Difference between pages "Principles of Systems Thinking" and "Fundamentals for Future Systems Engineering"

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This topic forms part of the [[Systems Thinking]] Knowledge Area. It identifies systems [[Principle (glossary) | principles]] as part of the basic ideas of [[Systems Thinking (glossary) | systems thinking]].  
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'''''Lead Author:''''' ''Rick Adcock'', '''''Contributing Author:''''' ''Duane Hybertson''
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This article forms part of the [[Systems Fundamentals]] knowledge area (KA). It considers future trends in SE and how these might influence the evolution of future fundamentals.
  
Some additional [[Concept (glossary) | concepts]] more directly associated with [[Engineered System (glossary) | engineered systems]] are described and a summary of system [[Principle (glossary) | principles]] associated with the concepts already defined, is providedA number of additional “laws” and [[Heuristic (glossary) | heuristics]] are also discussed.  
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The SEBoK contains a guide to generalized knowledge about the practice of SE.  It does not pass judgement on that knowledgeHowever, it can be useful in some cases to indicate which parts of the knowledge are rooted in existing practice and which point towards the future evolution of SE.
  
==Systems Principles, Laws, and Heuristics==
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This article provides a sketch of how SE is changing and suggests how these changes may affect the future of systems engineering, the SEBoK, and the foundations in Part 2.
A principle is a general rule of conduct or behavior (Lawson and Martin 2008), or a basic generalization that is accepted as true and that can be used as a basis for reasoning or conduct (WordWeb 2012c). Thus, systems principles can be used as a basis for reasoning about systems (systems thinking) or associated conduct ([[Systems Approach (glossary) | systems approaches]]).
 
  
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==INCOSE Vision==
  
==Separation of Concerns==
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The INCOSE Vision 2025 statement (INCOSE 2014) depicts some future directions in:
  
A systems approach is focused on a [[System-of-Interest (glossary)| systems-of-interest]] (SoI) of an  [[Open System (glossary) | open system]]. This SoI consists of open, interacting subsystems that a as a whole interacts with and adapts to other systems in an [[Environment (glossary) | environment]]. The systems approach also considers the SoI in its environment to be part of a larger, wider, or containing system (Hitchins 2009).
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Broadening SE Application Domains
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*SE relevance and influence will go beyond traditional aerospace and defense systems and extend into the broader realm of engineered, natural and social systems
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*SE will be applied more widely to assessments of socio-physical systems in support of policy decisions and other forms of remediation
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More Intelligent and Autonomous Systems
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*Systems of the future need to become smarter, self-organized, sustainable, resource-efficient, robust and safer
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*The number of autonomous vehicles and transportation systems needs to increase
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*Systems become more “intelligent” and dominate human-safety critical applications
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Theoretical Foundations
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*SE will be supported by a more encompassing foundation of theory and sophisticated model-based methods and tools allowing a better understanding of increasingly complex systems and decisions in the face of uncertainty
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*Challenge: A core body of systems engineering foundations is defined and taught consistently across academia and forms the basis for systems engineering practice
  
In the [[What is Systems Thinking?]] topic a “systems thinking paradox” is discussed. How can we take a holistic system view while still being able to focus on changing or creating systems? 
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In this article we will consider how the fundamentals of SE might need to evolve to support this vision.
  
Separation of Concerns is a term used to describe a balance between considering parts of a system [[Problem (glossary) | problem]] or [[Solution (glossary) | solution]] while not losing sight of the whole (Greer 2008).  [[Abstraction (glossary)]] is the process of taking away characteristics from something in order to reduce it to a set of essential characteristics (SearchCIO 2012). In attempting to understand [[Complex (glossary) | complex]] situations it is easier to focus on [[Boundary (glossary) | bounded]] problems, whose [[Solution (glossary) | solutions]] “still remaining agnostic to the greater problem.” (Erl 2012).  This sounds [[Reductionism (glossary) | reductionist]], but it can be applied effectively to systems. The key is that one of the selected problems, needs to be the concerns of the system as a whole. This idea of a balance between using abstraction to focus on specific concerns while ensuring we continue to consider the whole is at the center of [[Systems Approach (glossary)| systems approaches]].
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==How will SE Change?==
 
A [[View (glossary) | view]] is a subset of information observed of one or more entities, such as systems. The physical or conceptual point from which a view is observed is the [[Viewpoint (glossary) | viewpoint]], that can be motivated by one or more observer concerns. Different views of the same target must be both separated, to reflect separation of concerns, and integrated such that all views of a given target are consistent and form a coherent whole (Hybertson 2009). Some sample views of a system are: internal (what does it consist of?); external (what are its properties and [[Behavior (glossary) | behavior]] as a whole?); static (parts, structures); and dynamic (interactions).
 
