1. Engineering & Models:Real Engineers Use More than Just Equations David E. GoldbergIllinois Foundry for Innovation in Engineering Education University of Illinois at Urbana-ChampaignUrbana, Illinois 61801 USAdeg@illinois.edu © David E. Goldberg 2010

3. Implies: Meaningful models come from math & science alone.

4. Young engineers confused on first jobs.

5. 2 problems:

6. Don’t use appropriate models.

7. Don’t think they’re doing engineering.

8. Need better understanding of types & breadth of engineering modeling. © David E. Goldberg 2010

9. Roadmap What is a model? Legacy of Newton: equations versus words & images. Matching models to problems. What are models used for. Tech visionaries as broad spectrum modelers. Toulmin’s model of arguments as unifying approach. Return to flour physics. © David E. Goldberg 2010

11. Typical model  facet combinations:

12. Drawing or solid model  geometry.

13. Prototype  geometry & operation.

14. Graph  variation of variable with independent variable(s) (time, space, etc.).

15. Equilibrium equation  select state variables at steady state.

16. Dynamic equation  variation of select state variables with time.

17. Computer simulation  similar to equations.© David E. Goldberg 2010

19. Study of knowledge: Epistemology.

20. Study of existence: Ontology.

21. What engineers know and how they know it?

22. Walter Vincenti’sbook takes examples from aeronautical history.

23. Discusses distinctions between engineering knowledge and scientific-mathematical knowledge.© David E. Goldberg 2010

25. In 1687 published Philosophiae Naturalis Principia Mathematica.

26. Changed world.

27. Remarkable agreement between equations & measurements.

28. Many engineering models use his equations (F=ma) directly.

29. Represents an ideal of scientific knowledge that others attempt to emulate.

30. Highest status accorded to those who use these kinds of models.

31. Does status = efficacy?Sir Isaac Newton (1643-1727) © David E. Goldberg 2010

33. Engineers often use natural language in modeling.

34. Many first models are verbal.

35. Types of verbal models:

36. Single word or noun phrase.

37. Description of an object/process.

38. Feature list.

39. Dimension list.

40. Set of engineering specifications, standards, or claims.© David E. Goldberg 2010

41. Images and Engineering Modeling History of drawings and visual representations of engineered objects is long. Downgrading of engineering visualization and drawing since Cold War. Ferguson’s book argues this was/is educational mistake. © David E. Goldberg 2010

42. Connection to the Napkin Diagrams can be models. Drawings can be models. The Back of the Napkin connects visual thinking and verbal thinking in important way. © David E. Goldberg 2010

43. How to Match Models to Engin Problems What characterizes an appropriate model in engineering? What do you think? Take out a piece of paper and write down 3 attributes that suggest you have a good model. 2 minutes. © David E. Goldberg 2010

45. Have many models with different precision-accuracy and different costs.

46. Can we distinguish appropriate engineering model usage from that of scientist?

47. The economics of modeling.

48. Engineers use models in economic context  model usage must support objectives within available resources.© David E. Goldberg 2010

49. Fundamental Modeling Tradeoff Engineer/Inventor ε, Error Scientist/Mathematician C, Cost of Modeling Error versus cost of modeling © David E. Goldberg 2010

50. Spectrum of Models © David E. Goldberg 2010

51. What Are Models Good For? Many uses for models: Description: describe the ways things are (were). Prediction: describe the ways things will be. Prescription: describe the way things should be. Key variables: time and change. Usually assumes have extant object to model. © David E. Goldberg 2010

53. Price, Vojak, & Griffin have done work on tech visionaries (TVs).

54. TV creates bottom line revenue from new products & services.

55. TVs are consummate broad-spectrum modelers.

56. Use qualitative-quantitative models as necessary to bring monster products/services to market.Ray Price © David E. Goldberg 2010

58. To model imagined or desired objects, what can we draw upon?

59. Existing objects that fail in some regard.

60. Similar or related objects.

61. Analogically related objects.

62. Creatively concocted objects.

63. Problem of the tabula rasa: How to model that which does not exist.

64. In category creation, more modeling will be to the left (qualitative versus quantitative).

65. Category enhancement: improvements require more precision. More modeling to the right (quant over qual).© David E. Goldberg 2010

67. Newton’s laws?

68. Need framework to tie different models together.Back to the Tortilla Factory © David E. Goldberg 2010

70. How do people really make arguments?

71. How do people give reasons for what they think or do?

72. Form of reasoning ties together formal and informal engineering reasoning.© David E. Goldberg 2010

74. if pthen q

75. pis true

76. thereforeqis true

77. Method of mathematical logic & formal reasoning.

78. Note: Once premises and rules in place, formal logic derives conclusions mechanistically.Aristotle (384-322 BCE) © David E. Goldberg 2010

80. Claim. A single statement advanced for the adherence of others.

81. Grounds. A statement about persons, conditions, events, or things that says support is available to provide a reason for a claim.

82. Warrant. A general statement that justifies using the grounds as a basis for the claim

83. Backing. Any support (specific instance, statistics, testimony, values, or credibility) that provides more specific data for the grounds or warrant.

84. Qualifier. A statement that indicates the force of the argument (words such as certainly, possibly, probably, usually, or somewhat).

85. Warrants can be generalizations, cause, sign, analogy, authority.

86. Backing can be anecdote, stats, testimony, credibility, and values.Rieke, R. D & Sillars, M. O. (1997). Argumentation and critical decision making. New York: Longman. © David E. Goldberg 2010

87. Back to the Tortillas: Burnt Flour Model Grounds. Dusting flour is spread onto the moving dough on a continuous tortilla line. Claim. Burnt black flour deposits is mistaken for mold, resulting in quality complaints Warrant. Excess flour can become airborne and burn in the oven, deposit on tortilla. Qualifier. Sometimes Backing. Client story & increased flour results in increased spot problem. © David E. Goldberg 2010

89. Should you improve warrant and backing?

90. Or should you work on solving the problem?

91. Difficult choice: If you assume correctness of warrant/backing & you are wrong, will it prevent you from solving problem.

92. In tortilla problem students took explanation as true because it didn’t affect investigation.© David E. Goldberg 2010

93. Summary Engineering students are convinced that math and physics are the main (only?) tools of engineering. Real engineers use a spectrum of models from qualitative to quantitative. Economy of modeling separates engineering from scientific practice. Toulmin’s model of arguments introduced & example from flour physics given. © David E. Goldberg 2010

94. Bottom Line Modeling is critical engineering activity, but don’t let emphasis on math-science mislead you. Great engineers and tech visionaries are broad-spectrum modelers. Use simplest models that will advance design objectives (economy of modeling). Unify models by using Toulmin’s model of arguments & use explicitly to tradeoff model improvement vs. design. © David E. Goldberg 2010

95. Engineering & Models:Real Engineers Use More than Just Equations David E. GoldbergIllinois Foundry for Innovation in Engineering Education University of Illinois at Urbana-ChampaignUrbana, Illinois 61801 USAdeg@illinois.edu © David E. Goldberg 2010