ArchME: A Systems Modeling Language extension for mechatronic system architecture modeling. Issue 1 (14th August 2017)
- Record Type:
- Journal Article
- Title:
- ArchME: A Systems Modeling Language extension for mechatronic system architecture modeling. Issue 1 (14th August 2017)
- Main Title:
- ArchME: A Systems Modeling Language extension for mechatronic system architecture modeling
- Authors:
- Chen, Ruirui
Liu, Yusheng
Cao, Yue
Zhao, Jianjun
Yuan, Lin
Fan, Hongri - Abstract:
- Abstract: System architecture is important for the design of complex mechatronic systems because it acts as an intermediator between conceptual design and detail design. An explicit and exact system modeling language is imperative for successful architecture design. However, some deficiencies remain, such as the lack of geometry elements, hybrid behavior description, and specific association semantics for existing architecture modeling languages. In this study, a Systems Modeling Language extension for mechatronic system architecture modeling called ArchME is proposed. The requirements for the mechatronic System Modeling Language are analyzed, and the metamodels are defined. Then, the modeling elements are determined. Finally, the profiles based on the systems modeling language are defined to support the modeling of function, behavior, structure, and their association. This enables system designers to model the system architecture and facilitates communication between different stakeholders. A case study is provided to demonstrate the modeling capability of ArchME.
- Is Part Of:
- AI EDAM. Volume 32:Issue 1(2018)
- Journal:
- AI EDAM
- Issue:
- Volume 32:Issue 1(2018)
- Issue Display:
- Volume 32, Issue 1 (2018)
- Year:
- 2018
- Volume:
- 32
- Issue:
- 1
- Issue Sort Value:
- 2018-0032-0001-0000
- Page Start:
- 75
- Page End:
- 91
- Publication Date:
- 2017-08-14
- Subjects:
- Mechatronic System, -- Model-Based Systems Engineering, -- Modeling Language, -- SysML, -- System Architecture
Engineering design -- Data processing -- Periodicals
Artificial intelligence -- Periodicals
Expert systems (Computer science) -- Periodicals
620.00420285 - Journal URLs:
- http://www.journals.cambridge.org/jid%5FAIE ↗
- DOI:
- 10.1017/S0890060417000245 ↗
- Languages:
- English
- ISSNs:
- 0890-0604
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 5683.xml