  
[[Encapsulation (glossary)]], encloses [[System Element (glossary) | system elements]] and their interactions from the external environment is discussed in [[Concepts of Systems Thinking]] topic. Encapsulation is associated with [[Modularity (glossary) | modularity]] the degree to which a system's [[Component (glossary) | components]] may be separated and recombined (Griswold 1995). Modularity applies to systems in many domains, natural, social, and engineeredIn [[Engineering (glossary) | engineering]], encapsulation is the isolation of a system [[Function (glossary) | function]] within a module and providing precise specifications for the module (IEEE Std. 610.12-1990).
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In [[Types of Systems]], we describe three general contexts in which a SE life cycle can be applied.  In a {{Term|Product System (glossary)}} {{Term|Context (glossary)}}, the outputs of SE focus on the delivery of technological systems.  While such systems are designed to be used by people and fit into a wider problem-solving context, this context has been seen as largely fixed and external to SEThe {{Term|Service System (glossary)}} context allows SE to consider all aspects of the solution system as part of its responsibility.  This is currently seen as a special case of SE application largely focused on software intensive solutions.  The {{Term|Enterprise System (glossary)}} context offers the potential for a direct application of SE to tackle complex socio-technical problems, by supporting the planning, development and use of combinations of service systems.  While this is done, it can be difficult to connect to the product focused life cycles of many SE projects.  
  
[[Dualism (glossary)]] is a characteristic of systems in which they exhibit seemingly contradictory characteristics that are important for the system (Hybertson 2009)The yin yang concept in Chinese philosophy emphasizes the interaction between dual [[Element (glossary) | elements]] and their harmonization, ensuring a constant dynamic balance often through a cyclic dominance of one element and then the other, such as day and night (IEP 2006).  
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The role of the systems engineer has already begun to change somewhat due to the first two of the future trends above. Changes to the scope of SE application and the increased use of software intensive reconfigurable and autonomous solutions will make the service system context the primary focus of most SE life cyclesTo enable this, most product systems will need to become more general and configurable, allowing them to be used in a range of service systems as needed.  These life cycles are increasingly initiated and managed as part of an enterprise portfolio of related life cycles.  
  
From a systems perspective the interaction, harmonization, and balance between system properties is important(Hybertson 2009) defines '''Leverage''' as the duality between
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In this evolution of SE, the systems engineer cannot consider as many aspects of the context to be fixed, making the problem and possible solution options more complex and harder to anticipate. This also means the systems engineer has greater freedom to consider solutions which combine existing and new technologies and in which the role of people and autonomous software can be changed to help deliver desired outcomes.  For such systems to be successful, they will need to include the ability to change, adapt and grow both in operation and over several iterations of their life cycleThis change moves SE to be directly involved in enterprise strategy and planning, as part of an ongoing and iterative approach to tackling the kinds of societal problems identified in the INCOSE vision.
*'''Power:''' the extent to which a system solves a specific problem
 
*'''Generality:''' the extent to which a system solves a whole class of problems.  
 
  
While some systems or elements may be optimized for one extreme of such dualities a dynamic balance is needed to be effective in solving complex problems.
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This evolution of both the role and scope of SE will also see the {{Term|System of Systems (SoS) (glossary)|system of systems}} aspects of all system contexts increase. We can expect {{Term|System of Systems Engineering (glossary)}} to become part of the systems engineering of many, if not most, SE life cycles.
  
===Summary of Systems Principles===
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==Evolution of Fundamentals==
A set of systems principles is given in Table 1 below.
 
