Bio inspired design: how do designers use tools in new product development process?

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D

IPARTIMENTO DI

I

NGEGNERIA DELL

’E

NERGIA DEI

S

ISTEMI

,

DEL

T

ERRITORIO E DELLE

C

OSTRUZIONI

RELAZIONE PER IL CONSEGUIMENTO DELLA LAUREA MAGISTRALE IN INGEGNERIA GESTIONALE

Bio Inspired Design: How do designers use biomimicry tools during new

product development process?

RELATORI CANDIDATO

Prof. Antonella Martini Davide Sanna

Dipartimento di Ingegneria dell’Energia, dei Sistemi, del Territorio e delle Costruzioni

Eng. Francesco Paolo Appio

Dipartimento di Ingegneria dell’Energia, dei Sistemi, del Territorio e delle Costruzioni

Prof. Sofiane Achiche

Department of Mechanical Engineering Ecole Polytechinique de Montreal

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"Everything you can imagine, nature has already created."

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Bio inspired design: how do designers use biomimicry tools during

new product development process

? Davide Sanna

Sommario

La mia tesi è il risultato di un progetto durato sei mesi, svoltosi presso l’Ecole Polytechnique de Montreal. Il lavoro è focalizzato su una metodologia di sviluppo di nuovo prodotto con un trend in crescita negli ultimi quindici anni: la Biomimetica. L’obiettivo del progetto è quello di analizzare questo tipo di metodologia, sia dal punto di vista teorico, che pratico. In particolare, il focus è stato posto sullo studio degli strumenti che vengono utilizzati dai designers e dai ricercatori per mettere in atto il processo. Per farlo abbiamo risposto a tre domande di ricerca: 1) I designers sfruttano gli strumenti messi a disposizione dalla letteratura? 2) Gli strumenti vengono utilizzati nel modo corretto? 3) Il loro utilizzo porta dei vantaggi durante il processo di sviluppo di un nuovo prodotto? La raccolta dati è stata effettuata tramite due canali: un questionario che è stato sottoposto a designers e ricercatori provenienti da tutto il mondo e da diverse tipologie di aziende, e un’intervista diretta al CEO della Mawashi Protective Clothing Inc.. L’analisi è stata fatta in tre step successivi, tramite 1) analisi descrittiva; 2) regressione logistica; 3) calcolo dei coefficienti di correlazione di Spearman.

Abstract

My thesis is the result of a project lasted six months done in the “Ecole Polytechnique de Montreal”. The work focuses on a new product development process which has had an increasing trend in the last fifteen years: Biomimicry. The goal of the project is to analyze this process from both practical and theoretical point of view. In particular we focused on the study of biomimicry tools used by designers and researchers during the process. To do that we answered three research questions: 1) Do designers use the tools made available from literature? 2) How do they use these tools? 3) Is their utilization useful? The data collection has been made through two ways: a survey submitted to designers and researchers from around the world and working in different kind of companies, and a face to face interview with the CEO of the Mawashi Protective Clothing Inc.. The data analysis has been done through three steps: 1) descriptive analysis; 2) Logistic regression; 3) Spearman’s correlation

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LIST OF TABLES

Table 1: Literature review references ... 17

Table 2: Definitions ... 20

Table 3: PRIZM matrix ... 40

Table 4: BioTRIZ matrix ... 40

Table 5: Tools description ... 42

Table 6: Survey development process ... 43

Table 7: Sample experience level ... 52

Table 8: Familiarity ... 53

Table 9: Tools evaluation ... 59

Table 10: Literature tools evaluation ... 63

Table 11: Tools comparison ... 67

Table 12: Distances ... 68

Table 13: Awareness indicators ... 69

Table 14: First logistic regression results ... 70

Table 15: Significant variables ... 70

Table 16: Second logistic regression ... 71

Table 17: Significant variables ... 72

Table 18: First correlation analysis ... 73

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LIST OF FIGURES

Figure 1: Paper structure ... 10

Figure 2: Literature review flowchart ... 12

Figure 3: Articles selection flowchart ... 12

Figure 4: Literature review results ... 13

Figure 5: WhalePower wind turbine ... 22

Figure 6: Bio inspired pump ... 24

Figure 7: Bio inspired self-healing material ... 25

Figure 8: Da Vinci index ... 26

Figure 9: Biomimicry growth ... 27

Figure 10: Biomimetic publications ... 28

Figure 11: connected words ... 29

Figure 12: Patents publication ... 29

Figure 13: Articles publications ... 30

Figure 14: Biomimicry estimated impact ... 31

Figure 15: Biomimicry taxonomy ... 35

Figure 16: AskNature search sample ... 36

Figure 17: SAPPhIRE model of causality ... 37

Figure 18: SAPPhIRE model sample ... 38

Figure 19: Literature review process ... 41

Figure 20: Survey development process ... 45

Figure 21: Qualitative analysis methodology ... 48

Figure 22: Awareness indicators methodology ... 48

Figure 23: Logistic regression methodology ... 49

Figure 24: Spearman's correlation methodology ... 50

Figure 25: Sample composition ... 51

Figure 26: Sample general experience ... 51

Figure 27: Companies size ... 52

Figure 28: Familiarity level ... 53

Figure 29: Familiarity with AskNature ... 54

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Figure 32: Tools usage in phase 1 ... 55

Figure 36: AskNature evaluation ... 60

Figure 37: IdeaInspire evaluation ... 60

Figure 38: E2B evaluation ... 60

Figure 39: DANE evaluation ... 61

Figure 40: BioTRIZ evaluation ... 61

Figure 41: Knowledge based CAD system evaluation ... 61

Figure 42: BioCards evaluation ... 62

Figure 43: Tools evaluation ... 62

Figure 44: AskNature comparison ... 63

Figure 45: IdeaInspire comparison ... 64

Figure 46: E2B comparison ... 64

Figure 47: DANE comparison ... 65

Figure 48: BioTRIZ comparison ... 65

Figure 49: Unused percentages ... 74

Figure 50: Awareness indicators ... 75

Figure 51: Logistic model for radicalness 1 ... 75

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1. INTRODUCTION

1.1 Problem definition

Never as these years is important to find a solution to the big consumption of resources. We have overtaken the point of no return: our planet is unable to give us all the resources that we need in a sustainable way. That’s why is important to find more and more efficient solutions in goods production and usage. Otherwise customer needs are more and more differentiated and the market requires more innovative and functional products. This creates pressures on the designers who try to increase their creativity adopting new methodologies and tools.

