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Systems Engineering and
System Denitions
Version: 1.0
Issued on: 8 January 2019
AUTHOR TEAM
Hillary Sillitto, James Martin, Dorothy McKinney, Regina Griego, Dov Dori, Daniel Krob,
Patrick Godfrey, Eileen Arnold, Scott Jackson
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COPYRIGHT INFORMATION
This INCOSE Technical Product was prepared by the International Council on Systems Engineering
(INCOSE). It is approved by the INCOSE Technical Operations Leadership for release as an
INCOSE Technical Product.
Copyright (c) 2019 by INCOSE, published under Open Access.
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EXECUTIVE SUMMARY
The Fellows Initiative on System and Systems Engineering Denitions was established in 2016, to:
1. review current INCOSE denitions of SYSTEM and SYSTEMS ENGINEERING; and
2. recommend any changes necessary to align the denitions to current practice and to the aspirations of
INCOSE’s 2025 Vision.
This document presents the nal proposals from the initiative. It takes into account the extensive comments
received during the review of the previous draft in September 2018. The review was open to all INCOSE
members, and attracted over 350 individual comments and suggestions.
The three key recommendations – for denitions of systems engineering, engineered system, and a general
denition of system - are presented below, with a very brief contextual explanation. After the table of contents,
the main body of this document provides more explanation of these denitions, and also denes other specic
system types and categories that are important for the systems engineering community.
Systems Engineering is a transdisciplinary and integrative approach to enable the successful realization,
use, and retirement of engineered systems, using systems principles and concepts, and scientic,
technological, and management methods.
We use the terms “engineering” and “engineered” in their widest sense: “the action of working artfully to
bring something about”. “Engineered systems” may be composed of any or all of people, products, services,
information, processes, and natural elements.
An engineered system is a system designed or adapted to interact with an anticipated operational
environment to achieve one or more intended purposes while complying with applicable constraints.
Thus, an “engineered system” is a system – not necessarily a technological one - which has been or will be
“systems engineered” for a purpose.
Finally, a very general and inclusive denition of “system” is provided:
A system is an arrangement of parts or elements that together exhibit behavior or meaning that the individual
constituents do not.
Systems can be either physical or conceptual, or a combination of both. Systems in the physical universe
are composed of matter and energy, may embody information encoded in matter-energy carriers, and exhibit
observable behavior. Conceptual systems are abstract systems of pure information, and do not directly exhibit
behavior, but exhibit “meaning”. In both cases, the system’s properties (as a whole) result, or emerge from:
• the parts or elements and their individual properties; AND
• the relationships and interactions between and among the parts, the system and its environment.
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TABLE OF CONTENTS
EXECUTIVE SUMMARY 3
TABLE OF CONTENTS 4
SYSTEMS ENGINEERING 5
TRANSDISCIPLINARY APPROACH 5
INTEGRATIVE APPROACH 6
SYSTEMS PRINCIPLES AND CONCEPTS 6
ENGINEERING AND ENGINEERED 6
ENGINEERED SYSTEM 7
ENTERPRISES 7
SERVICES 7
DEFINITION OF SYSTEM: GENERAL CASE 8
PHYSICAL AND CONCEPTUAL SYSTEMS 8
PHYSICAL SYSTEMS 9
CONCEPTUAL SYSTEMS 9
PHYSICAL AND CONCEPTUAL COMPONENTS OF ENGINEERED SYSTEMS 10
THE CONSTRUCTIVIST PERSPECTIVE – SYSTEMS AS CONCEPTUAL MODELS OF REALITY 11
OPEN AND CLOSED SYSTEMS 11
NATURAL, ARTIFICIAL AND HYBRID SYSTEMS 12
SOCIAL AND SOCIO-TECHNICAL SYSTEMS 12
SPECIAL CASES – SUBTYPES AND EXEMPLARS RELEVANT TO SYSTEMS ENGINEERING 13
BIOLOGICAL AND LIVING SYSTEMS 13
VIABLE AND SELF-REPLICATING SYSTEMS 13
COMPLEX SYSTEMS 14
ANTICIPATORY SYSTEMS 14
REFERENCES. 15
APPENDIX: TYPICAL FEATURES OF SYSTEMS ENGINEERING 16
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SYSTEMS ENGINEERING
Systems Engineering is a transdisciplinary and integrative approach to enable the successful realization,
use, and retirement of engineered systems, using systems principles and concepts, and scientic,
technological, and management methods.
We use the terms “engineering” and “engineered” in their widest sense: “the action of working artfully to
bring something about”. “Engineered systems” may be composed of any or all of people, products, services,
information, processes, and natural elements.
Systems Engineering focuses on:
• establishing, balancing and integrating stakeholders’ goals, purpose and success criteria, and dening
actual or anticipated customer needs, operational concept and required functionality, starting early in the
development cycle;
• establishing an appropriate life cycle model, process approach and governance structures, considering
the levels of complexity, uncertainty, change, and variety;
• generating and evaluating alternative solution concepts and architectures;
• baselining and modelling requirements and selected solution architecture for each phase of the
endeavor;
• performing design synthesis and system verication and validation;
• while considering both the problem and solution domains, taking into account necessary enabling
systems and services, identifying the role that the parts and the relationships between the parts play with
respect to the overall behavior and performance of the system, and determining how to balance all of
these factors to achieve a satisfactory outcome.
