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Combining Quantitative and Qualitative Aspects of Problem Structuring in Computational Morphological Analysis

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Combining Quantitative and Qualitative Aspects of Problem Structuring in Computational Morphological Analysis 1 Combining quantitative and qualitative aspects of problem structuring in computational morphological analysis Its role in mitigating uncertainty in early stage design creativity and innovation and how best to translate it into practice. A thesis submitted for fulfillment of the requirements of Imperial College London for the degree of Doctor of Philosophy Presented by Bruce Garvey Dyson School of Design Engineering Date: October 7th 2016 2 COPYRIGHT DECLARATION The copyright of this thesis rests with the author and is made available under a Creative Commons Attribution, Non-Commercial, No Derivatives licence. Researchers are free to copy, distribute or transmit the thesis on the condition that they attribute it, that they do not use it for commercial purposes and that they do not alter, transform or build upon it. For any re-use or redistribution, researchers must make clear to others the licence terms of this work. Declaration of Originality I can confirm that this thesis was prepared and developed by myself. Specific quotations by other authors have been presented as italicised references and been suitably identified within the body of the text. Other references ad citation are identified also within the text and subsequently listed in the bibliography 3 ABSTRACT Morphological Analysis (MA) is a problem-structuring method that defines a problem as a set of key parameters, especially under conditions of uncertainty and complexity. Each parameter is broken down into a set of discrete states or dimensions, being qualitative or quantitative in nature. The scale of the problem is represented as a product of all the selected parameters and their individual states expressed as a total number of configurations. This is the problem space. Configurations where each state within a parameter is deemed consistent with every other state across the other parameters are identified and isolated. This is called the solution space. MA’s uptake has been patchy, and latterly overlooked mainly due to the user experience being compromised by three interrelated factors: poor access to support software which can address the combinatorial explosion generated by multi-parameter problem spaces inherent in the use of MA; insufficiently flexible processes that address users’ operational constraints; seen to be overly generic, disguising identification of specific application areas of interest. The main research aim in this thesis is to address these constraints. Action Research was used to develop a viable prototype, and beyond, making the product robust enough for commercially viability. The prototype combined algorithms and internal databases with cross-platform accessibility – an innovation complemented by improved processes to enhance user friendliness whilst maintaining methodological integrity. New research areas, including the latest incarnation of MA, are presented with particular emphasis in the areas of ideation, technological creativity and innovation. A company has been established to exploit the technology, with NATO purchasing a licence. With a paucity of in-depth literature on the method combined with little evidence of demonstrable outcomes the thesis is one of a handful of dedicated publications in the last 40 years thus providing a major contribution to the understanding of “Zwickian” Morphological Analysis. 4 PREFACE Acknowledgements The author would like to thank his supervisor, Professor Peter Childs, Head of the newly established Dyson School of Design Engineering at Imperial College. It was his initial enthusiasm for the topic of Morphological Analysis that enabled me to take up this research role, and by giving me his support and encouragement throughout the last three and a half years has led me to submitting this thesis. His interventions have been incisive and have kept me on the academic straight and narrow – a difficult ask when dealing with a student whose previous numerous decades had been spent in the business arena. I have also to thank my co-founder and director at Strategy Foresight Limited, Dr Nasir Hussain, a formidable “morphologist” in his own right, who has given me his profound support during this process. During our numerous discussions and work sessions, not just over the period of the PhD, but in the learning and experiential phase prior to starting the research programme, he has been instrumental in helping me to forge the ideas and concepts developed in this thesis. His understanding of the need for me to take time-out from conducting mainstream business at SFL has been of special value. Other acknowledgements of encouragement must also go to my other