Contents of

Heuristic Innovation

 

Dedication   iii

Table of Contents v

Table of Examples     ix

To all problem solvers    xi

Preface       xv

Organization of heuristic innovation in three parts   xvii

 

Part A Mental Problem Solving – How the Mind Solves Technical Problems   1

Goal of heuristic innovation  1

Procedure  2

Assumptions    2

Analogy of visual cues and problem-solving seeds   7

Using seeds   8

Solutions  11

Causes and effects in a well-defined problem  12

Plausible root-cause analysis  17

Forms of the proforma graphic 21

Focus on attribute → unwanted effect → attribute units     21

Orphan attributes  23

Questions having answers / Problems having solution concepts  23

Inventing problems  23

How do seeds work?  24

Generification of problem definition  27

Iteration in mental problem solving    29

Natural thinking in problem solving  30

The neural chemistry of problem solving  32

Brain lateralization          34

The struggle between intuition and logic     34

Resolving the struggle between intuition and logic  36

Brain divergence  37

Transition from structured to unstructured problem solving  38

    

Part B Application of heuristics     41

Preface       41

Origins   43

  Proof of efficacy  44

Introduction     45

  Structured problem solving from TRIZ to USIT      45

The model of heuristic innovation  48

Logical problem solving – a linear path   51

Problem definition – the heart of heuristic innovation  52

Engaging both hemispheres of cognition     55

Metaphors – thought starters     54

Awareness images     55

Metaphorical images     56

Hemispheres of cognition     57

Goal of studying cognitive-hemisphere modes of thinking  57

What our two cognitive hemispheres have to offer    58

When do we use both logical and intuitive thinking traits? 61

Ambiguous metaphors     63

Filters  64

Two objects – ultimate focus  66

Introduction of thought paths  67

Examples of thought paths found through attribute paring     68

Depth of understanding of an effect     74

Using thought paths     74

Attribute pairing in ambiguous effects     75

Thought paths fond through attribute triplets     80

Images in problem solving  82

A real-world problem     82

More on cognitive-hemisphere thinking traits  90

Heuristics    94

Strategy for heuristic innovation demonstration   94

Demonstration problem: the loose wire-harness connectors   96

Construction of a problem statement     96

Simple sketch     97

Discussion     99

Iteration of problem statement     100

Iteration of heuristics         103

Utilize an unwanted effect     103

Eliminate an unwanted effect     104

Nullify an unwanted effect     104

Challenge assumptions      105

Take objects to extremes     105

Take attributes to extremes     106

The transition from USIT to heuristic innovation     111

The USIT plausible root-cause heuristic     111

The heuristic-innovation transition     113

How to invent from an unwanted effect     114

Left behind?     118

In the end, it is problem analysis        118

Conclusion     120

 

Part C      Theory, Derivation, and Application of Heuristics     123

     Preface        123

     Overview      124

I. Theory for Derivation of Heuristics  125   

          Introduction            125

Heuristics in mathematics     125

Definition of heuristics and intuition     126

Table C1. Examples of heuristics used by technologists in problem solving  127

Heuristics seed the subconscious     127

The use of heuristics in problem solving     128

Unstructured brainstorming   129

          Background     130

Structured, problem-solving methodologies     130

Origin of heuristics     130

A simple model of cognition     130

Perspectives and biases in problem solving     131

Abstraction of heuristic      133

Comments on the method     133

  The Method for Derivation of Abstract Heuristics  135

     Application of heuristics to a physical-world problem   135

Problem-definition phase     135

Problem-analysis phase     137

Problem-solution phase     141

     Table C2. Summary of heuristics used     146

  Abstract heuristics – no physical-world references  147

     Application of heuristics to an abstract problem   148

Problem-definition phase     148

Problem-analysis phase     149

Problem-solution phase     149

     Table C3. Summary of new graphic heuristics for an abstract problem 155

     Abstract heuristics for abstract problems 155

     Graphic representation of heuristics 156

     Comments on the adaptation of derived heuristics to other fields    157

Object      159

Information as an object      159

Attribute      160

Function      160

Object abstraction     161

Note on Mathematical Heuristics 162

Table C4. Comparison of twelve mathematical heuristics with known and derived heuristics  162

 

