Abstract
Engineers interact with their products and processes largely through models, however rarely reflect about the nature of these models and how technical possibilities and actions are affected by the models’ properties and characteristics. Models in engineering describe the product as well as its generating process, but at the same time also shape and create them. This clearly distinguishes them from scientific models that primarily aim to describe a certain target system. While over the last decade, there has been a growing body of literature on models in the sciences, much less research has been done on models in engineering design. In this chapter we aim to fill this gap by taking a closer look at models in engineering design from an epistemic point of view. In particular we suggest a classification of different types of models used in engineering design and compare them to models used in scientific research. Thereby we do not aim at an encompassing map of models in engineering practice, but we aim to identify key categories of models with regards to their relationship to their targets. We contend that the functions of models in engineering design cannot be fully captured when focusing on the representative aspects of models alone as done in contemporary philosophy of science.
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Notes
- 1.
The philosophical literature does not dwell on the details of modelling the scientific practice. Scientific processes are discussed today rather in the context of the sociological study of science and technology. An example provides the actor-network theory that originally aims to describe processes of innovation and knowledge-creation in science and technology (e.g. Latour 1987). Psychological studies of scientific processes, e.g. Dunbar (1997) has been picked up in the artificial intelligence literature and in creativity research (e.g. Sawyer 2011; Holyoak and Thagard 1997).
- 2.
Notwithstanding its name, the standard model is often seen also as a theory. We will briefly turn to the intricate relationship between model and theories in the following section
- 3.
However this example also shows that in practice it is often unrealistic to assume that (at least the basic) structure remains unspecified, as no car company begins this process without knowing what type of car they will build
- 4.
Models of requirements can be thought of as part of the design models, however as they are often provided by customers or other teams outside the design organisation they are treated as external.
References
Bailer-Jones, D. M. (2003). When scientific models represent. International Studies in the Philosophy of Science, 17(1), 59–74.
Browning, T. R., & Ramasesh, R. V. (2007). A survey of activity network-based process models for managing product development projects. Production and Operations Management, 16, 217–240.
Bucciarelli, L. L. (1994). Designing engineers. MIT press.
Cartwright, N. (1999). The dappled world: A study of the boundaries of science. Cambridge University Press.
Chakravartty, A. (2010). Informational versus functional theories of scientific representation. Synthese, 172(2), 197–213.
Duhem, P. (1954). The aim and structure of physical theory. Princeton: Princeton University Press.
Dunbar, K. (1997). How scientists think: On-line creativity and conceptual change in science. Creative thought: An investigation of conceptual structures and processes, 4.
Eckert, C. (2013). That which is not form: The practical challenges in using functional concepts in design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 27(03), 217–231.
Eckert, C., Clarkson, P. J., & Zanker, W. (2004). Change and customisation in complex engineering domains. Research in Engineering Design, 15(1), 1–21.
Eckert, C. M., & Clarkson, P. J. (2010). Planning development processes for complex products. Research in Engineering Design, 21(3), 153–171.
Eckert, C. M., Stacey, M., & Earl, C. (2005). References to past designs. Studying designers, 5(2005), 3–21.
Eckert, C. M., & Stacey, M. K. (2010). What is a process model? Reflections on the epistemology of design process models. In Modelling and Management of Engineering Processes (pp. 3–14). London: Springer.
Eger, T., Eckert, C., Clarkson, P. J. (2005). The role of design freeze in product development. In DS 35: Proceedings ICED 05, the 15th International conference on engineering design, Melbourne, Australia, 15.-18.08. 2005.
Eppinger, S. D., Ulrich, K. T. (1995). Product design and development. 1995.
van Fraassen, B. (1980). The scientific image. Oxford: Clarendon Press.
Ferguson, E. S. (1994). Engineering and the Mind's eye. MIT press.
French, M. J. (1999). Conceptual design for engineers. Springer.
Frigg, R. (2010). Fiction in science. In J. Woods (Ed.), Fictions and models: New essays (pp. 247–287). Munich: Philosophia.
Frigg, R. and Hartmann, S., 2012 “Models in science”, The stanford encyclopedia of philosophy (Fall 2012 Edition), Edward N. Zalta (ed.), http://plato.stanford.edu/archives/fall2012/entries/models-science/
Galle, P. (1999). Design as intentional action: A conceptual analysis. Design Studies, 20(1), 57–81.
Gero, J. S., & Kannengiesser, U. (2004). The situated function-behaviour-structure framework. Design Studies, 25, 373–391.
Giere, R. (1988). Explaining science: A cognitive approach. Chicago: University of Chicago Press.
Grauer, R., Marliani, C., & Germaschewski, K. (1998). Adaptive mesh refinement for singular solutions of the incompressible Euler equations. Physical Review Letters, 80(19), 4177.
Goel, A. K., Rugaber, S., & Vattam, S. (2009). Structure, behavior, and function of complex systems: The structure, behavior, and function modeling language. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 23(01), 23–35.
Hartmann, S. (1996). The world as a process. In: R. Hegselmann u. a. (eds.): Modelling and simulation in the social sciences from the philosophy of science point of view (pp. 77–100), Dordrecht.
Hesse, M. (1963). Models and analogies in science. London: Sheed and Ward.
Hillerbrand, R. (2012). Order out of chaos? A case study in High Energy Physics. Studia Philosophica Estonica, 5(2), 61–78.
Hillerbrand, R. (2015). Explanation via micro-reduction: On the role of scale separation for quantitative modelling. In B. Falkenburg & M. Morrison (Eds.), Why more is different – philosophical issues in condensed matter physics and complex systems (pp. 69–87). Berlin Heidelberg: Springer.