  
The names points to concepts underlying the principle (see topic on [[Concepts of Systems Thinking]]). Following the table, two additional sets of items related to systems principles are noted and briefly discussed: Prerequisite laws for [[Design (glossary) | design science]], and [[Heuristic (glossary) |heuristics]] and pragmatic principles.
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These ongoing changes to SE place more emphasis on the role of autonomous agents in systems engineering, and agency will be an area of increased emphasis in the systems engineering and SEBoK of the future. Hybertson (2019) spells out in more detail the increased role of agents and agency in future SE. Moving from a total control model to a shared responsibility model changes the nature of engineering to something more like collective actualization, as proposed by Hybertson (2009 and 2019). Systems will represent a combination and interplay of technology and social factors, and they can range from technical product to service provider to social entity. In many cases they will be a socio-technical combination or hybrid.
  
<center>'''Table 1. A Set of Systems Principles.'''  (SEBoK Original)</center>
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The above trends have an impact on SE foundations, including technical aspects, social aspects, and ethical aspects. Inclusion of people in systems implies significant expansion of foundation sciences, to provide principles, theories, models, and patterns of the human, biological, social, and agent realm as well as the technical and physical realm. Emphasis on agents implies a revised conceptualization of system change, from the traditional model of mechanistic and controlled fixes and upgrades to a more organic change model that involves growth, self-learning, self-organizing, and self-adapting. Ethical considerations will include how to allocate responsibility for a system in a shared responsibility model. Further discussion of the expanded foundation and a list of foundation disciplines for future SE are presented in (Hybertson 2009 and 2019).  
{| align="center"
 
! Name
 
! Statement of Principle
 
|-
 
|[[Regularity (glossary)]]
 
|[[Systems Science (glossary) | Systems science]] should find and capture regularities in systems, because those regularities promote systems understanding and facilitate systems practice. (Bertalanffy 1968)
 
|-
 
|[[Holism (glossary)]]
 
|A system should be considered as a single entity, a whole, not just as a set of parts. (Ackoff 1979; Klir 2001)
 
|-
 
|'''Interaction'''
 
|The properties, [[Capability (glossary) | capabilities]], and [[Behavior (glossary) | behavior]] of a system derive from its parts, from interactions between those parts, and from interactions with other systems. (Hitchins 2009 p. 60)
 
|-
 
|'''Relations'''
 
|A system is characterized by its relations: the interconnections between the elements. Feedback is a type of relation. The set of relations defines the [[Network (glossary) | network]] of the system. (Odum 1994)
 
|-
 
|[[Boundary (glossary)]]
 
|A boundary or membrane separates the system from the external world. It serves to concentrate interactions inside the system while allowing exchange with external systems. (Hoagland, Dodson, and Mauck 2001)
 
|-
 
|[[Synthesis (glossary)]]
 
|Systems can be created by choosing (conceiving, designing, selecting) the right parts, bringing them together to interact in the right way, and in orchestrating those interactions to create requisite properties of the whole, such that it performs with optimum effectiveness in its operational [[Environment (glossary) | environment]], so solving the problem that prompted its creation” (Hitchins 2008: 120).
 
|-
 
|[[Abstraction (glossary)]]
 
|A focus on essential characteristics is important in problem solving because it allows problem solvers to ignore the nonessential, thus simplifying the problem. (Sci-Tech Encyclopedia 2009; SearchCIO 2012; Pearce 2012)
 
|-
 
|'''Separation of Concerns'''
 
|A larger problem is more effectively solved when decomposed into a set of smaller problems or concerns. (Erl 2012; Greer 2008)
 
|-
 
|[[View (glossary)]]
 
|Multiple views, each based on a system aspect or concern, are essential to understand a complex system or problem situation. One critical view being how concern relates to properties of the whole. (Edson 2008; Hybertson 2009)
 
|-
 
|[[Modularity (glossary)]]
 
|Unrelated parts of the system should be separated, and related parts of the system should be grouped together. (Griswold 1995; Wikipedia 2012a)
 
|-
 
|'''Encapsulation'''
 
|Hide internal parts and their interactions from the external environment. (Klerer 1993; IEEE 1990)
 
|-
 
|'''Similarity/ Difference'''
 
|Both the similarities and differences in systems should be recognized and accepted for what they are. (Bertalanffy 1975 p. 75; Hybertson 2009). Avoid forcing one size fits all, and avoid treating everything as entirely unique.
 
