Introduction to Innovative Design Thinking

1. 1 Introduction to Innovative Design Thinking CDI

2. 2 Lecture 4 Concept of Fuzzy Logic Lateral thinking Six Thinking Hats Problem Identification

3. 3 Fuzzy Logic Fuzzy logic is a notion introduced by Lotfi Zadeh, a Russian professor in 1964.

4. 4 Fuzzy Logic It is a notion of uncertainty. Unlike logical thinking in a dialectic deduction or induction pattern, fuzzy logic aims at investigating the Class � categories.

5. 5 Fuzzy Logic Fuzzy logic is a superset of conventional (Boolean) logic that has been extended to handle the concept of partial truth -- truth values between"completely true" and "completely false".

6. 6 Fuzzy Logic The process of �fuzzification� as a methodology to generalize ANY specific theory from a crisp (discrete) to a continuous(fuzzy) form. Thus recently researchers have also introduced "fuzzy calculus", "fuzzy differential equations",and so on .

7. 7 Fuzzy Logic Fuzzy logic depends on the degree of �truth�. The issue studying can be categorized into mathematical calculation and classify the in-between differences in the degree of �truth� and �fact�.

8. 8 Fuzzy Logic

9. 9 Fuzzy Logic

10. 10 Fuzzy Logic

11. 11 Fuzzy Logic In classical set theory, a subset U of a set S can be defined as a mapping from the elements of S to the elements of the set {0,1}, U: S --> {0, 1}

12. 12 Fuzzy Logic This mapping may be represented as a set of ordered pairs, with exactly one ordered pair present for each element of S. The first element of the ordered pair is an element of the set S, and the second element is an element of the set {0, 1}.

13. 13 Fuzzy Logic The value zero is used to represent non-membership, and the value one is used to represent membership. The truth or falsity of the statement x is in U is determined by finding the ordered pair whose first element is x.

14. 14 Fuzzy Logic The statement is true if the second element of the ordered pair is 1, and the statement is false if it is 0.

15. 15 Fuzzy Logic Similarly, a fuzzy subset F of a set S can be defined as a set of ordered pairs, each with the first element from S, and the second element from the interval [0,1], with exactly one ordered pair present for each element of S

16. 16 Fuzzy Logic This defines a mapping between elements of the set S and values in the interval [0,1]. The value zero is used to represent complete non-membership, the value one is used to represent complete membership, and values in between are used to represent intermediate DEGREES OF MEMBERSHIP.

17. 17 Fuzzy Logic The set S is referred to as the UNIVERSE OF DISCOURSE for the fuzzy subset F. Frequently, the mapping is described as a function, the MEMBERSHIP FUNCTION of F. The degree to which the statement x is in F is true is determined by finding the ordered pair whose first element is x.

18. 18 Fuzzy Logic The DEGREE OF TRUTH of the statement is the second element of the ordered pair. In practice, the terms "membership function" and fuzzy subset get used interchangeably.

19. 19 Fuzzy Logic Let's talk about people and "tallness". In this case the set S (the universe of discourse) is the set of people. Let's define a fuzzy subset TALL, which will answer the question "to what degree is person x tall?"

20. 20 Fuzzy Logic TALL as a LINGUISTIC VARIABLE, which represents our cognitive category of "tallness". To each person in the universe of discourse, we have to assign a degree of membership in the fuzzy subset TALL.

21. 21 Fuzzy Logic The easiest way to do this is with a membership function based on the person's height. Tall(x) = { 0, if height(x) < 5 ft., (height(x)-5ft.)/2ft., if 5 ft. <= height (x) <= 7 ft., 1, if height(x) > 7 ft. }

22. 22 Fuzzy Logic We can draw a graph like this:

23. 23 Fuzzy Logic Given this definition, here are some example values:� Person Height degree of tallness Billy 3' 2" 0.00 [I think] Yoke 5' 5" 0.21 Drew 5' 9" 0.38 Erik 5' 10" 0.42 Mark 6' 1" 0.54 Kareem 7' 2" 1.00 [depends on who you ask]

24. 24 Fuzzy Logic Expressions like "A is X" can be interpreted as degrees of truth, e.g., "Drew is TALL" = 0.38.

25. 25 Fuzzy Logic The standard definitions in fuzzy logic are:� truth (not x) = 1.0 - truth (x) truth (x and y) = minimum (truth(x), truth(y)) truth (x or y) = maximum (truth(x), truth(y))

26. 26 Fuzzy Logic This is a very commonly used mathematical calculation in developing artificial intelligence. The power of fuzzy logic depends on the ambiguity of the language.