Holyoak, K. J., & Thagard, P. (1997). The analogical mind. American Psychologist, 52(1), 35.
Hughes, R. I. G. (1999). The sing model, computer simulations and universal physics. In M. Morgan & M. Morrison (Eds.), Models as mediators: Perspectives on natural and social science (pp. 97–145). Cambridge: Cambridge University Press.
Humphreys, P. (1991). “Computer simulations”, In: A. Fine, M. Forbes & L. Wessels (eds.), PSA 1990, Vorl. 2, 497–506, East Lansing.
Klein, E. E., & Herskovitz, P. J. (2005). Philosophical foundations of computer simulation validation. Simulation & Gaming, 36(3), 303–329.
Kosslyn, S. (1994). Image and brain. Cambridge, MA: MIT Press.
Küppers, G., & Lenhard, J. (2005). Validation of simulation: Patterns in the social and natural sciences. Journal of artificial societies and social simulation, 8(4).
Latour, B. (1987). Science in action: How to follow scientists and engineers through society. Harvard university press.
Mayo, D. G. (1996). Error and the growth of experimental knowledge. University of Chicago Press.
Morgan, M. S., & Morrison, M. (1999). Models as mediators. Perspectives on natural and social science. Cambridge: Cambridge University Press.
Morrison, M. (1999). Models as autonomous agents. In M. Morgan & M. Morrison (Eds.), Models as mediators (pp. 38–65). Cambridge: Cambridge University Press.
Morrison, M. (2009). Models, measurement and computer simulation: The changing face of experimentation? Philos. Stud, 143, 33–57.
Pahl, G., Beitz, W. (1996). Engineering design: A systematic approach (edited by Ken Wallace and translated by Ken Wallace, Lucienne Blessing, and Frank Bauert).
Parker, W. S. (2009). Does matter really matter? Computer simulations, experiments, and materiality. Synthese, 169(3), 483–496.
Pidd, M. (1999). Just modeling through: A rough guide to modeling. Interfaces, 29(2), 118–132.
Poznic, M. (2016). Modeling organs with organs on chips: Scientific representation and engineering design as modeling relations. Philosophy and Technology, 29(4), 357–371.
Sargent, R. G. (2005, December). Verification and validation of simulation models. In Proceedings of the 37th conference on Winter simulation .Winter simulation conference. pp. 130–143.
Sawyer, R. K. (2011). Explaining creativity: The science of human innovation. Oxford University Press.
Schön, D. A. (1984). The reflective practitioner: How professionals think in action (Vol. 5126). New York: Basic books.
Searle, J. (1983). Intentionality. An essay in the philosophy of mind. Cambridge: Cambridge University Press.
Stacey, M., & Eckert, C. (2003). Against ambiguity. Computer Supported Cooperative Work (CSCW), 12(2), 153–183.
Stiny, G. (1980). Introduction to shape and shape grammars. Environment and planning B, 7(3), 343–351.
Suárez, M. (1999). Theories, models, and representations. In Model-based reasoning in scientific discovery springer US (pp. 75–83).
Suppe, F. (1977). The structure of scientific theories. Chicago: University of Chicago Press.
Suppes, P. (1961). A comparison of the meaning and use of models in mathematical and empirical sciences. In H. Freudenthal (Ed.), The concept ad role of the models in mathematics and natural and social sciences (pp. 163–177). Dordrecht: Reidel.
Suppes, P. (1962). Models of data. In E Nagel, P. Suppes and A. Tarski (eds.): Logic, methodology and philosophy of science: Proceeding of the 1960 International Congress. Stanford, CA. Stanford University Press, pp 252–261.
Umeda, Y., Ishii, M., Yoshioka, M., Shimomura, Y., & Tomiyama, T. (1996). Supporting conceptual design based on the function-behavior-state modeller. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 10, 275–288.
Tahera, K., Earl, C., & Claudia, E. (2014). Integrating virtual and physical testing to accelerate the engineering product development process. International Journal of Information Technology and Management 9, 13(2–3), 154–175.
Tolk, A., Turnitsa, C. (2012, December). Conceptual modeling with processes. In Proceedings of the 2012 Winter Simulation Conference (WSC)(pp. 1–13). IEEE.
Tolk, A. (2012). Truth, trust, and Turing – Implications for Modeling and simulation. In A. Tolk (Ed.), Ontology, epistemology, and teleology for Modeling and simulation (pp. 1–26). Berlin: Springer Berlin Heidelberg.
Vermaas, P. E. (2013). The coexistence of engineering meanings of function: Four responses and their methodological implications. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 27(03), 191–202.
Visser, W. (2006). The cognitive artifacts of designing (p. 264). Lawrence Erlbaum Associates.
Weisberg, M. (2013). Simulation and similarity. Using models to understand the world. New York: University Press.
Wynn, D. C. (2007). Model-based approaches to support process improvement in complex product development (Doctoral dissertation, University of Cambridge).
Wynn, D., & Clarkson, J. (2005). Models of designing. In Design process improvement (pp. 34–59). London: Springer.
Wynn, D. C., & Eckert, C. M. (2017). Perspectives on iteration in design and development. Research in Engineering Design, 28(2), 153–184.
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Eckert, C., Hillerbrand, R. (2018). Models in Engineering Design: Generative and Epistemic Function of Product Models. In: Vermaas, P., Vial, S. (eds) Advancements in the Philosophy of Design. Design Research Foundations. Springer, Cham. https://doi.org/10.1007/978-3-319-73302-9_11
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