|-
 
|[[Dualism (glossary)]]
 
| Recognize dualities and consider how they are, or can be, harmonized in the context of a larger whole (Hybertson 2009)
 
|-
 
|[[Leverage (glossary)]]
 
|Achieve maximum leverage (Hybertson 2009). Because of the power versus generality tradeoff, leverage can be achieved by a complete solution (power) for a narrow class of problems, or by a partial solution for a broad class of problems (generality.
 
|-
 
|'''Change'''
 
|Change is necessary for growth and adaptation, and should be accepted and planned for as part of the natural order of things, rather than something to be ignored, avoided, or prohibited. (Bertalanffy 1968; Hybertson 2009)
 
|-
 
|'''Stability/ Change'''
 
|Things change at different rates, and entities or concepts at the stable end of the spectrum can and should be used to provide a guiding context for rapidly changing entities at the volatile end of the spectrum (Hybertson 2009). The study of complex adaptive systems can give guidance to system behavior and design in changing environments (Holland 1992).
 
|-
 
|'''Equifinality'''
 
|In open systems, the same final state may be reached from different initial conditions and in different ways. (Bertalanffy 1968). This principle can be exploited especially in systems of purposeful agents.
 
|-
 
|'''Parsimony'''
 
|One should choose the simplest explanation of a phenomenon, the one that requires the fewest assumptions. (Cybernetics 2012). This applies not only to choosing a design, but also operations and requirements.
 
|-
 
|'''Layer, ''' [[Hierarchy (glossary)]]
 
|The evolution of complex systems is facilitated by their hierarchical structure (including stable intermediate forms), and the understanding of complex systems is facilitated by their hierarchical description. (Pattee 1973; Bertalanffy 1968; Simon 1996)
 
|-
 
|[[Network (glossary)]]
 
|The network is a fundamental topology for systems that forms the basis of togetherness, connection, and dynamic interaction of parts that yield the behavior of complex systems (Lawson 2010; Martin et al. 2004; Sillitto 2010)
 
|}
 
  
The principles are not independent. They have synergies and tradeoffs. Lipson (2007), for example, argued that “Scalability of open-ended evolutionary processes depends on their ability to exploit functional modularity, structural regularity and hierarchy.” He proposed a formal model for examining the properties, dependencies, and tradeoffs among these principles. Edson (2008) related many of the above principles in a structure called the conceptagon, which he modified from (Boardman and Sauser 2008), and also provided guidance on how to apply the principles. Not all principles apply to every system or engineering decision. Judgment, experience, and heuristics (see below) help understand which principles apply in a given situation.
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==References==
 
 
Several principles illustrate the relation of view with the dualism and yin yang principle. An important example is the Holism and Separation of Concerns pair of principles. These look contradictory, but they are dual ways of dealing with complexity. Holism deals with complexity by focusing on the whole system, and Separation of Concerns deals with complexity by dividing a problem or system into smaller more manageable elements that focus on particular concerns. They are reconciled by the fact that both views are needed to understand systems and to engineer systems; focusing on only one or the other does not give sufficient understanding or a good overall solution. This dualism is closely related to the Systems Thinking Paradox described in [[What is Systems Thinking?]]. Rosen (1979) discussed “false dualisms” of systems paradigms that are considered incompatible but are in fact different aspects or views of reality. In the present context, they are thus reconcilable through yin yang harmonization. Edson (2008) emphasized viewpoints as an essential principle of systems thinking and specifically as a way to understand opposing concepts.
 
 
 
Derick Hitchins (Hitchins 2003), produced a “systems-lifecycle-theory” described by a set of 7 principles forming an integrated set which describe the creation, manipulation and demise of Engineered Systems.
 
 
 
These principles consider the factors which contribute to the stability and survival of man made systems in an environment.  Stability is associated with the principle of '''Connected Variety''' in which stability is increased by variety plus the '''cohesion''' and '''adaptability''' of that variety; and stability is limited by allowable relations, resistance to change and patterns of interaction.  Hitchins describes how interconnected systems tend to a '''cyclic progression''' in which variety is generated, dominance emerges to suppress variety, dominant modes decays and collapse and survivors emerge to generate new variety.
 
 
 
Guidance on how to apply many of these principles to engineered systems is given in the article [[Synthesizing Possible Solutions]] as well as in [[System Definition]] and other knowledge areas in Part 3 of this SEBoK.
 