II. Derivation of Heuristics     163

     Introduction     163

          Common rules / uncommon language 163

     Derivation     164

Definitions   164

Axioms      165

Known Heuristics   166

Abstraction 167

Problem state      167

Problem-state – to – Solution-state strategies     169

Problem State graphic model     170

Solution State graphic models     170

Characterization of Attributes     171

     Analysis of solution states with example solutions  174

Solution by utilization     174

Table C5.  Space-time attribute modifications for solution by utilization      175

Examples of solution by utilization     177

Solution by A-F-A linking     179

Solution by nullification      181

Solution by elimination        184

Graphic metaphors as solution heuristics     185

Table C6 Random two-attribute arrangements and their metaphorical implications.      186

Spatial and temporal heuristics     188

Solution by transposition 190

Table C7.  Paired spatial | temporal attributes     191

Table C8.  Summary of Heuristics for Problem Statement, Analysis and Solution 193

     Summary of heuristic strategies for problem solving     196

          Solution strategies     196

     Phraseology in words and graphics  198

     Conclusion of Derivation of Heuristics     199

 

III. Application of Derived Heuristics     201

     Introduction     1201

Inventing a belt – a problem to be solved using the newly derived heuristics    202

Deduction of problem definition information     202

An unwanted effect as a strategy for invention    203

Graphic problem statement  205

Solution by utilization    207

Solution by utilization using A-F-A linking  210

Solution by nullification      212

Solution by elimination   214

     Conclusion of Application of Derived Heuristics         216

 

 

Appendices

A1. Infovores crave information    217

A2. For managers: Strategic partitioning of problem-solving resources  219

 

 

Glossary     223

 

References     231

 

Exercises     233

 

Acknowledgements    237

 

About the Author   239

 

Index     241


Examples – Ideas, partial demonstrations, completed exercises, etc.

 

 

 

Complete problems:

     Erasure smudge        5, 8–17, 19,  23-29,

     Pin and balloon         49-55, 64-81

     Loose wire-harness   96-110

     Hand-held binoculars     135-145

 

Engineering scale-up:

     Audio speech compression 2

 

Graphic proforma:

     Trunk lid and airbag     3

     Erasure smudge        24, 25-26, 28

     Pin and balloon         70

     A law and a suspect   160

     Specimen and glass slide     166

     Rod and solid        168

     N2 and O2 (speed control)     177

     Polymer and location   182

     Belt and swabs          182

     Front wheel and rear wheel     183

     Cell and blood       183

     Belt and buckle          205, 207

     Belt: stress and creep     210, 211

    

Images and metaphors

     Laundry room leak     81-89

 

Introspection

     Jigsaw puzzle     91

     Volume of a sphere     92

     Inventing an electric motor     92

 

Invention:

     Computer mouse     115-117

     Men’s trousers belt     202-215

 

Problem statements (well defined and not so well defined)”

     Pin and balloon         497, 51-53,

     Four saloons      61-62

     Two trains and a bumble bee    63

 

Solution by utilization:

     Nitrogen and oxygen    177

 

Solution using A-F-A links:

     Pedal and driver (speed control)   180

 

Solution by nullification:

     Polymer birefringence          182

     Conveyor belt and swabs     182

     Turn radius of a vehicle       183

     Pancreas cells in silicon holes  183

 

Solution by elimination:

     Car radio temptation         184

 

 

 

Exercises

     Practice metaphors    6

     Sticky asphalt         39

     Flag pole invention 39

     Solution vs. concept   39

     Balloon sketch error 53

     Two trains and a bumble bee    63

     Reactions to Fig. B.3   64

     Ice cream         67

     Reactions to language      121

     Problem from one’s own field   121

     Apples in a box              121

 

     E1– A fix-it problem        233

     E2 – Reverse engineering     233

     E3 – Attributes              233

     E4 – Generification of objects     233

     E5 – Points of contact         234

     E6 – Invention           234

     E7 – Well-defined problem     234

     E8 – Functions               234

     E9 – Object minimization     234

     E10 – Solution strategies     235

     E11 – Attribute pairing from lists of randomly selected attributes 235

     E12 – Attribute pairing in ambiguous effects    236

    

 

 

 

                     (More examples are found in Ref. 1)