For these reasons biomimicry has been a growing trend in the last 15 years. The term Biomimicry is constructed from the Greek “bios” meaning life and “mimesis” meaning to imitate. The concept is to take inspiration from nature to solve problems and create innovative products. There are many great samples of product inspired by nature, such as Velcro invented by Georges de Mestral, or the Eastgate building center in Zimbabwe inspired by the anthill structure.

Actually the issue is more complex: around this concept researchers developed methodologies and tools to help designers during the all the phases of the process. In literature we can find many of these methodologies and tools. Some of them is tested in experiments done with students in the academic field to check their practical utility. Unfortunately all the case studies described in the scientific articles are done in the academic field, so we have no proof of their real utilization inside companies.

1.2 Aim

For this reason we decided to investigate how they are really used by designers in real processes. The aim of this research is to piece together the state of art of the Biomimetics field describing the most important works done until now. In particular we will focus on the biomimetics tools. Then we related directly with practitioners. We asked them, through a survey and an interview, questions about how they realize the new product development process using biomimicry comparing it with the traditional process.

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1.3 Objectives

The different objectives defined to achieve the final results are:

 Rebuild the state of art of the biomimetics field focusing on the tools for NPD process;

 Collect data through a survey and an interview to obtain as more data as possible;

 Manage, analyze the data collected through statistical models and report the results obtained.

 Validate the results through a different statistical model. 1.4 Paper structure

Figure 1 shows how the work is organized.

After introduced the research in the first section we describe the state of art of the biomimetic field. This is useful for the readers to better understand the contest and the future analysis. At the beginning of each chapter is described the methodology that we followed for that part. In section 3 we explained the survey structure4 and its contents. Then we presented the results in the section 5 interpreting the statistical data obtained in output from the software. In the last part we resumed the results obtained and we suggested

Section 1: Introduction Section 2: Literature review Methodology Section 3: Survey development Section 4: Data analysis and

results

Section 5: Conclusions and recomendations

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2 LITERATURE REVIEW

In this chapter we will present the most important studies done in the biomimetics field, useful to understand the starting point of this research and the future analysis. The studies will be presented starting from a macro-point of view with the definition and the distinction between the terms biomimicry, bionics, biomimetics and bio-inspired design.

Subsequently we will explain how biomimicry is diffusing inside universities and companies, and which is its economic impact on the business.

Afterwards we will focus on the practices explaining the two approaches used by designers to apply biomimicry inside the new product development process: “Problem based” and “Solution based”.

Finally we will report the main works about the most important biomimicry tools. The thing to notice is that all the tools are described inside the academic world. There is no proof on how they are really used inside companies; we only have some example coming from student experiment. Whereby this will be the starting point of this research, or rather we will try to understand if and how companies use these tools and how they do it.

2.1 Literature review methodology

The literature make available many tools to aid designers during the traditional NPD process (Bhuiyan, 2011) and they are widely used by companies during their processes (Nijssen and Frambach, 2000; Stolterman and Pierce, 2012). The use of Biomimicry add complexity to the NPD process, even more so we suppose that all the Biomimicry tools available from literature are widely used by companies in their processes. Unfortunately there are no available studies proving this theory. So the aim of this research is to investigate on how designers and researchers use these tools inside companies.

2.1.1 Articles selection and argument review

The starting argument was “Biomimicry”. So we started to analyze the articles selected using different channels like “Google scholar”, the online database available from the Polytechnique, the Polytechnique library and the “Mendeley” tool search.

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keywords: “Biomimicry”, “Biomimetics”, “Bio-inspired design”, “Bionics”, “Product inspired by nature”.

After the first articles search we decided to focus on the methodologies developed by researchers, changing the keywords for the search (see the feedback in the figure) and using the articles linked in the bibliographies.

The same steps have been followed for the second iteration. After have read the articles we decided to focus on the tools changing the search keywords.

At the end of the two iterations we have selected 118 articles regarding the three topics mentioned before. Articles selection Argument review Methods Tools Biomimicry

Figure 2: Literature review flowchart

2.1.2 Articles selection

After the first screening of more than 100 articles, as shown in the flow chart we group them in three patterns:

 General Biomimicry;

 Methodologies;

 Tools.

Then we start a deep lecture of the most relevant articles and books. For “relevant” we consider the most mentioned in the bibliographies and the most pertinent compared with the keywords. Abstract reading Is the article relevant? Choose a

category Read article

Are articles finished? Tools selection Yes Yes No

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The flowchart in Figure 3 shows the decisional process followed during the articles analysis. It is to notice that the final activity shown is “Tools selection” because it is the main topic of the research but we followed the same steps during the “General Biomimicry” analysis and

“Methodology” analysis achieving the following results:

General

Biomimicry

Methodologies

Tools

Definitions

Case

studies

Problem

based

approach

Solution

based

approach

AskNature

IdeaInspire

Engineering

to biology

thesaurus

DANE

BioTRIZ

BioCards

Knowledge

based CAD

system

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In Table 1 is shown the articles splitting done during the literature review:

Keyword Argument Articles

General Biomimicry

General

(Bonser 2006) (Edwards 2014)

(Feng, Cheong, and Shu 2014)

(Fermanian Business and Economic Institute 2010)

(Gamage and Hyde 2012)

(Srinivasan and Chakrabarti 2010) (Hu, Feng, and Dai 2013)

(Johnson, Hayles, and Chen 2011) (King 2007)

(Lepora 2013)

(Lu and Lieber 2007a)

(Pade, Petschow, and Pissarskoi 2009)

(Parvan, Schwalmberger, and Lindemann 2011) (Quinn and Gaughran 2010)

(Shinomura 2008) (Shu 2012)

(Singh et al. 2012)

(Srinivasan and Chakrabarti 2010) (Vattam, Helms, and Goel 2009)

(Fermanian Business and Economic Institute 2013)

(Thomas 2014)

Definitions

(Ahmed-Kristensen, Christensen, and Lenau T. 2014)

(Ashok K. Goel, Swaroop Vattam, Michael Helms 2011)

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(J. F. V Vincent et al. 2006) (Vogel 2000) (Crowford 2008) (Iouguina 2012) (Wahl 2006) Case studies (Antonescu 2010) (Balazs 2007a) (Bar-Cohen 2006) (Benyus 1997)

(Cheong, Hallihan, and Shu 2012) (Cheong and Shu 2013)

(Ingrid C. de Pauw et al. 2014) (Eggermont)

(El-Zeiny 2012) (Holbrook et al. 2010)

(Torben Lenau and Hesselberg 2013) (Torben Lenau and Mejborn 2011) (Mitić and Miljković 2014)

(R. L. Nagel et al. 2008)

(I C De Pauw, Karana, and Kandachar 2012) (Shinomura 2008)

(Shu 2006)