Systems Engineering provides facilitation, guidance and leadership to integrate the relevant disciplines and
specialty groups into a cohesive effort, forming an appropriately structured development process that proceeds
from concept to production, operation, evolution and eventual disposal.
Systems Engineering considers both the business and the technical needs of customers with the goal of
providing a quality solution that meets the needs of users and other stakeholders, is t for the intended
purpose in real-world operation, and avoids or minimizes adverse unintended consequences.
The goal of all Systems Engineering activities is to manage risk, including the risk of not delivering what the
customer wants and needs, the risk of late delivery, the risk of excess cost, and the risk of negative unintended
consequences. One measure of utility of Systems Engineering activities is the degree to which such risk is
reduced. Conversely, a measure of acceptability of absence of a System Engineering activity is the level of
excess risk incurred as a result.
TRANSDISCIPLINARY APPROACH
Transdisciplinarity is described in Wikipedia as an approach which “crosses many disciplinary boundaries to
create a holistic approach.” This emphasis on a holistic approach distinguishes it from cross-disciplinary, which
focuses mainly on working across multiple disciplines while allowing each discipline to apply their own methods
and approaches. Systems engineering is simultaneously cross-disciplinary and transdisciplinary. (The cross-
disciplinary aspect is discussed in the next section on the Integrative Approach.)
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The transdisciplinary approach originated in the social sciences. It “transcends” all of the disciplines involved,
and organizes the effort around common purpose, shared understanding and “learning together” in the context
of real-world problems or themes. It is usable at any level, from complex to simple, from global to personal. A
transdisciplinary approach is needed when the problem cannot readily be “solved” and the best that can likely
be achieved is instead a “resolution.” The participants in the endeavor need to “transcend” their particular
disciplinary approach to instead come to some overall useful compromise or synergistic understanding that
their disciplines cannot come to on their own (even when working together in a normal integrative approach
with other disciplines).
INTEGRATIVE APPROACH
The integrative approach has long been used in systems engineering and usually involves either
interdisciplinary (e.g.. integrated product teams) or multi-disciplinary (e.g.. joint technical reviews) methods.
The integrative approach by itself can be adequate where the situation is not overly complex and there are
smaller numbers of stakeholders potentially impacted. The integrative approach can be used when dealing
with a highly precedented situation that has been encountered before and a path to the solution can be readily
identied and understood (albeit there will still be many challenges along the way, technical and otherwise).
The integrative approach includes the traditional multi-disciplinary and inter-disciplinary approaches commonly
used in systems engineering practice. The transdisciplinary approach may be needed in unprecedented
situations or where there is a signicant degree of complexity involved. See Madni (2018).
SYSTEMS PRINCIPLES AND CONCEPTS
Systems principles and concepts are the ways that systems thinking and the systems sciences infuse systems
engineering. Examples of some of the principles, concepts and supporting tools are: mental models, system
archetypes, holistic thinking, separation of concerns, abstraction, modularity and encapsulation, causal loop
diagrams, and systems mapping. (The Systems Engineering Body of Knowledge describes many of these,
and more, at https://www.sebokwiki.org/wiki/Principles_of_Systems_Thinking).
ENGINEERING AND ENGINEERED
Both ancient and modern denitions of Engineering allow for the wide interpretation intended here. For
example, Google dictionary denes Engineering in two ways:
1. the branch of science and technology concerned with the design, building, and use of engines,
machines, and structures.
2. the action of working artfully to bring something about.
And Wikipedia:
• Engineering is the creative application of science, mathematical methods, and empirical evidence to the
innovation, design, construction, operation and maintenance of structures, machines, materials, devices,
systems, processes, and organizations.
• The term engineering is derived from the Latin ingenium, meaning “cleverness” and ingeniare, meaning
“to contrive, devise”.
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ENGINEERED SYSTEMS
An engineered system is a system designed or adapted to interact with an anticipated operational
environment to achieve one or more intended purposes while complying with applicable constraints.
The following may be useful as a working denition that focuses on what it “is”: An engineered system is a
composite of people, products, services, information, and processes (and possibly natural components) that
provides a capability that satises a stated customer need or objective.
Thus, an “engineered system” is a system – not necessarily a technological one - which has been or will be
“systems engineered” for a purpose. Note that the required behavior of such a system might be achieved by
inuence and self-organization, rather than by top-down direction.
The people component can be individuals, roles, organizations, organizational units, governance structures,
etc. The products component can be hardware, software, rmware, data, facilities, etc. The services
component can be business services, information services, application services, infrastructure services, etc.
The information component can be individual information items, information categories, information structures,
documentation, knowledge elements, etc. The processes component can be procedures, methods, techniques,
work instructions, policies, directives, etc. Capability is an ability to do something in the anticipated operational
environment.
