Hostname: page-component-8448b6f56d-t5pn6 Total loading time: 0 Render date: 2024-04-19T13:11:26.680Z Has data issue: false hasContentIssue false
  • English
  • Français

A case for multiple views of function in design based on a common definition

Published online by Cambridge University Press:  24 July 2013

Amaresh Chakrabarti ,
V. Srinivasan ,
B.S.C. Ranjan  and
Udo Lindemann
Amaresh Chakrabarti*
Affiliation:
Centre for Product Design and Manufacturing, Indian Institute of Science, Bangalore, India
V. Srinivasan
Affiliation:
Institute of Product Development, Technical University of Munich, Munich, Germany
B.S.C. Ranjan
Affiliation:
Centre for Product Design and Manufacturing, Indian Institute of Science, Bangalore, India
Udo Lindemann
Affiliation:
Institute of Product Development, Technical University of Munich, Munich, Germany
*
Reprint requests to: Amaresh Chakrabarti, Centre for Product Design and Manufacturing, Indian Institute of Science, Bangalore 560012, India. E-mail: ac123@cpdm.iisc.ernet.in
Get access Rights & Permissions [Opens in a new window]

Abstract

Functions are important in designing. However, several issues hinder progress with the understanding and usage of functions: lack of a clear and overarching definition of function, lack of overall justifications for the inevitability of the multiple views of function, and scarcity of systematic attempts to relate these views with one another. To help resolve these, the objectives of this research are to propose a common definition of function that underlies the multiple views in literature and to identify and validate the views of function that are logically justified to be present in designing. Function is defined as a change intended by designers between two scenarios: before and after the introduction of the design. A framework is proposed that comprises the above definition of function and an empirically validated model of designing, extended generate, evaluate, modify, and select of state-change, and an action, part, phenomenon, input, organ, and effect model of causality (Known as GEMS of SAPPhIRE), comprising the views of activity, outcome, requirement–solution–information, and system–environment. The framework is used to identify the logically possible views of function in the context of designing and is validated by comparing these with the views of function in the literature. Describing the different views of function using the proposed framework should enable comparisons and determine relationships among the various views, leading to better understanding and usage of functions in designing.

