1.1. Introduction

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1.1. Introduction

• 1. Fundamentals
• CEIE 411 Introduction to Design and Inventive
  Engineering
• Tomasz Arciszewski
• Spring, 2009

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Instructor

• Formal background structural mechanics and
  engineering
• Teaching structural analysis and design, IT,
  design science
• Research interests in
• Evolutionary designing
• Inventive designing
• Bio-inspiration in design
• Engineering education
• Design experience
• analysis and design of bridges and residential
  structures (Switzerland)
• analysis and design of large span roof space
  structures (Poland)
• Inventor with patents in three countries (Canada,
  Poland, USA)
• Certificate Program Discovery, Design, and
  Innovation

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This course is for you if

• You are willing to change your attitudes and
  reexamine your preconceptions
• You have positive attitude to learning and can
  accept out of the box concepts and thinking
• You want to improve your understanding of the
  design science
• You want to improve your creative problem solving
  skills
• You believe in the importance of
  transdisciplinary science and holistic approaches
• You want to become successful a leader and an
  inventor

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The course is NOT for you if

• You hate crazy interdisciplinary stuff
• You are looking only for formal models, methods,
  and theories
• You are interested only in the formal
  deterministic procedures (a follower)
• You are unable to accept inconsistencies
• You are unable to accept incomplete knowledge

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Mission

• Learn fundamentals of Design and Inventive
  Engineering
• Improve your holistic understanding of the design
  and problem solving processes
• Improve your ability to act outside the
  analytical box while designing and problem
  solving
• Change our attitude from quantitative to
  qualitative (Da Vincian spirit)
• Become a more creative civil engineer
• Become a successful civil engineer

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Memento Mori
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• Fairy Tale

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History

• Early eighties, an Igbo engineer in Nigeria, Kalu
  Uduma, is dreaming about becoming a professor
• Mid-eighties, graduate studies at Wayne State
  University
• reluctant participation in a structural
  optimization class dealing with inventive problem
  solving
• specialization in finite elements analysis
• Early nineties, crash engineering job at Chrysler
  Technology Center

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Challenge

• New LH cars failed side crash tests (Spring of
  1997)
• Kalu was given the task to redesign the B-pillar
• He was terrified and suspects sinister reasons of
  his assignment
• He had no choice, but to start thinking
• He recalled his lectures on inventive design
• He applied Brainstorming and Morphological
  Analysis

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LH Cars
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Finite Element Model
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Finite Element Model
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Results

• Kalu discovered that problem had been initially
  improperly formulated
• He produced several design concepts gradually
  evolved to the final design concept
• LH cars passed side crash tests
• New design saved several hundred dollars per car
• Kalu became a corporate hero and applies for a
  patent
• New LH cars were finally introduced

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Fairly Tale Conclusions

• There is a need for inventive designing
• It works, but three conditions must be
  satisfied
• - Motivation
• - Domain knowledge
• - Inventive design knowledge and skills
• Inventive designing exists in practice, but it is
  not widely taught and does not formally exist as
  a science

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Mission

• To learn transdisciplinary understanding of
  engineering design and creativity

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• Transdisciplinarity

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Complex World

• System families
• Systems of systems
• Critical importance of integration
• Required integrative knowledge, or
  transdisciplinary knowledge

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Knowledge evolution

• Rapidly growing body of knowledge
• Increasing specialization of knowledge leading to
  fragmentation
• Emerging spheres of knowledge with limited
  overlap
• Example from economics of natural resources
• Natural resources economics
• Environmental economics
• Ecological economics
• Bionomics

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Knowledge Evolution

• TRIZ and Directed Evolution
• Increased complexity then simplification
  evolution pattern
• Example quartz watches,
• very simple digital watches
• multifunctional complex analog-digital watches
• simple analog single-function watches
• Division followed by integration
• Disciplinary knowledge followed by
  transdisciplinary knowledge

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Contradictions and solutions

• Contradictions
• Knowledge depth versus breath
• Specialization versus generalization (and
  abstraction)
• Disciplinary versus transdisciplinary knowledge
• Knowledge soup versus transdisciplinary
  knowledge
• Solutions
• Synthesize together relevant knowledge from
  different disciplines to integrate this knowledge
• Develop a knowledge acquisition process producing
  transdisciplinary knowledge

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Fusion versus transdisciplinarity

• Fusion
• mixing knowledge from various disciplines to
  create a knowledge soup
• Transdisciplinarity
• integrating knowledge from various disciplines to
  create the unity of knowledge, or
  transdisciplinary knowledge

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ITE Example

• ITE School established in 1984 by Andrew Sage, a
  visionary and transdisciplinary scholar
• Schools mission was to create transdisciplinary
  knowledge integrating IT and engineering
• First integrative Ph.D. Program in Information
  Technology open to both engineers and IT workers

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Transdisciplinarity

• It is a knowledge acquisition process from
  multiple disciplines, which through
  transformation, restructuring and integration
  produces transdiciplinary knowledge
• Acquiring knowledge from multiple perspectives to
  produce a new holistic (multidemensional/systems)
  perspective

