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<meta name="citation_title" content="Representing Systems with Models">
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'''''Lead Author:''''' ''Sanford Friedenthal,'' '''''Contributing Authors:''''' ''Dov Dori, Yaniv Mordecai''
<meta name="citation_author" content="Pyster, Art">
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<meta name="citation_author" content="Olwell, David H.">
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A {{Term|Model (glossary)|model}} is a simplified representation of a system at some particular point in time or space intended to promote understanding of the real system. As an abstraction of a {{Term|System (glossary)|system}}, it offers insight about one or more of the system's aspects, such as its {{Term|Function (glossary)|function}}, {{Term|Structure (glossary)|structure}}, properties, performance, {{Term|Behavior (glossary)|behavior}},  or {{Term|Cost (glossary)|cost}}.  
<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">
 
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A [[Model (glossary)|model (glossary)]] is a simplified representation of a system at some particular point in time or space intended to promote understanding of the real system. As an an abstraction of a [[System (glossary)|system]], it offers insight about one or more of the system's aspects, such as its [[Function (glossary) |function]], [[Structure (glossary)|structure]], properties, performance, [[Behavior (glossary)|behavior]],  or [[Cost (glossary)|cost]].  
 
  
The modeling of systems as [[Holistic (glossary)|holistic]], [[Value (glossary) | value]]-providing entities has been gaining recognition as a central process of [[Systems Engineering (glossary)|systems engineering]]. The use of modeling and simulation during the early stages of the system design of complex systems and architectures can document system functions and requirements, assess the mission performance, estimate costs, evaluate tradeoffs and provide insights to improve performance, reduce risk, and manage costs.  Modeling and analysis can complement testing and evaluation which occur 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 to 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 in accompaniment with operational system training (INCOSE 2012). Modeling serves to make [[Concept (glossary)|concepts]] concrete and formal, enhance [[Quality (glossary)|quality]], productivity, documentation, and innovation, as well as to reduce the cost and [[Risk (glossary) | risk]] of [[Systems Development (glossary)| systems development]]. Different types of models may be needed to represent systems in support of the analysis, specification, [[Design (glossary)|design]], and [[Verification (glossary)|verification]] of systems. This knowledge area provides an overview of models used to represent different aspects of systems.
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==Overview==
  
Modeling occurs at many levels:  component, subsystem, system, and systems-of-systems throughout the life cycle of a system. Modeling is a common practice that is shared by most [[Engineering (glossary) | engineering]] disciplines, including:  
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The modeling of systems as {{Term|Holistic (glossary)|holistic}}, {{Term|Value (glossary)|value}}-providing entities has been gaining recognition as a central process of {{Term|Systems Engineering (glossary)|systems engineering}}. The use of modeling and simulation during the early stages of the system design of complex systems and architectures can:
* electrical engineering, which uses electrical circuit [[Design (glossary) | design]] models
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* document system functions and requirements,
 +
*assess the mission performance,
 +
*estimate costs,
 +
*evaluate tradeoffs, and
 +
*provide insights to improve performance, reduce risk, and manage costs. 
 +
 
 +
Modeling and analysis can complement testing and evaluations which occur 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 to 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 in accompaniment with operational system training (INCOSE 2012).
 +
 
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Modeling serves to make {{Term|Concept (glossary)|concepts}} concrete and formal, enhance {{Term|Quality (glossary)|quality}}, productivity, documentation, and innovation, as well as to reduce the cost and {{Term|Risk (glossary)|risk}} of {{Term|Systems Development (glossary)|systems development}}.
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Modeling occurs at many levels:  component, subsystem, system, and systems-of-systems; and throughout the life cycle of a system. Different types of models may be needed to represent systems in support of the analysis, specification, {{Term|Design (glossary)|design}}, and {{Term|Verification (glossary)|verification}} of systems. This knowledge area provides an overview of models used to represent different aspects of systems.
 +
 
 +
Modeling is a common practice that is shared by most {{Term|Engineering (glossary)|engineering}} disciplines, including:  
 +
* electrical engineering, which uses electrical circuit {{Term|Design (glossary)|design}} models
 
* mechanical engineering, which uses three-dimensional computer-aided design models
 
* mechanical engineering, which uses three-dimensional computer-aided design models
* software engineering, which uses software design and architecture models
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* software engineering, which uses software design and architecture models.
Each of these disciplines has its own language with its syntax and [[Semantics (glossary) | 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 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.  
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Each of these disciplines has its own language with its syntax and {{Term|Semantics (glossary)|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 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.
  
