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
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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
1 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
2 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
Trang 2“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 6 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 organisation; “informativeness”; regulation: ultimate ideal (computing) objects should be
self-organising, 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 IVYcriteria: (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 8 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)
Trang 3self-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 8 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 6 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
3 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 3 “Laws” of IVYality (Ultimate Ideality) & IVY- Matrix of Bipolar Variables
The 3 “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
Trang 4Degree 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/ 0 [Dimension]: + ∞
Low Medium High/ Extreme
1
Quantity
(Number/
Amount):
bidirectional
Negative;
One; mono-;
bi-; few Several;
multi-Multitude; multi-; poly-; ubiquitous; myriad
2
Size
(3-DSpace/
Scale):
bidirectional
Anti-matter Nothing; invisible; void
Micro-;
nano-;
atomic;
molecular
Meso-;
average Macro-; mega-; giga-; galactical
3 Efficiency Anti- efficiency No value added; 100% waste
Low efficiency;
high waste
Moderate or average efficiency
High/infinite efficiency; closed (self-contained); complete recyclability; 0% waste
4 “Automaticity” Anti- automaticity Human-operated/ contact Mechaniza- tion
Moderately mecha-nized;
semi-automatic
Fully automatic; machine-operated; self-operating; self-working; no contact
5 Conflict/Contradiction Anti-conflict/ contradiction Friction-less; no conflict; Peace
Minor conflict, contradiction,
or dilemma
Moderate conflict, contradic-tion,
or dilemma
Major conflict; all-out or perpetual war
6
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; net-worked; total integration
7 Simplicity Absolutely complex Complex; convoluted Barely simple Moderately simple Absolutely simple
8 Variety:
bidirectional
Anti-variety Completely homoge-neous or
symmetri-cal; rigid; complete
Low degree of freedom; High
Moderate degree of
Completely heterogeneous or asymmetri-cal; absolute degree of freedom or
Trang 5standardi-sation; no degree of freedom; Oblique
standardisa-tion
freedom or variation
variation; No standardisa-tion; extremely modularised or flexible
9 Beauty/Ergonomics Ugly; shocking Plain; unadorned Mono-chrome Modera-tely beautiful Multi-coloured; awesome
10
Identification/
Detection/
Branding:
bidirectional
Anti-identifi-cation/
detection/
branding
Incognito; invisible; transparent Plain
Conspi-cuous;
selectively recognised
Globally recognised; glaring
11 Versatility Anti- versatility Nowhere; punctiform
1-D; 2-D;
uni-, bi-lateral
3-D; multi-lateral 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 Anti- functional Dys-functional Mono-, bi- functional Multi- functional Multi-, poly-functional
14
Material/
Substance/
Physical State
Anti-matter Gas; vacuum; field; void; wave Liquid; soft; 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 Anti- flexibility Monolithic; rigid; jointless; No joint
Soft;
Single/double-jointed
Softer; Multi-jointed Extremely flexible or mobile; fluid
17 Vibration:bidirectional Anti- resonance 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
20 Cost Loss; debt Free Inexpensive; cheap Expensive; cosly Astronomical cost
22
Length
(Width/thick-ness/ Height)
Anti-linear
23 Quality/
25 Colour Anti-colour None; invisible Plain; mono-; bi- Multi- Whole colour spectrum
26 Reality:bidirectional Anti-reality None Fictitious Virtual; artificial Physical; visceral
27 Coordinates(Position) Anti- coordinates None 1-D; 2-D 3-D Multi-/poly-dimensional
28 Environment:
29 Temperature:bidirectional Absolute zero Zero; freez-ing point Cold; room temperature Hot Extremely hot
30 Form/Shape:bidirectional Anti- form/shape Amorphous
Linear;
geons;
simple;
1D;2D
Hierarch-ical;
Cells, the contents of which are embolded in table 1 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
Trang 6very high efficiency Other variables in table 1 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 1 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 2 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 1 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 1 to 5 Computing networks are currently considered to be moving towards the peak of level 4 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
mega-problems 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
Trang 7This supersystem will form a new genus at level 1 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)/ Mini-problems
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
“unusuality” or
improbability
Closed-system solution(s)/ Midi-problems
Minor structural change (intermediate “creaLogical” substitution); significant quantitative and qualitative changes; intermediate-order or surprising (2-D) emergent properties;
Intermediate (rarer) tools and technology
Core domain; System
Level 3: National
“unusuality” or
improbability
“Extended”
closed-system solution(s)/ Maxi-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 solution(s)/ Mega-problems
Emergent (bisociated/ hybrid/transition) system; cross-fertilisation or “bisociation” of tools, technology, and resources in apparently disparate domains
Peripheral domain(s); Super-system Level 5: Global
“unusuality” or
improbability
Open-system solution(s)/ Giga-problems
Completely unforeseen (3-D) emergent properties; new invention or genus; paradigm shift; discovery or application of new (“original”) principle or technology
Remote domain(s); New system
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 8 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?
Trang 8Problem-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 4 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
problem-archetypes, inventive problems belong to problem-archetype 4 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 1 These technical conflicts could be described as sub-archetypal problem 4 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)
Trang 9B: 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 3 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, “Solution-Archetypes,” 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 “closed-system 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”
Trang 10- 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
PROBLEM-DEFINITION 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-attribute-function 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) knowledge-base: 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-Space
Application of solutions obtained (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 4 as the “SCAMPER-DUTION” matrix This matrix includes solution-patterns from Osborne-Eberle’s SCAMPER23 as well as the 40 Inventive Principles and Separation Heuristics from