of Thought London: Penguin Books Goldratt, E.M (1994) It’s Not Luck Hampshire: Gower Goldratt, E.M (1999) The Goal Hampshire: Gower Greenfield, T (ed.) (2002) Research Methods for Postgraduates London: Arnold Horn, P (2001) Autonomic Computing: IBM’s persective on the state of information technology http://www.research.ibm.com/autonomic/manifesto/autonomic_computing.pdf Horn, P (2001) How Autonomic Computing Will Shape IT http://news.com.com/2010-1079-281578.html Kaku, M (1998) Visions: How science will revolutionise the 21st century New York: Oxford University Press King, R (2002) The Theory of Ideal SuperSmart Learning http://www.supersmartnetwork.com/ or www.triz-journal.com/archives/2002/04/d/index.htm King, R When to Use Creativity in: Greenfield, T (ed.) (2002) Research Methods for Postgraduates London: Arnold Koestler, A (1976) The Ghost in the Machine London: Hutchinson & Co Ltd Mann, D (2002) Hands-on Systematic Innovation Belgium: CREAX Press Michalko, M (1998) Thinkertoys California: Ten Speed Press Rantanen, K (1997) Levels of Solutions http://www.triz-journal.com/archives/1997/12/d/index.htm Rantanen, K; Domb, E (2002) Simplifed TRIZ: New Problem-Solving Applications for Engineers and Manufacturing Professionals Florida: St Lucie Press Rea, K.C (2001) TRIZ and Software - Part I http://www.triz-journal.com/archives/2001/09/e/index.htm Rea, K.C (2001) TRIZ and Software - Part II http://www.triz-journal.com/archives/2001/11/e/index.htm Retseptor, G (2002) 40 Inventive Principles in Microelectronics http://www.triz-journal.com/archives/2002/08/b/index.htm Rosenhead, J.; Mingers, J (eds.) (2001) Rational Analysis for a Problematic World Revisited: Problem structuring methods for complexity, uncertainty, and conflict West Sussex: John Wiley & Sons, Ltd Salamotov, Y (1999) TRIZ: The Right Solution at the Right Time Hattem: Insytec B.V Savransky, S.D (2000) Engineering Creativity: Introduction to TRIZ methodology of inventive problem solving Florida: CRC Press Footnotes CuuDuongThanCong.com https://fb.com/tailieudientucntt The Theory of Ideal SuperSmart Learning could be downloaded from http://www.supersmartnetwork.com/ or www.triz2 10 11 12 13 14 15 16 17 18 journal.com/archives/2002/04/d/index.htm (back to article) Pioneered by the Russian scientist, Genrich Altshuller, TRIZ was developed by examining patent databases and organizing methods by which inventors resolved “apparently impossible” technical contradictions There are claims that over 1.5million patents have now been studied and analysed by TRIZ experts The methods of TRIZ, however, have been largely applied to design problems in the manufacturing sector TRIZ is increasingly being used in other domains as well as by major corporations and manufacturers all over the world Although there are attempts to apply the methodology of TRIZ to the field of computing, applications are at an embryonic stage Examples of applying TRIZ to computing could be found in the following articles: Rea (2001) and Retseptor (2002) (back to article) “IVYality” is a concept that is introduced in the Theory of Ideal SuperSmart Learning to replace the relatively narrower concept of technical ideality as used in classic Theory of Inventive Problem Solving (TRIZ) In TRIZ, ideality is defined as the ratio of benefits to the sum of cost and harmful effects IVYality focuses on advantages and disadvantages and has two operational criteria: level and degree of IVYality The level of IVYality refers to the difference between advantages and disadvantages while the degree of IVYality refers to the ratio of advantages to disadvantages Theoretically, advantages and disadvantages should be expressed in the same unit of measurement When the advantages of a system are infinite and its disadvantages are zero, both the level and degree of IVYality are infinite An important thesis of the IVYparadigm, which is based on TRIZs ideality, states that technological and information systems generally move towards increasing IVYality In this paper, IVYality is used synonymously with ideality (back to article) For more details on the application of (technical) ideality in inventive problem solving and technological forecasting, see the following literature: Mann (2002); Fey & Rivin (1999) (back to article) Conditions of ideality are discussed in the (Internet) publication of the Theory of Ideal SuperSmart Learning (back to article) The word “automaticity” is preferred to automation, since the latter term connotes artefacts Automaticity refers to autonomous systems in nature and automated systems in the world of artefacts (back to article) In practice, the criterion of no (additional) resource translates into obtaining the highest possible return or benefit on using an external resource (back to article) This criterion implies that practically ideal (computing) objects should be microscopic or molecular in size (back to article) These criteria could also be linked to TRIZs concept of “self”; see