(Simpson and Sastry 2013) (Tsujimoto et al. 2008)

(Vattam, Helms, and Goel 2008) (J. F. V. Vincent 2006)

(“Fluidic Muscle | Festo Corporate” 2015)

(“Self-Healing Plastic Can Regenerate Itself like It’s Alive | DVICE” 2015)

Methodologies Problem based

approach

(Badarnah 2012)

(Badarnah and Kadri 2014) (El-Zeiny 2012)

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(Junior and Guanabara 2005) (T Lenau et al. 2010)

(Michael E. Helms, Swaroop S. Vattam 2008) (Pade, Petschow, and Pissarskoi 2009)

(Pandremenosa, Vasiliadisa, and Chryssolourisa 2012)

(Shu et al. 2011)

(Siang, Muftah, and Sani 2013) (Versos and Coelho 2011)

(Michael E. Helms, Vattam, and Goel 2009) (Michael E. Helms et al. 2008)

Solution based approach

(Badarnah 2012) (El-Zeiny 2012) (Fu et al. 2014)

(Michael E. Helms, Swaroop S. Vattam 2008) (Pade, Petschow, and Pissarskoi 2009)

(Pandremenosa, Vasiliadisa, and Chryssolourisa 2012)

(Shu et al. 2011)

(Siang, Muftah, and Sani 2013) (Versos and Coelho 2011) (Michael E. Helms et al. 2008)

Tools

AskNature

(Deldin and Schuknecht 2014) (Fu et al. 2014)

(Peters 2011)

(The Biomimicry Institute 2009) (Volstad and Boks 2008)

IdeaInspire

(Michael E. Helms, Vattam, and Goel 2009) (CHAKRABARTI et al. 2005)

(Fu et al. 2014)

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(Michael E. Helms, Vattam, and Goel 2009)

Engineering to biology thesaurus

(Fu et al. 2014)

(Goel, McAdams, and Stone 2013)

(Jacquelyn K S Nagel, Stone, and Mcadams 2010) (Torben Lenau et al. 2011)

(Lindemann and Gramann 2004) (R. L. Nagel et al. 2008)

(Jacquelyn K. S. Nagel, Stone, and McAdams 2010)

DANE

(Cheong and Shu 2014) (Fu et al. 2014)

(Goel et al. 2012)

(“DANE: Design Analogy to Nature Engine” 2015)

BioTRIZ

(Bogatyrev and Bogatyreva 2009) (Cheong and Shu 2014)

(Fu et al. 2014)

(J. F. V Vincent et al. 2006) (Volstad and Boks 2008) (Wadia 2011)

(Michael E. Helms, Vattam, and Goel 2009) Knowledge

based CAD system

(Cheong and Shu 2014) (Goel et al. 2012) (Trotta 2011) (Leon 2009)

BioCards

(Keshwani, Lenau, and Kristensen 2013) (T Lenau et al. 2010)

(Torben Lenau and Mejborn 2011) (Volstad and Boks 2008)

Table 1: Literature review references

2.2 Biomimicry, bionics, biomimetics and bio-inspired design

Often in literature, researchers use these terms as synonymous. In fact the general meaning of these words is quite the same but they have little differences that will be explained in this chapter.

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Biomimicry has very old origins, Leonardo da Vinci (1452-1519) used to observe and take inspiration by birds to design his flight machines. Another great example is given by Wright Brothers who in 1903 succeeded in creating and flying the first airplane taking inspiration by pigeon flight.

For the first formal definition we have to wait the 1958 when Jack E. Steele (1924-2009), American psychiatrist, engineer and retired US Air Force colonel, defined bionics as:

“imitation of nature, natural processes, and living organisms in the design of mechanical systems – as solutions “to engineering problems””(Papanek, 1984).

The word became then popular thanks to the TV show “The bionic woman” (inspired by Steele’s work), taking sometimes a different meaning, used mostly in cybernetic and robotics field. In his book “Cat’s paws and catapults”, Steven Vogel (2000) defines bionics

“…as based on living systems. The word ‘systems’ came naturally to those, mostly engineers, initially involved; neural systems and physiological controls formed biological parallels to human technology’s cybernetics and systems theory”.

A comment on this definition has been made by Daniel Wahl who described it from a different perspective saying that

“unfortunately the focus [of bionic-centered conferences] was so exclusively on technological innovation that it almost actively tried to discourage ecological concerns and the issue of sustainability”(Wahl and Baxter, 2008).

In the same years the American inventor, engineer and biophysicist Otto H. Schmitt (1913-1998) started to pay attention; he carried out a research on a physical device that explicitly mimicked the electrical action of a nerve. He became famous also to have created the word “biomimetics”, from the Greek bios (life) and mimesis (imitating). In a meeting at Dayton in 1963 Schmitt stated:

“Let us consider what bionics has come to mean operationally and what it or some word like it (I prefer biomimetics) ought to mean in order to make good use of the

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phenomenology in the hope of gaining insight and inspiration for developing physical or composite bio-physical systems in the image of life”(Harkness, 2002).

The word biomimetics was publically used for the first time in the Webster dictionary in 1974 with the following definition:

“The study of the formation, structure, or function of biologically produced substances and materials (as enzymes or silk) and biological mechanisms and processes (as protein synthesis or photosynthesis) especially for the purpose of synthesizing similar products by artificial mechanisms which mimic natural ones”(Harkness 2002).

According to this definition, in 1994 Janine Beynus, a natural sciences writer with a degree in natural resource management and English literature/writing from Rutgers University, coined the word Biomimicry, from Greek bios (life) and mimesis (imitating). In her book “Biomimicry- Innovation inspired by nature” she gives a definition to biomimicry under three points of view:

 “Nature as model. Biomimicry is a new science that studies nature’s models and then imitates or takes inspiration from these designs and processes to solve human problems.

 Nature as measure. Biomimicry uses an ecological standard to judge the “rightness” of our innovations. After 3.8 billion years of evolution, nature has learned: What works. What is appropriate. What lasts.

 Nature as mentor. Biomimicry is a new way of viewing and valuing nature. It introduces an era based not on what we can extract from the natural world, but on what we can learn from it” (Benyus 1997).

The last term that we will discuss is Bioinspired design, mostly used in the engineering field. The professor of engineering at Georgia Institute of Technology Bert Bras argues that biomimicry implies copying, and simply copying is not necessarily the best or smartest way to do things. He also says that inspiration allows the engineer to take the best from nature and put it in a new (engineering) context.

A question then arises: if there is only one meaning and only one goal, why do we have so many words? About this issue Julian Vincent, chair in Biomimetic in the Department of Mechanical Engineering in the University of Bath states:

“people are inventing an increasing number of other words to label the area, thus giving them some sort of exclusivity”.

