Semantic and Qualitative Physics-Based Formal Reasoning for Functional Decomposition in Mechanical Design
Abstract
Function modeling plays an essential role in academy design studies, yet a
lack of acceptance in industry. A possible reason is that the designer must have well
understand of the controlled vocabularies and grammars to utilize this method. The
research presented in this dissertation is to fill this gap so that designers can use
function-based design method without relevant knowledge. In graph-based function
models, the function verbs and flow nouns are usually chosen from predefined
vocabularies. The vocabulary class definitions, combined with function modeling
grammars defined at various levels of formalism, enable function-based reasoning.
However, the text written in plain English for the names of the functions and
flows is presently not exploited for formal reasoning. This dissertation presents
a formalism (representation and reasoning) to support semantic and physics-based
reasoning on the information hidden in the plain-English flow terms, esp. for automatically decomposing black-box function models and to generate multiple
design alternatives. First, semantic reasoning infers the changes of flow types, flow
attributes, and the direction of those changes between the input and output flows
attached to the black-box. Then, a representation of qualitative physics is used to
determine the material and energy exchanges between the flows and the function
features needed to achieve them. Finally, the topological layer provides reasonings
to infer multiple options of composing those function features into topologies and to
thus generate multiple alternative decompositions of the functional black-box. The
data representation formalizes flow phases, flow attributes, qualitative value scales
for the attributes, and qualitative physics laws. A three-layer algorithm manipulates
this data for reasoning. The dissertation shows four validation case studies to
demonstrate the workings of this formalism.