co-directors and colleagues at Strategy Foresight Ltd; Dr Giles Russell, without whom I probably would not have considered approaching Imperial College, Jeremy Glover, Dr David Campbell, Brenda King MBE and Dr Wes Harry. Mention of course must be made of the “in-house” team at the Dyson School, Sarah Wissing, Sam McKenny and Alex Marsh who have been ever helpful and cheerful. Thanks also to Gabriel Amorim and Erwin Saevedra who converted my instructions and product briefs into code. There is one acknowledgement that I have to make and this is to Dr Tom Ritchey, probably the leading MA practitioner and evangelist in recent times. It was Tom, whilst at the FOI in Sweden, who brought MA into the 21st century with the 5 development of the Carma/Casper software. Without his flying a lonely flag for MA these last couple of decades, my major re-engagement with MA, following earlier exposure to its value, might not have been re-ignited. Finally I have to mention naturally enough my wife, Golnaz, and my two sons, Sean & Patrick and my daughter Roaya. Apart from having to put up with me over these last three and a half years, none of them ever questioned why I should be doing a PhD at my age – their attitude being – “yes – go for it”. These last few weeks of writing up have been especially difficult (much more than just challenging), as I’ve had to battle against the twin evils of Procrastination and Formatting of text (when I was young we had secretaries to do that!). My wife and daughter have done sterling work in helping with the latter problem – the lack of an intuitive interface that MS Word and other Office features which I have confronted, has brought on severe bouts of “grumpiness” over the last few weeks for which I apologise. Resources: Access to the on-line version of MA presented in this thesis, and the Decision Support Methods database can be obtained by contacting the author at [email protected] or at [email protected] 6 CONTENTS COPYRIGHT DECLARATION 2 ABSTRACT 3 CONTENTS 4 PREFACE Error! Bookmark not defined. NOMENCLATURE Error! Bookmark not defined. SCHEDULE OF FIGURES 12 CHAPTER 1 INTRODUCTION 16 PART 1 POSITIONING AND RESEARCH APPROACH 25 CHAPTER 2: PROBLEMS GOVERNED BY UNCERTAINTY, RISK, and COMPLEXITY – HOW TO MAKE DECISIONS UNDER SUCH CIRCUMSTANCES 26 1.2: Problems and their characteristics 28 1.2.1: Problem Types 28 1.3: The Risk Spectrum: Positioning Uncertainty 35 1. 4: Uncertainty and Risk – a confusion of terms when it comes to measurement 37 1.5: Profiling Risk and Uncertainty 39 1.5.1: Event Predictability 39 1.5.2: Event Visibility 39 1.5.3: Quadrant 1: Predictable & Identifiable. 41 1.5.4: Quadrant 2 identifies predictable events not yet identifiable. 41 1.5.5: Quadrant 3:Unpredictable & Identifiable. 41 1.5.6: Quadrant 4: Unpredictable & Not Identifiable. 41 1.6: Complexity 44 1.6.1: What is complexity? 44 1.6.2: Properties of Complexity 46 1.6.3: Relevance of complexity 47 1.7: Decision Making and Decision Support 48 1.7.1: How to define decision-making? 48 7 1.7.2: What is Decision Support? 49 1.8: Problem Structuring Methods 51 1.8.1: Beyond PSMs 55 Conclusion - Re-positioning Morphological Analysis (MA) as a PSM 56 3.1 Introduction 58 3.2 Objective of the Research Programme 58 3.3 Study and Outcomes to-date. 58 3.4 Live case studies 59 3.5 Action Research Principles 61 3.6 Other research influences 63 3.6.1 Technology Readiness levels (TRLs) 64 3.6.2 The Fraunhofer Model 66 3.6.3 Lean & Lean Start-up 67 3.7 Actual Research Process Adopted 69 3.8 Operational Issues 71 Modules 72 3.8.1 Addressing the Disadvantages and Performance Constraints 74 3.8.2 Module 1 Research 75 3.8.3 Detailed Breakdown of Modularised Research Programme 77 Conclusion 77 PART 2 MORPHOLOGICAL ANALYSIS – ITS DEFINITION AND USE 80 CHAPTER 4: MORPHOLOGICAL ANALYSIS (MA) AND GENERAL MORPHOLOGICAL ANALYSIS (GMA) DEFINED 81 4.1: Introduction 81 4.2 Historical Summary 85 4.3 The Role of Fritz Zwicky 86 4.4 Morphological Analysis (MA) or General Morphological Analysis (GMA)? 87 4.5 Other Schools and Interpretations 91 4.5.1 Robert Ayres 91 4.5.2 Russell Rhyne & Geoff Coyle 93 4.5.3 Michel Godet 94 4.5.4 Tom Ritchey 95 4.5.5 Arnold et al 97 4.6 Other Influencers and Proponents 99 8 4.6.1 Eric Jantsch 99 4.6.2 Simon Majaro 100 4.6.5 Cross and Childs 102 4.7 Towards a definition of Morphological Analysis 103 4.7.1 Formal 103 4 .7.2 Informal 104 CHAPTER 5: AWARENESS AND REPUTATION OF MA (Including Literature Review) 106 5.1 Introduction 107 5.2 Literature Survey & Analysis of Aggregators 107 5.3 An analysis of DSMs 110 5.4 Surveys and Method Studies 114 5.5 Other observations 117 5.6 Search engine analysis (Scopus and Google Scholar) 119 5.6.1 Google Scholar 120 5.6.2 Scopus 120 5.7 The Alvarez/Ritchey GMA applications white paper study 121 Conclusion 122 CHAPTER 6: SUMMARY OF PROS AND CONS 123 6.1 PROs or Advantages 123 6.2 CONs or Disadvantages 128 6.2.1.
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