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In the Table 2 we present the four terms analyzed with the respective originating field and definitions:

Term Definition Originating Field

Author

Bionics “[the] science of systems that work like or in the same manner as or in a similar manner to living systems”

Medical/ Neuroanatomy

J. E. Steele

Biomimetics the study of the formation, structure, or function of biologically produced substances and materials (as enzymes or silk) and biological mechanisms and processes (as protein synthesis or photosynthesis) especially for the purpose of synthesizing similar products by artificial mechanisms which mimic natural ones

Biomedical engineering/ Electronic

Merriam Webster

Biomimicry Biomimicry is an approach to innovation that seeks sustainable solutions to human challenges by emulating nature’s time-tested patterns and strategies.

Natural sciences Biomimicry Institute

Bio-inspired design

Biologically inspired engineering design uses analogies to biological systems to

develop solutions for engineering problems.

Engineering M. Helms et al.

Table 2: Definitions

Actually, the reasons why we have all these words could have historical origins or could depend on the field where they are used. Analyzing the definitions in a timeline we can notice that there are big differences between the first terms created, probably due to the

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use these words as synonymous with preferences for the term of the origin field (e.g., articles about robotics use more the term bionics, engineering articles use more the term bio inspired, etc.).

The transfer of function from biology to the machine that allows biomimetics to test hypotheses from the biological sciences; otherwise, there is a danger of a merely blind copying or mimicry of design principles with no further insight into the living system (Lepora 2013). This argument is hardly discussed inside biomimicry communities: “How can we define what is biomimicry and what is not?”. In the book “Potential and trends ” the authors try to give an answer:

“Elementary to every definition is, in our opinion, a composition of the three elements that are essential in characterizing biomimetics today: (1) new (technical) possibilities for (2) innovations solving societal problems and/ or fulfilling demands and (3) “learning from living nature,” or more precisely: learning, in the broadest sense, from “biological research”” (Pade et al.2009).

Another question that should be answered is: “Which is the inspiration level whence we start to consider it Biomimicry?” (e.g., Copying the shape of an organism could be considered Biomimetics?). Pade et al. (2009) divide the Biomimicry field into three strands:

 Form and function;

 Bio cybernetics, sensor technology and robotics;

 Nanobiomimetics.

2.2.1 Form and function

The first strand mimics organism shapes and functions even if the phenomenon is not completely clear. In fact many product created with this method are strictly connected with fluid dynamics and turbulences. One example is given by the wind turbines inspired by humpback whales: researchers observed the movements made by this kind of whale and they noticed that they were able to do very tight turn in maneuvering to secure their food, and that was unusual for animals of this size. Studying the body and the shapes of the whale they discovered that the cause of the agility was possible thanks to their fins. In fact, instead to other kind of whales, they have a unique series of bump called tubercles. The second step was to build a mathematical model that could explain this phenomenon. Dr. Frank Fish,

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professor of biology at West Chester University of Pennsylvania, participated to the evaluation of the effectiveness of the tubercles. He said:

“We obtained an actual flipper from a humpback whale and then constructed one flipper with tubercles and a second flipper without tubercles. Both flippers were about two-feet tall and were evaluated in a wind tunnel.”

The work in the wind tunnel showed that the flipper with tubercles exhibited a higher operating angle, prior to stall. Fish added:

“We found that the tubercles allow the operating angle to increase from 11 degrees to 17 degrees, prior to stalling.”

This represents a performance improvement of nearly 40%. The materials employed to make these kind of inventions have a secondary role. It is not important to replicate the perfect structure but only the features that solve a particular functions.

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2.2.2 Bio cybernetics, sensor technology and robotics

Against the first strand, the second one is not strictly related to zoology, botany and ecology. “The fundamental approaches and models of bio cybernetics, sensor physiology and neurophysiology, as well as the ecosystem theory were initially developed in technical areas distant from biology, such as electrical engineering e.g. in resonant circuits, feedback effects, and control circuits, as well as sensors and actuators”(Pade et al, 2009).

The studies in these fields made possible the achievement of important progress in biology, particularly in bio cybernetic, sensor physiology, information processing and robotics. At the beginning the field that most benefited by this progress was the AI (Artificial Intelligence). After a big development, other biomimetics approaches, such as decentralized control, parallel computing, self-organizing software, and neuron networks, moved forward. Obviously, the inspiration model for these innovation is the human body in general, and the brain and the neural connections in particular.

“With the aid of these biomimetic approaches, some of the limitations that have accumulated in the areas of signal and information processing and robotics are being overcome”(Pade et al, 2009).

One of the most famous samples in this field is the actuator inspired by muscle created by the company Festo.

“The bionic muscles consist mainly of a hollow elastomer cylinder embedded with aramid fibers. When the fluidic muscle fills with air, it increases in diameter and contracts in length, enabling a fluid, elastic movement. The use of the fluidic muscle enables motion sequences which approach human movement not only in terms of kinematics, speed and strength, but also sensitivity. The fluidic muscle can exert ten times the force of a comparably sized cylinder, is very sturdy, and can even be used under extreme conditions such as in sand or dust.”(“Fluidic Muscle | Festo Corporate” n.a.)

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Figure 6: Bio inspired pump

2.2.3 Nanobiomimetics

The third strand have the most recent development, even if it has historical origins too: self-assembling monolayers, colloid chemistry. Its evolution has been possible thanks to the big development in the nanotechnologies field; some big challenges in this field are: bio mineralization, artificial spider silk, functionalized surfaces, template controlled crystallization, neurobiomimetics. Nanobiomimetics has its focus “on processes of molecular self-organization as well as on the (ontogenetic) development of molecules, cells, and tissue, including their reconfiguration (reaction to load) and (self-) healing” (Pade et al, 2009). In nature we can find organisms and membranes composed by very complex structures, monolayer or multilayers that fulfill different functions. The goal of biomimetics on self-organization processes is to understand how these processes works and reproduces them in micro fabrication. There are basically two approaches to build in nanoscale:

 Top down;

 Bottom up.

Top-down fabrication process starts with large pieces of materials and reduce them till arrive to the final product. This implied a big waste of material and don’t permit to work at very small dimensions.

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“Self-assembly is emerging as an elegant, 'bottom-up' method for fabricating nanostructured materials. This approach becomes particularly powerful when the ease and control offered by the self-assembly of organic components is combined with the electronic, magnetic or photonic properties of inorganic components”(Lu and Lieber, 2007).

This approach can bring big advantages in the microelectronic field.

As written above, another important strand is represented by the self-healing technologies of which we have a great example.