 
==Topics==
 
==Topics==
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:  
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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?]]
 
* [[What is a Model?]]
 
* [[Why Model?]]
 
* [[Why Model?]]
 
* [[Types of Models]]
 
* [[Types of Models]]
 
* [[System Modeling Concepts]]
 
* [[System Modeling Concepts]]
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* [[Integrating Supporting Aspects into System Models]]
 
* [[Modeling Standards]]
 
* [[Modeling Standards]]
  
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===Works Cited===
 
===Works Cited===
  
INCOSE. 2012. ''[[INCOSE Systems Engineering Handbook|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
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INCOSE. 2012. ''[[INCOSE Systems Engineering Handbook|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.
  
 
===Primary References===
 
===Primary References===
 
Dori, D. 2002. ''[[Object-Process Methodology – A Holistic Systems Paradigm]]''. Berlin, Germany: Springer Verlag.  
 
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.
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Estefan, J. 2008. ''[[A Survey of Model-Based Systems Engineering (MBSE) Methodologies]]'', rev, B. Seattle, WA, USA: International Council on Systems Engineering.  INCOSE-TD-2007-003-02. Available at: http://www.omgsysml.org/MBSE_Methodology_Survey_RevB.pdf. Accessed April 13, 2015.  
  
Friedenthal, S., A. Moore, and R. Steiner. 2009. "Chapter 2". ''[[A Practical Guide to SysML: The Systems Modeling Language]]''. Needham, MA, USA: OMG Press.
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Friedenthal, S., A. Moore, R. Steiner, and M. Kaufman. 2012. ''[[A Practical Guide to SysML: The Systems Modeling Language]],'' 2nd Edition. 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.
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Guizzardi, G. 2007. [[On Ontology, Ontologies, Conceptualizations, Modeling Languages, and (Meta)Models|On ontology, ontologies, conceptualizations, modeling languages, and (meta)models]],” ''Proceedings of the Databases and Information Systems IV Conference, '' Amsterdam, Netherlands. Available at: ACM http://portal.acm.org/citation.cfm?id=1565425. Accessed December 4 2014.
  
INCOSE. 2007. ''[[INCOSE Systems Engineering Vision 2020|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.
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INCOSE. 2007. ''[[INCOSE Systems Engineering Vision 2020|Systems Engineering Vision 2020]]''. Seattle, WA, USA: International Council on Systems Engineering. September 2007. INCOSE-TP-2004-004-02.  
  
 
Wymore, A.W. 1993. ''[[Model-Based Systems Engineering]]''. Boca Raton, FL, USA: CRC Press, Inc.
 
Wymore, A.W. 1993. ''[[Model-Based Systems Engineering]]''. Boca Raton, FL, USA: CRC Press, Inc.
  
 
===Additional References===
 
===Additional References===
Holt, Jon, and Simon Perry. 2008. ''SysML for systems engineering''. Stevenage: Institution of Engineering and Technology. http://site.ebrary.com/id/10263845.  
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Holt, J. and S. Perry. 2008. ''SysML for Systems Engineering''. Stevenage, UK: Institution of Engineering and Technology. Available at: Ebrary http://site.ebrary.com/id/10263845.  Accessed December 4 2014.
  
Grobshtein, Y. and Dori, D. ''Generating SysML Views from an OPM Model: Design and Evaluation''. Systems Engineering, 14 (3), Sept. 2011.
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Grobshtein, Y. and D. Dori. 2011. "Generating SysML views from an OPM model: Design and evaluation," ''Systems Engineering,'' vol. 14, no. 3, Sept.
  
West, P., J. Kobza, and S. Goerger, "Chapter 4, Systems Modeling and Analysis," in Parnell, G.S., P.J. Driscoll, and D.L Henderson (eds). 2011. ''[[Decision Making for Systems Engineering and Management]]'', 2nd ed. Wiley Series in Systems Engineering. Hoboken, NJ: Wiley & Sons Inc.
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West, P., J. Kobza, and S. Goerger. 2011. "Chapter 4, systems modeling and analysis," in Parnell, G.S., P.J. Driscoll, and D.L Henderson Eds., ''[[Decision Making for Systems Engineering and Management]]'', 2nd ed. Wiley Series in Systems Engineering. Hoboken, NJ, USA: Wiley & Sons Inc.
  
