A 30-year case study and 15 principles: Implications of an artificial intelligence methodology for functional modeling

Abstract

Research on design and analysis of complex systems has led to many functional representations with several meanings of function. This work on conceptual design uses a family of representations called structure–behavior–function (SBF) models. The SBF family ranges from behavior–function models of abstract design patterns to drawing–shape–SBF models that couple SBF models with visuospatial knowledge of technological systems. Development of SBF modeling is an instance of cognitively oriented artificial intelligence research that seeks to understand human cognition and build intelligent agents for addressing complex tasks such as design. This paper first traces the development of SBF modeling as our perspective on design evolved from that of problem solving to that of memory and learning. Next, the development of SBF modeling as a case study is used to abstract some of the core principles of an artificial intelligence methodology for functional modeling. Finally, some implications of the artificial intelligence methodology for different meanings of function are examined.

Taking a look at the utilisation of function models in interdisciplinary design: insights from ten engineering companies

“…Warell 1999;Chandrasekaran and Josephson 2000;Maier and Fadel 2001;Chiang et al 2001;Deng 2002;Chandrasekaran 2005;Ericson and Larsson 2005;Crilly 2010;Vermaas 2009;Carrara et al 2011;Aurisicchio et al 2011;and Goel 2013). The definitions typically divert in used terminology but most importantly also with respect to the specific notions of function (i.e.…”

“…The different authors conclude that designers need flexibility in modelling functions in order to support their reasoning concurrently. Based on own studies and a review of the research by Eckert and also Vermaas (2011Vermaas ( , 2013, Goel (2013) provides compelling arguments emphasising that shared function modelling, hence, needs to be able to cope with different notions of function and flexible changes in the way functions of a system are reasoned about. A somewhat analogue argumentation is given by Buur (1990) and Lawson and Dorst (2009).…”

A DSM-based framework for integrated function modelling: concept, application and evaluation

“…However, seeing the arguments discussed earlier, whereby restrictedness in function modelling may effectively hamper designers while generating function models, a flexible and intuitive approach is considered beneficial. That means, following Goel (2013), designers should be able to reason about and to model functionality flexibly, which may include them implicitly switching between different notions and types of function in their considerations. Subsequent formalisation can still facilitate information handling and computing, which scholars like Kitamura and Mizogushi (2007) promote.…”

“…Chandrasekaran 2005). It is concluded by some scholars that it is in fact imperative for designers to have flexibility in modelling functions, in order to support their reasoning concurrently, which means not to be forced to adopt a high level of abstraction or a single notion of function (Goel 2013). …”

A new model of conceptual design based on Scientific Ontology and intentionality theory. Part II: The process model

“…For A conceptual design model based on Scientific Ontology and intentionality theory 9 example, a designer can have various solution concepts and their functions in her/his mind or a knowledge base; when a desired function is identified, s/he probably can directly map the desired function into an existing solution concept, regardless of the model actions or model behaviors that are employed in the solution concept. This experience-based model of design is actually the cognitive foundation of many computer-based design approaches, such as the design prototype framework by Gero (1990), the Structure-Behavior-Function approach (Goel, 2013), and our multi-disciplinary conceptual design approach (Chen, Liu, & Xie, 2012), where existing solution concepts are stored in a knowledge base for retrieval and synthesis in the future.…”