“The ability to heal wounds is one of the truly remarkable properties of biological systems. A grand challenge in materials science is to design ‘smart’ synthetic systems that can mimic this behavior by not only ‘sensing’ the presence of a ‘wound’ or defect, but also actively re-establishing the continuity and integrity of the damaged area”(Balazs, 2007).

A group of researchers at the University of Illinois created a plastic material able to repair itself if damaged. They built capillary conduits where there are two fluids. If there is a damage, they start to pump those fluids that, once in contact, create a solid polymer. The big innovation is that they can repair holes of big dimensions because the fluids are two king of gels so they don’t fall down under the gravity. The last goal of this research is not only the self-healing, but also the creation of a material system that continually generates itself anew and remodels itself.

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2.3 How rapidly is biomimicry expanding?

Biomimetic technologies arise from a flow of biological ideas turned into engineering, benefiting from the millions of years of design effort performed by natural selection in living system (Bar-Cohen, 2006). During the last years the advances in robotic and biomaterial science favored the development of biomimicry innovation creating a growing trend. To figure out the range of this trend in this chapter we will analyze the data related to the Biomimicry business.

2.3.1 1st research

The Fermanian Business & Economic Institute conducted a research based on U.S. patents publications creating the Da Vinci index to track developments in bioinspiration over time. To do that they use different terms such as biomimicry, nature- inspired, biomimetics, biomimics, and bioinspiration. The DaVinci Index for the U.S. is based on the number of patents linked to bioinspiration, scholarly articles published, and the number together with dollar amounts of grants issued by the National Institutes of Health (NIH) and the National Science Foundation (NSF). The composite DaVinci Index showed a 5-1/2-fold increase between 2000 and 2012. This represented an impressive compound annual average growth rate of 15.3% (“BIOINSPIRATION: An Economic Progress Report” n.a.)

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The graph in Figure 8 shows that even during 2008, when the recession started, there has not been slowing, and the best performance has been registered during 2012 where the Da Vinci index jumped by 24%.

The second analysis of this research is about the articles related to bioinspiration published in journals through the world: it shows that U.S.A. accounted for 25% of the published articles, followed by China with 23%. Italy is in 7th position of the ranking with 5%. The research shows how Chinese universities are more interested in the field. In fact, five out of the top ten universities represented in bioinspired research papers were Chinese and only two were American.

Figure 9: Biomimicry growth

2.3.2 2nd research

According to the previews research, the second one that we consider in this chapter has been conducted by Nathan F. Lepora, Paul Verschure and Tony J. Prescott (2013). They constructed a database of publications on biomimetic researches and related sciences using general web based sources. As we said previously many terms are used as synonymous with the meaning of biomimicry, therefore they used many keywords for they research as: biomimetics, biomimetic, bionics, bionic, biomimicry, bioinspired and bioinspiration. The researchers collected in the database 18 000 biomimetic publications. In the first part of the research, that we will not discuss here for obvious reasons, they analyze the sources of these publications to understand which field is most interested in biomimicry.

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In the second part of the research they pose the question: “How rapidly is the subject of biomimetics expanding?” To answer it they counted the number of publications each year in their database and these are the results:

“we see that in the first decade of this century there has been an explosive growth in biomimetic research, with the number of published papers each annum doubling every 2–3 years”(Lepora, 2013).

Starting in 1990 with almost 50 publications, the number of publications reached 2000 in 2005 till to arrive at 3000 publications in the last years. Undoubtedly, we can say that biomimetics diffusion has a very positive trend. Furthermore this trend encouraged many foundations to finance biomimicry projects and researches.

“This changing research landscape should lead to changes in the composition of academic departments. We expect that a greater number of researchers, research groups and departments in leading universities will be explicitly focused around biomimetic research”(Lepora, 2013).

Figure 10: Biomimetic publications

Another interesting point of this research are the words connected to the keywords in the publications. This allows to understand the field where biomimicry is studied and its application fields.

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Figure 11: connected words

This biomimicry big growth is not restricted to the theoretical field but attracted the attention of many firms. This is confirmed by an increase of the patents registered in U.S. (Bonser, 2006). The graph in Figure 12 shows a forecast of the cumulative total number of patents until 2040. The model predicts that we are currently a little over 50% through a period of technological innovation, so if this prediction is robust there is excellent potential for growth within the sector for at least the next decade.

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To confirm this thesis we searched on “Google Scholar” the number of publications in scientific journals for each year starting from 2000 to the present that contains at least one of the following keywords:

 Biomimicry;

 Bionics;

 Bio inspired;

 Biomimetic.

Figure 13: Articles publications

We obtained in total 257.860 articles distributed in the years as shown in the graph, starting with 2860 publications in 2000 and with 32.100 publication in 2014. Therefore, as we can see in Figure 13 the publication growth is exponential until 2014 where we have a little decrement.

Another forecast done by the Fermanian Business and Economic Institute, commissioned by San Diego Zoo Global (Fermanian Business and Economic Institute 2010) says that the large biomimicry influence on a large number of American companies will translate into a sizable impact on total U.S. gross domestic product (GDP) and employment. It has been estimated that in the next 15 years the output in Bioinspired goods and services could account for 300 billion dollars. To have an idea of the amount, in 2010 American companies spent 285 billion dollars on computer software. While this seems to be a small part compared to the total goods and services output (about 21 trillion dollars), biomimicry will still have an highly

0 10000 20000 30000 40000 50000 60000 1995 2000 2005 2010 2015 2020

Publications

N. of publications Espo. (N. of publications)

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Figure 14: Biomimicry estimated impact

Overall, in the report the authors state that biomimicry could also have an impact on the national efficiency in terms of energy, mineral, forest resources and CO2 pollution. It is estimated that since 2010 to 2025 biomimicry will allow to save about the 10% of the U.S. Gross National Income. This would have an impact on the GDP of about 50 billion dollars.

2.4 Approach

As previously written, biomimicry is widely used inside companies and in the academic field, allowing the development of different approaches and methodologies. At the moment there are two general approaches (Vincent et al, 2006), with different terminologies:

 1st approach: “Challenge to biology” (Baumeister, 2012), “Top-down” (Speck, 2006), “Biomimetics by analogy” (Gebeshuber, 2008), “Problem based” (Vattam, Helms, and Goel 2009), starts from a problem and search the solution in nature.

 2nd approach: “Biology to design” (Baumeister, 2012), “bottom-up” (Speck, 2006),

“Biomimetics by induction” (Gebeshuber, 2008), “Solution based” (Vattam, Helms, and Goel

2009), start from a natural phenomenon and try to apply it into a technological domain. In order to not create confusion, in this work we will call the two approaches “Problem based” and “Solution based”.