 
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<center>[[Patterns of Systems Thinking|< Previous Article]] | [[Systems|Parent Article]] | [[What is a Model?|Next Article >]]</center>
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<center>[[Patterns of Systems Thinking|< Previous Article]] | [[Foundations of Systems Engineering|Parent Article]] | [[What is a Model?|Next Article >]]</center>
  
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<center>'''SEBoK v. 2.9, released 20 November 2023'''</center>
  
 
[[Category:Part 2]][[Category:Knowledge Area]]
 
[[Category:Part 2]][[Category:Knowledge Area]]
 
{{DISQUS}}
 

Latest revision as of 23:24, 18 November 2023


Lead Author: Sanford Friedenthal, Contributing Authors: Dov Dori, Yaniv Mordecai


A modelmodel is a simplified representation of a system at some particular point in time or space intended to promote understanding of the real system. As an abstraction of a systemsystem, it offers insight about one or more of the system's aspects, such as its functionfunction, structurestructure, properties, performance, behaviorbehavior, or costcost.

Overview

The modeling of systems as holisticholistic, valuevalue-providing entities has been gaining recognition as a central process of systems engineeringsystems engineering. The use of modeling and simulation during the early stages of the system design of complex systems and architectures can:

  • document system functions and requirements,
  • assess the mission performance,
  • estimate costs,
  • evaluate tradeoffs, and
  • provide insights to improve performance, reduce risk, and manage costs.

Modeling and analysis can complement testing and evaluations which occur 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 to 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 in accompaniment with operational system training (INCOSE 2012).

Modeling serves to make conceptsconcepts concrete and formal, enhance qualityquality, productivity, documentation, and innovation, as well as to reduce the cost and riskrisk of systems developmentsystems development.

Modeling occurs at many levels: component, subsystem, system, and systems-of-systems; and throughout the life cycle of a system. Different types of models may be needed to represent systems in support of the analysis, specification, designdesign, and verificationverification of systems. This knowledge area provides an overview of models used to represent different aspects of systems.

Modeling is a common practice that is shared by most engineeringengineering disciplines, including:

  • electrical engineering, which uses electrical circuit designdesign models
  • mechanical engineering, which uses three-dimensional computer-aided design models
  • software engineering, which uses software design and architecture models.

Each of these disciplines has its own language with its syntax and semanticssemantics, 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 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.

Topics

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:

References

Works Cited

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.

Primary References

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, USA: International Council on Systems Engineering. INCOSE-TD-2007-003-02. Available at: http://www.omgsysml.org/MBSE_Methodology_Survey_RevB.pdf. Accessed April 13, 2015.

Friedenthal, S., A. Moore, R. Steiner, and M. Kaufman. 2012. A Practical Guide to SysML: The Systems Modeling Language, 2nd Edition. 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: ACM http://portal.acm.org/citation.cfm?id=1565425. Accessed December 4 2014.

INCOSE. 2007. Systems Engineering Vision 2020. Seattle, WA, USA: International Council on Systems Engineering. September 2007. INCOSE-TP-2004-004-02.

Wymore, A.W. 1993. Model-Based Systems Engineering. Boca Raton, FL, USA: CRC Press, Inc.

Additional References

Holt, J. and S. Perry. 2008. SysML for Systems Engineering. Stevenage, UK: Institution of Engineering and Technology. Available at: Ebrary http://site.ebrary.com/id/10263845. Accessed December 4 2014.

Grobshtein, Y. and D. Dori. 2011. "Generating SysML views from an OPM model: Design and evaluation," Systems Engineering, vol. 14, no. 3, Sept.

West, P., J. Kobza, and S. Goerger. 2011. "Chapter 4, systems modeling and analysis," in Parnell, G.S., P.J. Driscoll, and D.L Henderson Eds., Decision Making for Systems Engineering and Management, 2nd ed. Wiley Series in Systems Engineering. Hoboken, NJ, USA: Wiley & Sons Inc.


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