Keywords

Common DefinitionEnvironmentExtend FunctionGenerateIntended ChangeGEMS of SAPPhIRERequirementScenariosSolutionSystem
Type
Response Papers
Information
AI EDAM , Volume 27 , Issue 3: Functional Descriptions in Engineering , August 2013 , pp. 271 - 279
Copyright
Copyright © Cambridge University Press 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Brown, D., & Blessing, L. (2005). The relationship between function and affordance. Proc. Int. Design Engineering Technical Conf. and Computers and Information in Engineering Conf., DETC/CIE, Report No. DECT2005-85017, Long Beach, CA, September 24–2008.CrossRefGoogle Scholar
Chakrabarti, A. (1998). Supporting two views of function in mechanical design. Workshop on Functional Modeling and Teleological Reasoning. Proc. 15th Association for the Advancement of Artificial Intelligence National Conf. AI, Madison, WI, July 26–30.Google Scholar
Chakrabarti, A. (2001). Improving efficiency of procedures for compositional synthesis using bidirectional search. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 15(1), 67–80.CrossRefGoogle Scholar
Chakrabarti, A. (2004). A new approach to structure sharing. Journal of Computer and Information Science in Engineering 4(1), 11–19.CrossRefGoogle Scholar
Chakrabarti, A., & Blessing, L. (1996). Representing functionality in design [Guest Editorial]. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 10(4), 251–253.CrossRefGoogle Scholar
Chakrabarti, A., Johnson, A., & Kiriyama, T. (1997). An approach to automated synthesis of solution principles for micro-sensor designs. Proc. Int. Conf. Engineering Design, ICED97, pp. 125–128, Helsinki.Google Scholar
Chakrabarti, A., Sarkar, P., Leelavathamma, B., & Nataraju, B. (2005). A functional representation for aiding biomimetic and artificial inspiration of new ideas. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 19(2), 113–132.CrossRefGoogle Scholar
Chandrasekaran, B., & Josephson, J. (2000). Function in device representation. Engineering With Computers 16, 162–177.CrossRefGoogle Scholar
Chittaro, L., & Kumar, A. (1998). Reasoning about function and its applications to engineering. AI in Engineering 12(4), 331–336.Google Scholar
Crilly, N. (2010). The roles that artefacts play: technical, social and aesthetic function. Design Studies 31(4), 311–344.CrossRefGoogle Scholar
Deng, Y. (2002). Function and behavior representation in conceptual mechanical design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 16(5), 343–362.CrossRefGoogle Scholar
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(3), 217–232 [this issue].CrossRefGoogle Scholar
Gero, J. (1990). Design prototypes: a knowledge representation schema for design. AI Magazine 11(4), 26–36.Google Scholar
Goel, A., 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(1), 23–35.CrossRefGoogle Scholar
Hirtz, J., Stone, R.B., McAdams, D.A., Szykman, S., & Wood, K.L. (2002). A functional basis for engineering design: reconciling and evolving previous efforts. Research in Engineering Design 13(2), 65–82.CrossRefGoogle Scholar
Hubka, V., & Eder, W. (1988). Theory of Technical Systems: A Total Concept Theory for Engineering Design. Berlin: Springer–Verlag.CrossRefGoogle Scholar
Keuneke, A. (1991). Device representation—the significance of functional knowledge. IEEE Expert 6(2), 22–25.CrossRefGoogle Scholar
Kitamura, Y., Koji, Y., & Mizoguchi, R. (2006). An ontological model of device function: industrial deployment and lessons learned. Journal of Applied Ontology 1(3–4), 237–262.Google Scholar
Kitamura, Y., & Mizoguchi, R. (2010). Characterizing functions based on ontological models from an engineering point of view. Proc. Formal Ontology in Information Systems (FOIS), pp. 301–314. Amsterdam: IOS Press.Google Scholar
Miles, L. (1972). Techniques of Value Analysis and Engineering. New York: McGraw–Hill.Google Scholar
Nidamarthi, S. (1999). Understanding and supporting requirement satisfaction in the design process. PhD Thesis. University of Cambridge.Google Scholar
Pahl, G., & Beitz, W. (2007). Engineering Design: A Systematic Approach. London: Springer–Verlag.CrossRefGoogle Scholar
Pahl, G., & Beitz, W. (1977). Konstruktionslehre. Berlin: Springer.CrossRefGoogle Scholar
Ranjan, B.S.C. (2012). An extended, integrated model of designing. Masters Thesis. Indian Institute of Science, Bangalore.Google Scholar
Ranjan, B.S.C., Srinivasan, V., & Chakrabarti, A. (2012). The extended, integrated model of designing. Proc. Tools and Methods of Competitive Engineering 2012, Karlsruhe, Germany, May 7–11.Google Scholar
Ranjan, B.S.C., Srinivasan, V., & Chakrabarti, A. (2013). System–environment view in designing. CIRP Design: 2012 Sustainable Product Development, pp. 59–70. London: Springer–Verlag.CrossRefGoogle Scholar
Rodenacker, W. (1971). Methodisches konstruieren. Berlin: Springer–Verlag.Google Scholar
Simon, H. (1996). The Sciences of the Artificial. Cambridge, MA: MIT Press.Google Scholar
Srinivasan, V., & Chakrabarti, A. (2010). An integrated model of designing. Journal of Computer and Information Science in Engineering 10(3), 031013.CrossRefGoogle Scholar
Stone, R., & Chakrabarti, A. (2005). Engineering applications of representations of function [Guest Editorial]. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 19(2), 63.Google Scholar
Stone, R., & Wood, K. (2000). Development of a functional basis for design. Journal of Mechanical Design 122(4), 359–370.CrossRefGoogle Scholar
Ullman, D. (1992). The Mechanical Design Process. Boston: McGraw–Hill.Google Scholar
Umeda, Y., Ishii, M., Yoshioka, M., Shimomura, Y., & Tomiyama, T. (1996). Supporting conceptual design based on the function–behavior–state modeler. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 10(4), 275–288.CrossRefGoogle Scholar
Vermaas, P. (2011). Accepting ambiguity of engineering functional descriptions. Proc. Int. Conf. Engineering Design, ICED11, pp. 98–107. Copenhagen: Design Society.Google Scholar
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(3), 191–202 [this issue].CrossRefGoogle Scholar
Wood, K., & Greer, J. (2001). Function-based synthesis methods in engineering design. In Formal Engineering Design Synthesis (Antonsson, E., & Cagan, J., Eds.). New York: Cambridge University Press.Google Scholar