2.4.1 Problem based approach

According to Michael E. Helms and Swaroop S. Vattam (2008), we can divide the process in six steps. Each phase influences the others; for this reason, during the process there are feedbacks and continuous changes.

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2.4.1.1 1st phase: Problem definition

In this step, designers are asked to invent or to solve a problem they care to solve. Then they translate the problem in the functional language. Usually this step occurs during all the process after many feedbacks and elaborations.

2.4.1.2 2nd phase: Reframe the problem

The functions defined in the 1st phase have to be elaborated and translated in biological terms. In fact, nature solves problems in different ways than engineering (Bogatyrev and Bogatyreva, 2009); so, to find the solutions in nature is necessary to search functions with biological terms. It is common that designers translate the problem in form of a question to facilitate the comprehension.

2.4.1.3 3th phase: Biological solution search

In this phase the goal for the designers is to find natural phenomena that can satisfy the researched function. The authors analyze four search techniques:

 Change constraints: when the problem is strictly defined is a good practice to delete some constraint to increase the search space.

 Champion adapters: the object of the search is an organism or a system that can survive in the most extreme case of the problem.

 Variation within a solution family: Find organism “families” that have faced and solved the same problem in slightly different ways.

 Multi-functionality: Find organisms or systems with single solutions that solve multiple problems simultaneously.

As a support to this phase there are many tools that we will analyze in the next chapters.

2.4.1.4 4th phase: Define the biological solution

In this phase designers analyze the phenomenon selected in the preview step and try to understand all the parts, structures, behaviors and interactions between all the parts.

2.4.1.5 5th phase: Principle extraction

After having understood the phenomenon, the designers translate the principles in a general form removing as more constraint as possible.

“For example describing the principles of the abalone shell in terms of “interactions between flexible proteins and hexagonal calcium carbonate deposits” may constrain

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structures for resisting impact,” allows for the possibility of using arrangements of many different kinds of flexible and rigid material” (Michael et al, 2008).

2.4.1.6 6th phase: Principle application

The solution is now in a general form so that designers have to adapt it in the technological domain by introducing new constraints and affordances. This transformation usually generates new sub-problems that designers solve using biologically inspired solutions. We classify designs that used multiple biological analogies as compound analogical designs (Vattam et al,2008).

2.4.2 Solution based approach

In this case the process start with the inspiration of a biological model with particular characteristics or potential qualities. The features of the model can be transformed into functional requirements and design parameters to solve some problem and to create new products. For instance, George Mestral in 1940s create Velcro reproducing the features of the natural hook surface of a cocklebur (Benyus, 1997; Pandremenosa et al., 2012). Vattam et al. (2008) and Pandremenosa et al. (2012) propose the following steps to apply this approach:

 1st phase: Biological solution identification;

 2nd phase: Define the biological solution;

 3th phase: Principle extraction;

 4th phase: Reframe the solution;

 5th phase: Problem search;

 6th phase: Problem definition;

 7th phase: Principle application. 2.5 Tools

In this chapter we describe the most important tools available for bio-inspired design. As previously said, there are no proofs about the real utilization of these tools inside companies, so after describing and evaluating them, we will try to understand if and how practitioners use them.

2.5.1 AskNature/ Biomimicry taxonomy

One of the biggest problems that designer face of during the new product development process is facing the linguistic difference between biology, engineering and common

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language (Bar-Cohen, 2006). Sometimes the same concept have different meanings if connected to different domains.

“For example, both a biologist and a civil engineer can talk about ‘‘managing temperature’’ and have a basic understanding of what the other means, whether one of them is talking about an elephant seal managing temperature or the other about the need to regulate temperature in a building”(Deldin and Schuknecht, 2014).

This problem affects all the process, especially the search phase in the “Problem based approach”. In fact in this phase, the designers have to find an organism or a system able to perform a particular function. The problem is even bigger if we think that designer are generally engineers with biology knowledge lack. Janine Benyus and colleagues developed Asknature.org in order to made available biological content as a source of information for non-biologist designers. AskNature is a free database that made available information, abstracts, journal articles, cataloging them by function. Since it was created in 2008, it growth rapidly, recording almost 1.8 million page views in 4 years (Deldin and Schuknecht, 2014). It contained at the beginning 1,300 pages of data selected by trained biologists. It is not a static database: individuals can generate additional content. However all the data must be approved by AskNature content editor in order to maintain a scientific integrity of the data. Once the data are collected, AskNature staff organize them by function. The result is the “Biomimicry Taxonomy”. Strategies are categorized on three levels:

 Group;

 Subgroup;

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For instance if we want to find a solution for a storage problem we have the following result:

Figure 16: AskNature search sample

2.5.2 IdeaInspire

IdeaInspire is a computational tool created by Chakrabarti et al. (2005) as a support for the new product development process, mostly for the generation of novel solutions. It is a database of more than 1,000 entries of biological and technical systems organized using SAPPhIRE model (Goel et al., 2013). The information registered in the database contains details about the structure, the behavior and the function of the described system (Tsujimoto et al., 2008). SAPPhIRE stands for State- Action- Part- Phenomenon- Input- oRgan- Effect. From the lower to the highest level (Srinivasan and Chakrabarti 2009) we can define the parts as:

 Parts: physical elements, interfaces system and environment that constitute the system.

 oRgans: properties and conditions of system and environment required for interaction.

 Effect: principle that governs interaction.

 Phenomenon: interaction between system and its environment.

 Input: physical quantity (material, energy or information) that comes from outside the system boundary, and is essential for interaction.

 State change: change in property of the system (and environment) that is involved in interaction.

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Figure 17: SAPPhIRE model of causality The authors explain how the model operates:

“parts create organs, which with the right input activate an effect; the effect creates a phenomenon, which creates a change of state; the state change with the right premises can be interpreted as an action or input or other state change. The model so far has only been used to explain the causality of natural and engineered systems, i.e., as a model of analysis and has not been explored in detail” (Srinivasan and Chakrabarti, 2009).

As they say in the paper, experiments shown that other researchers and designers found the model complex to understand. As said for AskNature, also IdeaInspire is not a static tool; indeed, the authors stated that they want to expand the database adding new entries, developing new strategies for more complex searches, and assessing the tool with more cases using more designers (Fu et al., 2014).

