TY - JOUR
T1 - A semantic model for axiomatic systems design
AU - Wang, Haoqi
AU - Zhang, Xu
AU - Tang, Chengtong
AU - Thomson, Vincent
N1 - Publisher Copyright:
© 2017, IMechE 2017.
PY - 2018/6/1
Y1 - 2018/6/1
N2 - Design of large-scale engineering systems such as an automobile, satellite, or airplane is a process to satisfy requirements by making various decisions. Design axioms provide system designers with a theoretical background to make right decisions. However, the axiomatic systems design is still hard to be implemented in the real word due to its informal representation for both the human and machine, and few researches focus on formalizing concepts of this process. In order to define axiomatic systems design models to be both user-understandable and machine-readable, this paper combines axiomatic design process with the Semantic Web technology and proposes an axiomatic design semantic representation model, called axiomatic design ontology, which organizes customers’ requirements, functional requirements, design parameters, and design solutions. The class of concepts elements and their semantic relationships are defined by the Web Ontology Language (OWL2). Rules for identifying functional couplings (the Independence Axiom) and selecting the optimal design solution (the Information Axiom) are formally represented and encoded with the Semantic Web Rule Language, which enhances the reasoning capability of the axiomatic design ontology. A framework for capturing systems design semantic information based on the axiomatic design ontology, and aligning it with domain-specific ontologies according to the semantic mapping approach has been developed, by which elaborated design information is captured and shared. Finally, a case study of systems design of a satellite solar wing subsystem is given to demonstrate the proposed axiomatic design ontology-based systems design approach.
AB - Design of large-scale engineering systems such as an automobile, satellite, or airplane is a process to satisfy requirements by making various decisions. Design axioms provide system designers with a theoretical background to make right decisions. However, the axiomatic systems design is still hard to be implemented in the real word due to its informal representation for both the human and machine, and few researches focus on formalizing concepts of this process. In order to define axiomatic systems design models to be both user-understandable and machine-readable, this paper combines axiomatic design process with the Semantic Web technology and proposes an axiomatic design semantic representation model, called axiomatic design ontology, which organizes customers’ requirements, functional requirements, design parameters, and design solutions. The class of concepts elements and their semantic relationships are defined by the Web Ontology Language (OWL2). Rules for identifying functional couplings (the Independence Axiom) and selecting the optimal design solution (the Information Axiom) are formally represented and encoded with the Semantic Web Rule Language, which enhances the reasoning capability of the axiomatic design ontology. A framework for capturing systems design semantic information based on the axiomatic design ontology, and aligning it with domain-specific ontologies according to the semantic mapping approach has been developed, by which elaborated design information is captured and shared. Finally, a case study of systems design of a satellite solar wing subsystem is given to demonstrate the proposed axiomatic design ontology-based systems design approach.
KW - Axiomatic design
KW - large-scale engineering systems
KW - ontology
KW - semantic representation
KW - system design
UR - http://www.scopus.com/inward/record.url?scp=85045441062&partnerID=8YFLogxK
U2 - 10.1177/0954406217718858
DO - 10.1177/0954406217718858
M3 - Article
AN - SCOPUS:85045441062
SN - 0954-4062
VL - 232
SP - 2159
EP - 2184
JO - Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
JF - Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
IS - 12
ER -