27. 27 Fuzzy Logic Hence, beyond profound calculation, we can make use of the concept to build up a fuzzy map, helping us to see the vague argument more clearly and thoroughly.

28. 28 My true story: When I was studying design �� If you were me, what would you do in order to get back the pen??? Lateral Thinking

29. 29 As you can see, logical thinking sometimes does not help in problem solving. You have to find another way out. Lateral Thinking

30. 30 Lateral thinking is a method introduced by Dr. Edward De Bono. Lateral Thinking

31. 31 It is also known as Horizontal thinking. This method is totally different from the traditional logical thinking � Vertical thinking. Lateral Thinking

32. 32 Lateral Thinking

33. 33 Lateral Thinking

34. 34 Lateral Thinking

35. 35 Lateral Thinking

36. 36 Lateral Thinking

37. 37 Lateral Thinking

38. 38 Lateral Thinking

39. 39 There are no fixed rules in lateral thinking. Hence, there are some points to note to arouse creativity. Lateral Thinking

40. 40 Encourage intuition. Allows crazy ideas. Simple is the best. Make use of possibilities. Treasure coincident. Lateral Thinking

41. 41 An interesting question before you go: Why 7 + 6 equal to 10 ? Lateral Thinking

42. 42 References Lateral Thinking, Edward de Bono, 1985

43. 43 Six Thinking Hats This is a thinking method introduced by Dr. Edward De Bono. It depends highly on role-playing technique.

44. 44 There are six different coloured thinking hats, which are White, Red, Black, Yellow, Green and Blue. Six Thinking Hats

45. 45 Six Thinking Hats

46. 46 White Hat: Collecting Data and Facts No interpretation and no personal opinion Six Thinking Hats

47. 47 Red Hat: Expression of one�s emotion and feeling. No need to elaborate the reasons behind. Six Thinking Hats

48. 48 Black Hat: Collecting all negative comments. It helps to build up the negative design criteria. Six Thinking Hats

49. 49 Yellow Hat: Optimistic opinions with reasons. Constructive ideas with logical thinking Six Thinking Hats

50. 50 Green Hat: Creative ideas under lateral thinking. Select the appropriate solution and skill. Six Thinking Hats

51. 51 Blue Hat: Drafting of design statement and criteria. Control and monitor the creative thinking process. Six Thinking Hats

52. 52 It is very important that you know the role of each hat. When conducting six thinking hats method in lesson, students can require others to wear or change their hats during the discussion. Six Thinking Hats

53. 53 It is also important that throughout the discussion, students ( and teachers ) should understand thoroughly the use of each hat and its limitation. Six Thinking Hats

54. 54 Six Thinking Hats

55. 55 Six Thinking Hats

56. 56 Six Thinking Hats

57. 57 Six Thinking Hats

58. 58 Six Thinking Hats

59. 59 After sorted out all the possibilities, we have to map out all of them and select the best solutions. It relies on the deduction of concept map to see the relationship between each proposal, and logic to execute the ideas. Six Thinking Hats

60. 60 Are you ready? Remember, play the role when you wear specific hat!!! Let us try this out. Any subject matter you would like to study or solve? Six Thinking Hats

61. 61 As you may see in the activities, the six thinking hats depends on the participation of role playing and it may works out lots of possibilities out of your imagination. Six Thinking Hats

62. 62 Six Thinking Hats It can be a very powerful tool when you encounter a specific problems and can pretended to be an outsider to scrutinize the subject matter that you are working at.

63. 63 Six Thinking Hats That is why lateral thinking and Six hats thinking method are also known as �Serious thinking� methodology.

64. 64 References Six thinking hats, Edward De Bono, 1988

65. 65 Words can help us to think, question, criticize and analysis a problem. Problem Identification

66. 66 Brief for HKCE D&T design project 2001: A restaurant menu holder can help promote food item. To design a restaurant menu holder for a selected restaurant. Problem Identification

67. 67 How can you guide students to build up their own mind set in designing the product under such �smartly� drafted design brief? Problem Identification

68. 68 Mind mapping, concept map, linguistic analysis and logic can help them to identify a problem and set up new design criteria. Problem Identification

69. 69 The way to identify a problem is first of all understand your position, i.e. What is your role play. Problem Identification

70. 70 You have to decipher the problem(s) behind the stated problem instead of the mentioned statement itself. Problem Identification

71. 71 Under careful examination, the problem can be elaborated by various means. Problem Identification

72. 72 Logical thinking Linguistic analysis Mind map and concept map Questioning Interpretation Semiotic �����.. Problem Identification

73. 73 Demonstration: Is there any problem you would like me trying to identify? Problem Identification

74. 74 Thank You