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In Figure 18 we report the description of a body acceleration on the ground with SAPPHiRE model:

Figure 18: SAPPhIRE model sample

2.5.3 Engineering to biology thesaurus

Functional modeling is a very popular and useful design method in new product development process (Hirtz et al., n.d.). In bio inspired design it allows designers exploring biological domain using an engineering oriented language (Design Computing and Cognition ’12, 2014). In fact, Engineering to Biology thesaurus help designers to find biological meaningful keywords from Functional Basis. After creating a functional model with Functional Basis terms, this tool translate those terms in biological language; afterwards, the research of natural phenomena can be done with other tools, like search engine or AskNature using the keywords suggested. The use of this tool is not restricted to the translation of the terms from one domain to another; rather, it can be used in different phases for different purpose. In their work Nagel et al. (2010), describe its possible applications such as:

 Comprehension: thesaurus “…is thought of as a way of easing communication between texts and users in order to increase the interaction in information retrieval, and thus facilitate information transfer” (López‐huertas, 1997): The information transfer happens through two ways: (1) direct translation of biological texts in engineering language and (2) abstraction of

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 Functional modeling of biological systems: thanks to a wide range of biological terms, the thesaurus allows engineers to choose the best suited function or flow term to model a biological system. Besides describe engineered systems inspired by biological strategies without use biological entities is an additional benefit of this tool.

 Concept generation: using functional modeling to describe biological systems and phenomena allows knowledge that otherwise would not be considered.

 Collaboration, creation and discovery: the terms contained in the engineering to biology thesaurus can help designers to increase the creativity and discover new concepts. Furthermore exploration of biomimetic design can promote the collaboration between biology and engineering researchers because usually an interdisciplinary team is required.

2.5.4 DANE

The Design by Analogy to Nature Engine (Goel et al., 2008) was created at the Design intelligence Lab at the Georgia Institute of Technology. It is a software containing a database with natural and engineering systems organized using the SBF (Structure- Behavior- Function) model (Fu et al., 2014). In the official website (“DANE: Design Analogy to Nature Engine” 2015) the authors identify four primary function of this tool:

 Facilitate biologically inspired design activity: this is the main function of the tool and imply maintaining a database with structured descriptions of natural and engineered phenomena and making them quickly available to designers.

 Cognitive research platform: the use of DANE by designers is useful to the team of cognitive scientists, that created the tool, to better understand the role of structured representation in the context of analogical design and improve it for an easier utilization.

 Augmented intelligence platform: a future goal will be to make the tool intelligent to

understand the designer’s needs and let it act as a collaborative tool during the new product development process.

 Structured representation development: DANE uses SBF model to describe the phenomena and systems. The authors affirm that this format facilitate the comprehension of these phenomena and their transfer into the design domain.

2.5.5 BioTRIZ

BioTRIZ is a methodology based on Altshuller’s Theory of Inventive Problem Solving (TRIZ) (Altshuller, 1999). The most used tool from the TRIZ theory is the contradiction matrix. From the review of around 3 million engineering patents Altshuller (1999) selected 40 principles that solve a common set of engineering conflicts creating a 39x39 matrix. The incidence between a row and a column is a contradiction that can be solved by one or more of the inventive principles founded. Vincent and Bogatyreva et al explain that nature uses different principles to solve the same contradictions identified by Altshuller et al (Wadia, 2011). Therefore, they readapt the matrix reducing the 39 engineering conflicts in 6 operation

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Table 3: PRIZM matrix

The second step of their work was to reorganize the principles inside the matrix to better reflect the way in which nature solves specific contradictions. To do that, the authors analyzed about 500 biological phenomena identifying for each one the contradiction and the solving principles. The readapted PRIZM is the BioTRIZ matrix.

Table 4: BioTRIZ matrix

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abstract to the technical domain. In particular it can be used in the functional modeling: every function can define shapes, behaviors or constraints so when, in the CAD environment, the system is defined we can simulate it.

2.5.7 BioCards

Biocards are inspirational tools created by Torben Lenau, associate professor at the Technical University of Denmark (Lakhtakia, Martín-Palma, and Vogler 2013). They are used to help designers during the idea generation phase and should contain the following information(Ahmed-Kristensen et al., 2014):

 A title which describe the organism and the phenomena;

 A picture or a drawing of the organism;

 A description of the phenomena using biology language;

 A description of the interesting principle applied in the phenomena formulated in functional engineering terms;

 A simplified drawing describing the principle. 2.6 Resume

In literature we can find many methodologies to apply Biomimicry in the NPD process. Whereas they are similar we decided to use a standard one composed by six phases as shown in the graph:

Figure 19: Literature review process

Problem definition Problem reframing Biological solution search Biological solution definition Principle extraction Principle application

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During the process many tools can be used as a support, in particular we have analyzed 7 of them, described in the following table:

Tool Description Phase

AskNature Web based search engine for natural phenomena.

 Problem reframing;

 Biological solution search.

IdeaInspire Software based search and retrieval

of both natural and artificial systems and strategies, founded on SAPPhiRE model (VNA) and/or functional modeling.  Biological solution search;  Biological solution definition. Engineering to biology thesaurus Translation of engineering to biology at a functional level and methodology to employ thesaurus in design process.

 Principle extraction

DANE Database for searching and authoring SBF (Structure-Behavior-Function) design cases/models.

 Problem reframing;

 Biological solution search.

BioTRIZ This tool suggests designers how nature solve contradictions.

 Problem reframing

Knowledge based CAD system

It's a tool that helps engineers to design objects described by SBF or SAPPhIRE model.

 Principle application

BioCards Tools used to communicate design principles found in nature

 Principle extraction;

 Principle application.

Table 5: Tools description

It should be noted that the tools indicated in the table can be used also in other phases but we wanted to underline the main focus of each tool.

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3 SURVEY DEVELOPMENT

3.1 Methodology

During the survey development we adopted the following methodology with the respective phases that we will describe in Table 6:

Process

Activities

Survey design  Strategy planning  Structure planning  Questions drafting  Contents checking

 Questions logic setting

 Statistic checking

 Survey testing

Sample selection  Groups selection

 Channel selection

Data collection  Survey sending

 Survey closing

Table 6: Survey development process

3.1.1 Survey design

To retrieve the data that we needed, we decided to develop this phase in two directions for the reasons that we will explain in the following points. We chose to collect both quantitative and qualitative data:

 Quantitative data

To retrieve quantitative data we chose to use a web survey for its characteristics, in particular we took advantage of the software “Limesurvey” provided by the Polytechnique. Online surveys have a number of positive strength points (Hoffmann and Szolnoki, 2013) such as:

 Time: online surveys allows researchers to reach a big number of people worldwide in a short period (Wright 2006). Thanks to social networks and forums it is also possible to contact people with same interest and common characteristics.

 Cost: all the costs related to material things such as papers, printers, recorders etc. useful for other methods are saved for online surveys. The cost for the software can change from a very small to a thousand dollars depending on the services. In our case, we decided to use an open source software called “Lime survey”.

