Functional reasoning is regarded as an important asset to the engineering designers’ conceptual toolkit. Yet despite the value of functional reasoning for engineering design, a consensus view is lacking and several distinct proposals have been formulated. In this paper some of the main models for functional reasoning that are currently in use or discussed in engineering are surveyed and some of their differences clarified. The models included the Functional Basis approach by Stone and Wood [1], the Function Behavior State approach by Umeda et al. [2, 3, 4], and the Functional Reasoning approach of Chakrabarti and Bligh [5, 6]. This paper explicates differences between these approaches relating to: (1) representations of function and how they are influenced by design aims and form solutions, and (2) functional decomposition strategies, taken as the reasoning from overall artifact functions to sub-functions, and how these decomposition strategies are influenced by the use of existing engineering design knowledge bases.
In this paper, I discuss a methodology for the conversion of functional models between functional taxonomies developed by Kitamura et al. (2007) and Ookubo et al. (2007). They apply their methodology to the conversion of functional models described in terms of the Functional Basis taxonomy into functional models described in terms of the Functional Concept Ontology taxonomy. I argue that this model conversion harbors two problems. One, a step in this model conversion that is aimed to handle differences in the modeling of user features consists of the removal of Functional Basis functions. It is shown that this removal can lead to considerable information loss. Two, some Functional Basis functions that I argue correspond to user functions, get re-interpreted as device functions in the model conversion. I present an alternative strategy that prevents information loss and information change in model conversions between the Functional Basis and Functional Concept Ontology taxonomies.
This paper advances three related arguments showing that the ontic conception of explanation (OC), which is often adverted to in the mechanistic literature, is inferentially and conceptually incapacitated, and in ways that square poorly with scientific practice. Firstly, the main argument that would speak in favor of OC is invalid, and faces several objections. Secondly, OC's superimposition of ontic explanation and singular causation leaves it unable to accommodate scientifically important explanations. Finally, attempts to salvage OC by reframing it in terms of 'ontic constraints' just concedes the debate to the epistemic conception of explanation. Together, these arguments indicate that the epistemic conception is more or less the only game in town.
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