  
===Prerequisite Laws of Design Science===
 
John Warfield (Warfield 1994) identified a set of laws of generic design science that are related to systems principles. Three of these laws are stated here:
 
 
#‘’Law of Requisite Variety’’: A design situation embodies a variety that must be matched by the specifications. The variety includes the diversity of stakeholders. This law is an application to design science of the Ashby (1956) Law of Requisite Variety, which was defined in the context of cybernetics and states that to successfully regulate a system, the variety of the regulator must be at least as large as the variety of the regulated system.
 
#‘’Law of Requisite Parsimony’’: Information must be organized and presented in a way that prevents human information overload. This law derives from Miller’s (1956) findings on the limits of human information processing capacity. Warfield’s structured dialog method is one possible way to help achieve the requisite parsimony.
 
#‘’Law of Gradation’’: Any conceptual body of knowledge can be graded in stages or varying degrees of complexity and scale, ranging from simplest to most comprehensive, and the degree of knowledge applied to any design situation should match the complexity and scale of the situation. A corollary, called the Law of Diminishing Returns, is that a body of knowledge should be applied to a design situation to the stage at which the point of diminishing returns is reached.
 
 
===Heuristics and Pragmatic Principles===
 
A heuristic is a common sense rule intended to increase the probability of solving some problem (WordWeb 2012b). In the present context it may be regarded as an informal or pragmatic principle. Maier and Rechtin (2000) identified an extensive set of heuristics that are related to systems principles. A few of these heuristics are stated here, and each is related to principles described above.
 
 
*Relationships among the elements are what give systems their added value. This is related to the ‘’Interaction’’ principle.
 
*Efficiency is inversely proportional to universality. This is related to the ‘’Leverage’’ principle.
 
*The first line of defense against complexity is simplicity of design. This is related to the ‘’Parsimony’’ principle.
 
*In order to understand anything, you must not try to understand everything (attributed to Aristotle). This is related to the ‘’Abstraction’’ principle.
 
An INCOSE working group (INCOSE 1993) defined a set of “pragmatic principles” for Systems Engineering. They are essentially best practice heuristics for engineering a system. A large number of heuristics are given. Three examples:
 
 
*Know the problem, the customer, and the consumer
 
*Identify and assess alternatives so as to converge on a solution
 
*Maintain the integrity of the system
 
 
Hitchins defines a set of SE principles which include principles of holism and synthesis as discussed above, plus principles describing how systems problems should be resolved which are of particular relevance to a [[Systems Approach Applied to Engineered Systems]]  (Hitchins 2009).
 
 
==References==
 
 
===Works Cited===
 
===Works Cited===
Ackoff, R. 1979. The Future of Operational Research is Past, ''J. Opl. Res. Soc.'', 30(2): 93–104, Pergamon Press.
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Hybertson, D. (2009). ''Model-Oriented Systems Engineering Science: A Unifying Framework for Traditional and Complex Systems'', Boca Raton, FL, USA: Auerbach/CRC Press.
  
Ashby, W.R. 1956. Requisite variety and its implications for the control of complex systems, ''Cybernetica'', 1(2):1–17.
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Hybertson, D. (2020 forthcoming). ''Systems Engineering Science''. Chapter in G. S. Metcalf, H. Deguchi, and K. Kijima (editors in chief). Handbook of Systems Science. Tokyo: Springer.
  
Bertalanffy, L. von. 1968. ''[[General System Theory: Foundations, Development, Applications]]''. Revised ed. New York, NY: Braziller.
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INCOSE (2014). “A world in motion: Systems engineering vision 2025.” International Council on Systems Engineering.
 
 
Bertalanffy, L. von. 1975. ''Perspectives on General System Theory''. E. Taschdjian, ed. New York: George Braziller.
 
 
 
Boardman, J. and B. Sauser. 2008. ''Systems Thinking: Coping with 21st Century Problems''. Boca Raton, FL: Taylor & Francis.
 
 
 
Cybernetics (Web Dictionary of Cybernetics and Systems). 2012. Principle of Parsimony or Principle of Simplicity. http://pespmc1.vub.ac.be/ASC/PRINCI_SIMPL.html
 
 
 
Edson, R. 2008. ''Systems Thinking. Applied. A Primer''. Arlington, VA, USA: Applied Systems Thinking (ASysT) Institute, Analytic Services Inc.
 