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Transdisciplinary knowledge

• Product of transdisciplinarity
• Represents a synthesis of knowledge from several
  disciplines
• Intellectual basis for
• Systems engineering
• Design and inventive engineering

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Design and Inventive Engineering

• A transdisciplinary discipline
• Main contributing disciplines
• Engineering
• Cybernetics
• Systemics (systems science)
• Systems Engineering
• Heuristics
• Artificial Intelligence
• Computer Science
• Psychology

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Design and Inventive Engineering

• Transdisciplinary engineering science
• Example Engineering Creativity is considered
  from three perspectives
• Society (Creative Class)
• Community (the Medici Effect)
• A man (the Renaissance Man)
• Objective to create transdisciplinary
  understanding of engineering design and creativity

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Transdisciplinarity Conclusions

• Natural evolution of science
• Emerging paradigm
• New understanding of science and technology
• Source of creativity
• Incredible potential to accelerate progress in
  science and technology
• Key to understanding Design and Inventive
  Engineering

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Successful Intelligence

• ity

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Theory of Successful Intelligence

• Proposed by Robert J. Sternberg in 1990s
• It is defined as a human ability to achieve life
  success

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Successful intelligence

• A combination of four major abilities
• to be successful
• to succeed using a balance of practical,
  analytical, and creative abilities
• to maximize somebodys strengths and to
  compensate for weaknesses
• to balance various abilities in order to adapt
  to shape, and to select environments

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Success

• A professional position, a social position
• Realization of dreams
• Fame and fortune
• A relative concept of ones personal standards
  within ones socio-cultural background

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Assumptions

• Successful intelligence is dynamic
• It can be learned
• It is a combination of 3 abilities
• Practical intelligence
• Analytical intelligence
• Creative intelligence

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Assumptions

• Intelligent abilities can be learned
  independently
• A balance of all three abilities is absolutely
  necessary for success

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Rote Learning Reasoning

• Rote Learning memorization of facts and
  procedures
• Deduction reasoning in which existing knowledge
  (BK) is used to verify a hypothesis
• Induction reasoning in which BK and knowledge in
  the form of examples is used to verify a
  hypothesis
• Abduction reasoning in which BK and knowledge in
  the form of examples is used to produce a
  hypothesis

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Practical intelligence

• An ability to solve simple everyday problems
• Product of rote learning of facts and heuristics
• Traditional learning in arts

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Analytical intelligence

• An ability to solve in real world routine
  analytical problems using mostly deduction
• Product of rote learning and learning deductive
  skills
• Traditional learning in science

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Creative Intelligence

• An ability to solve in real world non-routine
  (creative) problems using both abduction and
  induction
• Product of rote learning and learning deductive,
  inductive and abductive skills

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IQ versus Successful Intelligence

• IQ
• Measures ability to solve abstract problems
• Very weak correlation to professional success
• Static
• Cannot be learned
• Successful intelligence
• Represents ability to succeed in life
• Very strong correlation to success
• Dynamic
• Can be learned

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Advantage

• Knowing about successful intelligence changes
  your attitude
• Learning the creative intelligence helps you to
  advance your career and to become a leader and an
  inventor

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• Intelligence and styles

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Style of thinking

• It is a preferred way of thinking
• It is a methodological body of knowledge of a
  given individual
• A collection of methodical rules and heuristics
• 96 types of styles plus combinations

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Styles
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Functions

• A human is like a democratic society with
  legislative, executive, and judicial branches
• Legislative style generation of ideas, creative
  intelligence
• Executive style implementation of ideas,
  practical intelligence
• Judicial style judging implemented ideas,
  analytical intelligence

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Forms

• Monarchic 100 focus on a single goal
• Hierarchic dealing with a hierarchy of goals,
  focus on organization
• Oligarchic focus on several competing goals
• Anarchic no focus at all, many randomly selected
  competing goals

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Levels

• Global focus on a big (holistic) picture
• Local focus on details

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Scope

• Internal internal source of ideas, usually an
  introvert
• External external source of ideas, usually an
  extrovert

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Leanings

• Focused on risk aversivenness
• Liberal risk affinitive
• Conservative risk aversive

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Comments

• Thinking styles are poorly understood in
  engineering
• Thinking styles and attitudes have to be
  investigated
• More questions than answers
• Be simply aware of their existence
• Look at various methods from the perspective of
  your style

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• COURSE
• ORGANIZATION

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Major Parts

• Fundamentals (5 lectures)
• Inventive Engineering (4 lectures)
• Design Engineering (4 lectures)
• Contemporary Issues (1 lecture)
• Team Presentations (1 lecture)

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Invited Speakers

• Professor John Gero, University of Sydney,
  Australia.
• Dr. Rafal Kicinger, Metron Aviation, Inc.
• 3. Dr. Kalu Uduma, Chrysler Corporation, Inc.
• 4. Dr. Paul Seguin, US Army Corps of Engineers

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Projects

• Two team projects
• Potential areas
• Structural engineering (Dr. P. Sequin)
• Environmental engineering/land development (Mr.
  J. Matusik)
• Transportation engineering/safety (Dr. M.
  Bronzini, Dr. K. Uduma)