Mann (2002); Belski (2000) (back to article) The square brackets indicate an indirect link (back to article) These hypotheses are presented with a view to establishing them as laws The hypotheses are related to TRIZs concept of ideality The author would like to collaborate with other researchers on testing the three hypotheses External research on the hypotheses would also be welcomed (back to article) The degree of IVYality is similar to TRIZs operational definition of ideality, i.e., ideality = benefits/(cost + harmful effects) In the “law” of infinite IVYality, benefits are subsumed under advantages while cost + harmful effects fall under disadvantages (back to article) The booklet, “The Theory of Ideal Supersmart Learning” (see http://www.supersmartnetwork.com/), provides details on using table What is described as “vertical profiling” in table is similar to plotting a system’s evolutionary potential using multiple axes as in a radar chart; see Mann (2002) In vertical profiling, each variable for the given system is examined horizontally and rated in the cell that most describes its state For instance, if a single personal computer is under review, then for item no 1, its quantity would be rated as “one”; this falls under the general heading of “low.” Table could also be used as a screen or “pane” in TRIZs multi (9)-window operator; see Mann (2002) In other words, vertical profiling could be carried out for a supersystem/system/subsystem in the past/present/future (back to article) See Rantanen & Domb (2002) (back to article) See, for example, Salamotov, Y (1999) TRIZ: The Right Solution at the Right Time Hattem: Insytec B.V.; RRantanen, K (1997) Levels of Solutions http://www.triz-journal.com/archives/1997/12/d/index.htm (back to article) An alternative format for exploration: “Find many and different ways to get rid of or exacerbate [problem type].” (back to article) For a discussion on the characteristics of an inventive solution, see for example the book, Simplified TRIZ by K Rantanen & E Domb (back to article) See, in the TRIZ-Journal, K Reas’s articles, TRIZ and Software as well as G Retseptor’s article 40 Inventive Principles in Micro-electronics (back to article) CuuDuongThanCong.com https://fb.com/tailieudientucntt 19 For a list of thinking tools, see the versatile matrix in the Theory of Ideal Supersmart Learning; visit http://www.supersmartnetwork.com (back to article) 20 The originator of the Theory of Constraints is Dr Eli Goldratt; see Goldratt, E.M (1999) The Goal Hampshire: Gower; Goldratt, E.M 21 22 23 24 25 26 27 (1994) Its Not Luck Hampshire: Gower (back to article) Visit http://www.supersmartnetwork.com/ (back to article) An alternative format for exploration: “Find many and different ways to get rid of or exacerbate [problem type].” (back to article) For a description of the creativity technique of SCAMPER, see for example, Michalko, M (1998) Thinkertoys California: Ten Speed Press (back to article) Classic TRIZ uses a different approach, i.e., the contradiction matrix, to determine which inventive principles should be used for resolving technical contradictions For “speed vs reliability” contradiction, the contradiction matrix suggests the application of the following principles: (11): “Beforehand cushioning”; (35): “Parameter and property changes”; (27): “Inexpensive short-lived objects”; (28): “Mechanics substitution” See Savransky, S.D (2000) Engineering of Creativity: Introduction to TRIZ methodology of inventive problem solving Florida: CRC Press (back to article) Object mapping is described and illustrated in King (2002) Object mapping is an integration of visual thinking techniques such as mind mapping and concept mapping (back to article) The creative web is described in more detail in King (2002) (back to article) The term “holon” was coined by Arthur Koestler in his book, The Ghost in the Machine According to Koestler, a holon refers to a node in a hierarchy which behaves “partly as wholes or wholly as parts.” In Pattern and Object Thinking (King, 2002), a holon could be described as “an object of an object of an object is…” (back to article) (back to top) © Copyright 1997-2003 The TRIZ Institute http://www.triz-journal.com/ All Rights Reserved CuuDuongThanCong.com Site Design & Hosting by: Hunnicutt Internet Services http://www.hunnicutt.net https://fb.com/tailieudientucntt ... therefore be expanded using the listed criteria of the IVY-paradigm Applying Tools of TRIZ and the Theory of Ideal SuperSmart Learning to Computing Systems Combined with TRIZ, the Theory of Ideal. .. as ? ?ideal automaticity” in the Theory of Ideal SuperSmart Learning Ideal automaticity is one of conditions of ideality in the Theory of Ideal SuperSmart Learning The paradigm of autonomic computing. .. model of ? ?ultimate ideal autonomous (autonomic) object” for computing systems as well as case study applications of tools of TRIZ and the Theory of Ideal Supersmart Learning in the area of computing