 
 
Erl, T. 2012. SOA Principles: An Introduction to the Service Orientation Paradigm. http://www.soaprinciples.com/p3.php
 
 
 
Greer, D. 2008. The Art of Separation of Concerns. http://aspiringcraftsman.com/tag/separation-of-concerns/
 
 
 
Griswold, W. 1995. Modularity Principle. http://cseweb.ucsd.edu/users/wgg/CSE131B/Design/node1.html
 
 
 
Hitchins D. K. 2003. Advanced systems thinking engineering and management.  Boston MA, Artech House
 
 
 
Hitchins, D. 2009. "What are the General Principles Applicable to Systems?" INCOSE ''Insight''. 12(4): 59-63.
 
 
 
Hoagland, M., B. Dodson, and J. Mauck. 2001. ''Exploring the Way Life Works''. Jones and Bartlett Publishers, Inc.
 
 
 
Holland, J. 1992. ''Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence''. Cambridge, MA: MIT Press.
 
 
 
Hybertson, D. 2009. ''[[Model-Oriented Systems Engineering Science]]: A Unifying Framework for Traditional and Complex Systems''. Auerbach/CRC Press, Boca Raton, FL.
 
 
 
IEEE. 1990. ''IEEE Standard Glossary of Software Engineering Terminology''. IEEE Std 610.12-1990, IEEE, September 1990.
 
 
 
IEP (Internet Encyclopedia of Philosophy). 2006. Yinyang (Yin-yang). http://www.iep.utm.edu/yinyang/
 
 
 
INCOSE 1993. ''An Identification of Pragmatic Principles -Final Report''. SE Principles Working Group, January 21, 1993. http://www.incose.org/productspubs/pdf/techdata/pitc/principlespragmaticdefoe_1993-0123_prinwg.pdf
 
 
 
Klerer, S. “System Management Information Modeling,''IEEE Comm'', Vol 31:No 5, May 1993, pp 38-44.
 
 
 
Klir, G. 2001. ''[[Facets of Systems Science]], 2nd ed.'' New York: Kluwer Academic/Plenum Publishers.
 
 
 
Lawson, H. 2010. ''A Journey Through the Systems Landscape''. London, UK: College Publications, Kings College, UK.
 
 
 
Lawson, H. and J. Martin. 2008. On the Use of Concepts and Principles for Improving Systems Engineering Practice. INCOSE International Symposium 2008, The Netherlands.
 
 
 
Lipson, H. 2007. Principles of modularity, regularity, and hierarchy for scalable systems. ''Journal of Biological Physics and Chemistry'' 7, 125–128.
 
 
 
Maier, M. and E. Rechtin. 2000. ''The Art of Systems Architecting, 2nd ed''. Boca Raton, FL: CRC Press.
 
 
 
Martin, R., E. Robertson, and J. Springer. 2004. ''Architectural Principles for Enterprise Frameworks''. Technical Report No. 594, Indiana University, April 2004. http://www.cs.indiana.edu/cgi-bin/techreports/TRNNN.cgi?trnum=TR594.
 
 
 
Miller, G. 1956. The magical number seven, plus or minus two: some limits on our capacity for processing information. ''The Psychological Review'', 63, 81–97.
 
 
 
Odum, H.1994. Ecological and General Systems: An Introduction to Systems Ecology (Revised Edition). University Press of Colorado.
 
 
 
Pattee, H. (ed.) 1973. ''Hierarchy Theory: The Challenge of Complex Systems''. New York: George Braziller.
 
 
 
Pearce, J. 2012. The Abstraction Principle. http://www.cs.sjsu.edu/~pearce/modules/lectures/ood/principles/Abstraction.htm [Posting date unknown; accessed June 2012.]
 
 
 
Rosen, R. 1979. Old trends and new trends in general systems research. ''Int. J. of General Systems'' 5(3): 173-184. [Reprinted in Klir 2001]
 
 
 
Sci-Tech Encyclopedia. 2009. Abstract Data Type. ''McGraw-Hill Concise Encyclopedia of Science and Technology, Sixth Edition'', The McGraw-Hill Companies, Inc. http://www.answers.com/topic/abstract-data-type.
 
