Representing Systems with Models
<html> <meta name="citation_title" content="Representing Systems with Models"> <meta name="citation_author" content="Pyster, Art"> <meta name="citation_author" content="Olwell, David H."> <meta name="citation_author" content="Hutchison, Nicole"> <meta name="citation_author" content="Enck, Stephanie"> <meta name="citation_author" content="Anthony, James F., Jr."> <meta name="citation_author" content="Henry, Devanandham"> <meta name="citation_author" content="Squires, Alice (eds)"> <meta name="citation_publication_date" content="2012/11/30"> <meta name="citation_journal_title" content="Guide to the Systems Engineering Body of Knowledge (SEBoK)"> <meta name="citation_volume" content="version 1.0.1"> <meta name="citation_pdf_url" content="http://www.sebokwiki.org/1.0.1/index.php?title=Main_Page"></html> A model is an abstraction of a system that offers insight about one or more of the the system's aspects, such as its function, structure, properties, performance, behavior, or cost.
Modeling of systems as holistic, value-providing entities, has been gaining recognition as a central process of systems engineering. The use in modeling and simulation during early system design of complex systems and architectures can document system functions and requirements; assess the mission performance; estimate costs; and evaluate tradeoffs and provide insights to improve performance, reduce risk, and manage costs. Modeling and analysis can complement testing and evaluation which occurs later in the life cycle. In some systems modeling and simulation may be the only way to fully evaluate performance (e.g., ballistic missile defense) or the evaluate system performance in severe scenarios (e.g., response to weapons of mass destruction attacks on the homeland). Furthermore, advanced simulations, e.g. flight simulators and command and control center simulations, can be a cost effective technique for personnel training to complement operational system training. (ref: SE Handbook) This knowledge area provides an overview of models used to represent different aspects of systems.
Modeling occurs at many levels: component, subsystem, system, and systems-of-systems throughout the systems life cycle. Modeling is a common practice that is shared by most engineering disciplines, such as 1.) electrical engineering, which uses electrical circuit design models, 2.) mechanical engineering, which uses three-dimensional computer-aided design models, and 3.) software engineering, which uses software design models. Each of these disciplines has their own language, with its syntax and semantics, serving as a means of communication among professionals in that discipline. Analytic models are used to support power, thermal, structural, and embedded real-time analysis.
Modeling serves to make concepts concrete and formal, enhance quality, productivity, documentation, and innovation, as well as reduce the cost and risk of systems development. Different types of models may be needed to represent systems in support of the analysis, specification, design, and verification of systems.
Modeling standards play an important role in defining system modeling concepts that can be represented for a particular domain of interest and enable the integration of different types of models across domains of interest.
Each part of the Guide to the Systems Engineering Body of Knowledge (SEBoK) is divided into knowledge areas (KAs), which are groupings of information with a related theme. The KAs in turn are divided into topics. This KA contains the following topics:
- What is a Model?
- Why Model?
- Types of Models
- System Modeling Concepts
- Modeling Standards
- Model-Based Authoring of Standards and Other Technical Documents
INCOSE. 2012. Systems Engineering Handbook: A Guide for System Life Cycle Processes and Activities, version 3.2.2. San Diego, CA, USA: International Council on Systems Engineering (INCOSE), INCOSE-TP-2003-002-03.2.2.
Dori, D. 2002. Object-Process Methodology – A Holistic Systems Paradigm. Berlin, Germany: Springer Verlag.
Estefan, J. 2008. A Survey of Model-Based Systems Engineering (MBSE) Methodologies, rev, B. Seattle, WA: International Council on Systems Engineering. INCOSE-TD-2007-003-02. Available at http://www.incose.org/ProductsPubs/pdf/techdata/MTTC/MBSE_Methodology_Survey_2008-0610_RevB-JAE2.pdf.
Friedenthal, S., A. Moore, and R. Steiner. 2009. "Chapter 2". A Practical Guide to SysML: The Systems Modeling Language. Needham, MA, USA: OMG Press.
Guizzardi, G. 2007. On Ontology, Ontologies, Conceptualizations, Modeling Languages, and (Meta)Models. Proceedings of the Databases and Information Systems IV Conference, Amsterdam, Netherlands. Available at http://portal.acm.org/citation.cfm?id=1565425.
INCOSE. 2007. Systems Engineering Vision 2020. Seattle, WA, USA: International Council on Systems Engineering. September 2007. INCOSE-TP-2004-004-02. Available at http://www.incose.org/ProductsPubs/products/sevision2020.aspx.
Wymore, A.W. 1993. Model-Based Systems Engineering. Boca Raton, FL, USA: CRC Press, Inc.
Holt, Jon, and Simon Perry. 2008. SysML for systems engineering. Stevenage: Institution of Engineering and Technology. http://site.ebrary.com/id/10263845.
Grobshtein, Y. and Dori, D. Generating SysML Views from an OPM Model: Design and Evaluation. Systems Engineering, 14 (3), Sept. 2011.
West, P., Kobza, J., and Goerger, S., Chapter 4, Systems Modeling and Analysis Parnell, G. S., Driscoll, P. J., and Henderson D. L., Editors, Decision Making for Systems Engineering and Management, 2nd Edition, Wiley Series in Systems Engineering, Wiley & Sons Inc., 2011
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