Abstract
Abstract Functional decomposition is an important task in early systems engineering and design, where the overall function of the system is resolved into the functions of its components or subassemblies. Conventionally, this task is performed manually, because of multiple possible solution paths and the need for understanding the physics phenomena that could realize the desired effects. This paper presents an approach of developing a formal method for functional decomposition using physics-based qualitative reasoning. The representation includes three parts: (1) a natural language reasoner that detects the changes of physical states of material and energy flows, (2) a set of causation tables that abstract the knowledge of qualitative physics by capturing the causal relations between the various quantities involved in a physical phenomenon or process, and (3) a process-to-subgraph mapping that translate the physical processes into function structure constructs. The algorithm uses the above three representations and some topological reasoning to assemble function models that represent the decomposition of a given black box model. The paper illustrates the potential of this method for functional decomposition using an example of an air-heating device. The paper also discusses the limitations and challenges in maturing this approach into an end-usable design tool.
Published Version
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