 
 
SearchCIO. 2012. Abstraction. http://searchcio-midmarket.techtarget.com/definition/abstraction
 
 
 
Sillitto, H. 2010. Design principles for Ultra-Large-Scale (ULS) Systems. ''Proceedings of INCOSE International Symposium 2010'', Chicago, Ill.
 
 
 
Simon, H. 1996. ''The Sciences of the Artificial, 3rd ed''. Cambridge, MA: MIT Press.
 
 
 
Volk, T., & Bloom, J. W. (2007). The use of metapatterns for research into complex systems of teaching, learning, and schooling. Part I: Metapatterns in nature and culture. ''Complicity: An International Journal of Complexity and Education'', 4(1), 25—43 (http://www.complexityandeducation.ualberta.ca/COMPLICITY4/documents/Complicity_41d_Volk_Bloom.pdf).
 
 
 
Warfield, J.N. 1994. ''A Science of Generic Design''. Ames, IA: Iowa State University Press.
 
 
 
Wikipedia. 2012a. Modularity. http://en.wikipedia.org/wiki/Modularity
 
 
 
WordWeb. 2012a. Dualism. http://www.wordwebonline.com/en/DUALISM.
 
 
 
WordWeb. 2012b. Heuristic. http://www.wordwebonline.com/en/HEURISTIC.
 
 
 
WordWeb. 2012c. Principle. http://www.wordwebonline.com/en/PRINCIPLE.
 
  
 
===Primary References===
 
===Primary References===
Bertalanffy, L. von. 1968. ''[[General System Theory: Foundations, Development, Applications]]''. Revised ed. New York, NY: Braziller.
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None.
 
 
Hybertson, D. 2009. ''[[Model-Oriented Systems Engineering Science]]: A Unifying Framework for Traditional and Complex Systems''. Auerbach/CRC Press, Boca Raton, FL.
 
 
 
Klir, G. 2001. ''[[Facets of Systems Science]], 2nd ed.'' New York: Kluwer Academic/Plenum Publishers.
 
  
 
===Additional References===
 
===Additional References===
Francois, F. (ed.). 2004. ''International Encyclopedia of Systems and Cybernetics, 2nd ed''. K. G. Saur.
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None.
 
 
Meyers, R. (ed.). 2009. ''Encyclopedia of Complexity and Systems Science'' (10 vol. set). Springer.
 
 
 
Midgley, G. (ed.). 2003. ''Systems Thinking'' (4 Vol. Set). Sage Publications Ltd.
 
  
 
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<center> [[Concepts of Systems Thinking|< Previous Article]] | [[Systems Thinking|Parent Article]] | [[Patterns of Systems Thinking|Next Article >]] </center>
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<center>[[Emergence|< Previous Article]] | [[Systems Fundamentals|Parent Article]] | [[Systems Approach Applied to Engineered Systems|Next Article >]]</center>
 
 
 
 
  
[[Category:Part 2]][[Category:Topic]][[Category:Systems Thinking]]
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<center>'''SEBoK v. 2.1, released 31 October 2019'''</center>
{{DISQUS}}
 

Revision as of 20:02, 28 February 2020


Lead Author: Rick Adcock, Contributing Author: Duane Hybertson


This article forms part of the Systems Fundamentals knowledge area (KA). It considers future trends in SE and how these might influence the evolution of future fundamentals.

The SEBoK contains a guide to generalized knowledge about the practice of SE. It does not pass judgement on that knowledge. However, it can be useful in some cases to indicate which parts of the knowledge are rooted in existing practice and which point towards the future evolution of SE.

This article provides a sketch of how SE is changing and suggests how these changes may affect the future of systems engineering, the SEBoK, and the foundations in Part 2.

