Title
Transforming functional models to critical chain models via expert knowledge and automatic parsing rules for design analogy identification.
Abstract
Critical chains composed of critical flows and functions have been demonstrated as an effective qualitative analogy retrieval approach based on performance metrics. In prior work, engineers used expert knowledge to transform functional models into critical chain models, which are abstractions of the functional model. Automating this transformation process is highly desirable so as to provide for a robust transformation method. Within this paper, two paradigms for functional modeling abstraction are compared. A series of pruning rules provide an automated transformation approach, and this is compared to the results generated previously through an expert knowledge approach. These two approaches are evaluated against a set of published functional models. The similarity of the resulting transformation of the functional models into critical chain models is evaluated using a functional chain similarity metric, developed in previous work. Once critical chain models are identified, additional model evaluation criteria are used to evaluate the utility of the critical chain models for design analogy identification. Since the functional vocabulary acts as a common language among designers and engineers to abstract and represent critical design artifact information, analogous matching can be made about the functional vocabulary. Thus, the transformation of functional models into critical chain models enables engineers to use functional abstraction as a mechanism to identify design analogies. The critical flow rule is the most effective first step when automatically transforming a functional model to a critical chain model. Further research into more complex critical chain model architectures and the interactions between criteria is merited.
Year
DOI
Venue
2017
10.1017/S0890060417000488
AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING
Keywords
Field
DocType
Analogy Matching,Automated Abstraction,Design by Analogy,Functional Criteria Metrics,Functional Modeling
Computer science,Natural language processing,Artificial intelligence,Parsing,Analogy
Journal
Volume
Issue
ISSN
31
SP4
0890-0604
Citations 
PageRank 
References 
1
0.35
5
Authors
3
Name
Order
Citations
PageRank
Malena Agyemang110.35
Julie Linsey25512.39
Cameron J. Turner3133.23