 Automation: online software contains services unavailable with other methods like visualizing data entry in real time or exporting and translating results in different formats.

 Visual and flexible: instead telephone surveys the interviewed can see the questions and eventual graphic representation, so this foster a better comprehension of the questions

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 Interviewer effects: online surveys do not require interviewers, this means that the interviewed are not influenced by the survey conductor.

However they show weakness points. For example the absence of the interviewer do not make possible eventual clarifications and questions, driving the interviewed to give wrong answers. Furthermore they have a response rate very low compared to the other methods (Bech and Kristensen, 2009).

To avoid these problems we tried to follow the best practices suggested by literature (Umbach, 2004):

1. Making the survey simple with clear questions and explanations; 2. Preferring multiple questions avoiding use of drop down boxes; 3. Dividing the survey into sections;

4. Testing the survey to optimize its length and the necessary time to fill in it.

 Qualitative data

As written above the survey include many weak point. One of this is the percentage of answers related to the length and the number of questions. The more the survey is long the less will be the full answers percentage. This problem drive the interviewer to reduce the number of questions to the detriment of the possible retrieving information. For this reason we thought that another useful way to retrieve more data with higher quality would have been a face to face interview (Doyle 2003). It also allows us to confirm or not the results achieved with the survey.

Starting from the month of December we started to plan the structure of our survey and decide the priority of the information that we wanted to retrieve according with the material found in the literature review phase. Then we wrote the first version of the survey concentrating the biggest number of information in the smallest number of questions. We planned a check point with the tutor after these two phases to review and correct the contents of the survey until when it contained all the information the we planned to have. After that we had a meeting with the statistics expert and the responsible of the project to decide, for each question, the layout and the evaluation scale that was better to use. Afterwards we did a last review before to test the survey on random sample of 5 people to check the duration and the comprehensibility of the survey. The following flow chart shows

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Structure planning

Does the survey conteins all the information we

need? Question drafting Questions logic setting Is the logic

correct? Survey test

Yes Yes

No

Figure 20: Survey development process

3.1.2 Sample selection and data collection

The goal of the research was to retrieve information from biomimicry practitioners so in a first moment our target was composed by designers. In a second moment we thought that we could extend the sample including researchers with at least one year of experience in biomimicry projects.

Usually companies don’t declare to use biomimicry in their NPD process so the first problem was to find a way to know if they used it. For this reason we used a “Top down” approach starting from the case studies: we selected the products developed using biomimicry and we contacted these companies using the e-mails founded in the official web sites. With this strategy we didn’t obtained good results for two reasons:

 Not all the companies provide an e-mail address or employers contact;

 Even if they give the contacts, the response rate using e-mails is very low.

Thus we decided to change strategy, using social networks as channel and contacting directly the interested people. In particular we focus on social networks like Linkedin and Facebook selecting the people from groups specialized in Biomimicry. We tried first to reach people using posts on the groups without good responses. Then we contacted the single person with private messages obtaining an higher response rate. We sent about 500 requests obtaining 102 answers whereof 52 uncompleted and 50 full answers.

The final sample is composed by researchers and designers from all over the world and working mostly in design or consultancy companies.

3.2 The survey

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3.2.1 Biomimetics tools:

This group contains 3 introductive questions regarding the category of the interviewed and their experience. In particular this is a filter question, in fact the interviewed with no experience cannot go head answering the survey. Indeed selecting people from specialized group on social networks gave us only the information regarding their interest on biomimicry, but this question allow us to do a sample skimming. With the third question we introduced the tools subjects of the survey and we ask our interviewed if they know the tools and with which extent. This is another filter question, in fact only who knows the tools can evaluate them in the next groups.

3.2.2 Bio inspired approach:

In this section we describe a standard process composed by 4 phases: 1 Problem definition;

2 Function search; 3 Change domain; 4 Idea generation.

In the literature review we described a methodology composed by 6 phases. Nevertheless we decided to merge the 1st with the 2nd creating the “Problem definition” phase and the 3th with the 4th creating the “Function search” phase, because with 6 phases the survey would have been too long risking to bore the interviewed.

For each phase we ask which of the tools they use, specifying if they use their own or alternative tools and how long the phase lasts.

3.2.3 Approach evaluation:

With 2 questions we ask a comparison between the traditional NPD process and using bio inspiration under 3 aspects:

1 Number of ideas generated; 2 Quality of the ideas;

3 Time needed to solve a problem.

3.2.4 Tools evaluation:

Using the same indicators of a former research we ask to evaluate the tools that they say to know in the first part of the survey. In the former research the evaluation was done

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coming from 2 point of view: supply and demand. If the interviewed said to don’t use the tool we try to understand the reasons asking why they don’t use it.

3.2.5 Company information:

We need these information to understand if there is a correlation between the how designers and researchers use the tools and the field of provenience or the company dimension.

3.2.6 Contacts:

In this last group is possible to leave the contact to receive the final report of the research. However the survey is set in such a way as every question depends on the previews one so the number of the questions is always the same for each interviewed. The time to fill in the survey, tested with five random tester, is about 15/20 minutes.

3.3 The interview

To retrieve qualitative data we decided to use the method of the face to face interview. In this case we had the constraint of the distance, so we needed a Quebecoise company that declared to use biomimicry. Thus we searched the company on the web adding the filter of the distance. The only company that declare on the official website to use biomimicry was the Mawashi.

Mawashi is a leading manufacturer of High Technology Personal Equipment and also a Cutting-Edge Research & Development (R&D) Service Provider.

After contacting them via e-mail we fixed a meeting with the President of the company Alain L. Bujold, Human Factors and Ergonomics specialist with eighteen years of experience in New Product Development (NPD) within the security industry.

During the meeting we tried to retrieve information about:

 Their NPD process integrated with biomimicry;

 What kind of tools they used as a support;

 Comparison between traditional and biomimicry NPD process;

 Storytelling about some case study. 3.4 Results methodology

Bio inspired design: how do designers use tools in new product development process?

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Bio Inspired Design: How do designers use biomimicry tools during new

product development process?

Bio inspired design: how do designers use biomimicry tools during

new product development process

CONTENTS

LIST OF TABLES

1. INTRODUCTION

2 LITERATURE REVIEW

General

Biomimicry

Methodologies

Tools

Definitions

Case

studies

Problem

based

approach

Solution

based

approach

AskNature

IdeaInspire

Engineering

to biology

thesaurus

DANE

BioTRIZ

BioCards

Knowledge

based CAD

system

Publications

3 SURVEY DEVELOPMENT

Process

Activities