INCOSE Vision

The INCOSE Vision 2025 statement (INCOSE 2014) depicts some future directions in:

Broadening SE Application Domains

  • SE relevance and influence will go beyond traditional aerospace and defense systems and extend into the broader realm of engineered, natural and social systems
  • SE will be applied more widely to assessments of socio-physical systems in support of policy decisions and other forms of remediation

More Intelligent and Autonomous Systems

  • Systems of the future need to become smarter, self-organized, sustainable, resource-efficient, robust and safer
  • The number of autonomous vehicles and transportation systems needs to increase
  • Systems become more “intelligent” and dominate human-safety critical applications

Theoretical Foundations

  • SE will be supported by a more encompassing foundation of theory and sophisticated model-based methods and tools allowing a better understanding of increasingly complex systems and decisions in the face of uncertainty
  • Challenge: A core body of systems engineering foundations is defined and taught consistently across academia and forms the basis for systems engineering practice

In this article we will consider how the fundamentals of SE might need to evolve to support this vision.

How will SE Change?

In Types of Systems, we describe three general contexts in which a SE life cycle can be applied. In a product systemproduct system contextcontext, the outputs of SE focus on the delivery of technological systems. While such systems are designed to be used by people and fit into a wider problem-solving context, this context has been seen as largely fixed and external to SE. The service systemservice system context allows SE to consider all aspects of the solution system as part of its responsibility. This is currently seen as a special case of SE application largely focused on software intensive solutions. The enterprise systementerprise system context offers the potential for a direct application of SE to tackle complex socio-technical problems, by supporting the planning, development and use of combinations of service systems. While this is done, it can be difficult to connect to the product focused life cycles of many SE projects.

The role of the systems engineer has already begun to change somewhat due to the first two of the future trends above. Changes to the scope of SE application and the increased use of software intensive reconfigurable and autonomous solutions will make the service system context the primary focus of most SE life cycles. To enable this, most product systems will need to become more general and configurable, allowing them to be used in a range of service systems as needed. These life cycles are increasingly initiated and managed as part of an enterprise portfolio of related life cycles.

In this evolution of SE, the systems engineer cannot consider as many aspects of the context to be fixed, making the problem and possible solution options more complex and harder to anticipate. This also means the systems engineer has greater freedom to consider solutions which combine existing and new technologies and in which the role of people and autonomous software can be changed to help deliver desired outcomes. For such systems to be successful, they will need to include the ability to change, adapt and grow both in operation and over several iterations of their life cycle. This change moves SE to be directly involved in enterprise strategy and planning, as part of an ongoing and iterative approach to tackling the kinds of societal problems identified in the INCOSE vision.

This evolution of both the role and scope of SE will also see the system of systemssystem of systems aspects of all system contexts increase. We can expect system of systems engineeringsystem of systems engineering to become part of the systems engineering of many, if not most, SE life cycles.

Evolution of Fundamentals

These ongoing changes to SE place more emphasis on the role of autonomous agents in systems engineering, and agency will be an area of increased emphasis in the systems engineering and SEBoK of the future. Hybertson (2019) spells out in more detail the increased role of agents and agency in future SE. Moving from a total control model to a shared responsibility model changes the nature of engineering to something more like collective actualization, as proposed by Hybertson (2009 and 2019). Systems will represent a combination and interplay of technology and social factors, and they can range from technical product to service provider to social entity. In many cases they will be a socio-technical combination or hybrid.

The above trends have an impact on SE foundations, including technical aspects, social aspects, and ethical aspects. Inclusion of people in systems implies significant expansion of foundation sciences, to provide principles, theories, models, and patterns of the human, biological, social, and agent realm as well as the technical and physical realm. Emphasis on agents implies a revised conceptualization of system change, from the traditional model of mechanistic and controlled fixes and upgrades to a more organic change model that involves growth, self-learning, self-organizing, and self-adapting. Ethical considerations will include how to allocate responsibility for a system in a shared responsibility model. Further discussion of the expanded foundation and a list of foundation disciplines for future SE are presented in (Hybertson 2009 and 2019).

References

Works Cited

Hybertson, D. (2009). Model-Oriented Systems Engineering Science: A Unifying Framework for Traditional and Complex Systems, Boca Raton, FL, USA: Auerbach/CRC Press.

Hybertson, D. (2020 forthcoming). Systems Engineering Science. Chapter in G. S. Metcalf, H. Deguchi, and K. Kijima (editors in chief). Handbook of Systems Science. Tokyo: Springer.

INCOSE (2014). “A world in motion: Systems engineering vision 2025.” International Council on Systems Engineering.

Primary References

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Additional References

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SEBoK v. 2.1, released 31 October 2019