The category of “engineered system” includes the sub-categories of products, services and enterprises.
Services and enterprises usually depend on technological products but are essentially forms of socio-technical
systems.
ENTERPRISES
“Enterprise” is intended to mean a large undertaking, especially one of large scope, complication and risk – “a
complex web of interactions distributed across geography and time” (Rebovitch & White, 2011). We do not
just mean a large organization, since an enterprise often has multiple organizations that participate in the
enterprise to the extent that each organization will derive some benet from its participation. An enterprise is an
endeavor usually requiring special initiative and boldness. Not all large activities are enterprises since their size
does not necessarily entail taking large risk or dealing with a complicated situation.
SERVICES
“Service” is intended to mean actions taken to satisfy needs of individuals or organizations. The term service
initially was used in the last century to describe actions which involved no tangible products at all. Early in this
century (per Wikipedia at https://en.wikipedia.org/wiki/Managed_services) “managed services” emerged as a
business model. The “service economy” (per Wikipedia at https://en.wikipedia.org/wiki/Service_economy) has
resulted in an evolution in the meaning ascribed to “service”: “The old dichotomy between product and service
has been replaced by a service-product continuum. Many products are being transformed into services. The
Cambridge dictionary at https://dictionary.cambridge.org/us/dictionary/english/service says service is “work
done or help provided, especially for the public or for a person or an organization.”
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DEFINITION OF SYSTEM: GENERAL CASE
A system is an arrangement of parts or elements that together exhibit behavior or meaning that the individual
constituents do not.
“Parts” is the more general term, going back to Aristotle’s phrase “the whole is more than the sum of the parts”.
“Elements” has become established as the preferred term in recent systems engineering usage. The two terms
are sometimes used interchangeably, but in some domains they have specic meanings (e.g. mechanical part,
chemical element, part of a whole, part played by an actor or role).
The concept of “behavior or meaning of the whole not exhibited by the individual constituents” is often
referred to as “emergence”, and is the dening characteristic of “systems” that distinguishes them from “non-
systems”. However, we avoid using the term in this denition because of the risk of confusion with the other
notion of “emergence”, which denotes surprise where such properties “emerge” that could not be foreseen or
anticipated.
The goal of systems engineering is, then, to select, adjust, and arrange the parts or elements so as to achieve
the desired whole-system properties when the system of interest is used as intended.
PHYSICAL AND CONCEPTUAL SYSTEMS
Systems can be either physical or conceptual, or a combination of both. Systems in the physical universe
are composed of matter and energy, may embody information encoded in matter-energy carriers, and exhibit
observable behavior. Conceptual systems are abstract systems of pure information, do not directly exhibit
behavior, but exhibit “meaning”. In both cases, a system’s properties result, or emerge from:
• the parts or elements and their individual properties; AND
• the relationships and interactions between and among the constituents, the system and its environment;
where:
• a “property” is an attribute, quality, or characteristic of something;
• “between” refers to binary interactions or relationships (binary means between two constituents),
whereas “among” refers to relationships and interactions involving more than two constituents (in graph
theory, such a relationship involving N parts or elements is referred to as “N-ary”);
• It is often argued that in physical systems we only need to consider interactions, but relationships
are also important (e.g.. is part of, is assembled to, is vulnerable to, is owned by, costs, weighs....);
interactions can be considered as a special type of relationship, but because of their importance in
systems engineering, they are mentioned explicitly.
We can consider the structural ontology of physical and conceptual systems to be the same, at the
fundamental level of parts and relationships – this is what allows us to model physical systems using
conceptual systems; but the process ontology is quite different. A physical system can perform and manage
processes internal to the system; whereas any change to, or use of, a conceptual system involves processes
performed by external physical systems interacting with the conceptual system.
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PHYSICAL SYSTEMS
A physical system is an arrangement of parts or elements that together exhibit behavior that the individual
constituents do not. (This denition includes biological systems and living systems.)
Physical systems are composed of matter and energy. Information is embedded in physical systems, and is
stored and transported, in matter/energy carriers. The behavior of physical systems manifests itself as ows
and exchanges of matter, energy and information, and interaction through force elds. The emergent property
by which physical systems can be identied is that they perform processes to transform matter, energy and
information in ways that their individual parts cannot. (NB “physical systems” includes biological and living
systems, because they exist in the physical universe.)
Systems exhibit variable degrees of coupling and cohesion. A physical system may be a single complex object,
such as an organism; or an “object aggregate”, a collection of objects that are inter-related in a way that makes
them distinct from the rest of the universe. To be considered a system, the collection must exhibit observable
properties not exhibited by the parts, separately or in other combinations: typically, transformation processes
that cause observable effects, and binding processes that maintain observable cohesion.
Our knowledge of physical systems is ultimately limited by what can be observed, and is further limited by
what observations we have chosen to make. Rosen (2012) explains this very clearly in terms of “the modelling
relation” between models and observables. Our (inevitably partial) understanding of physical systems is
expressed as models and narratives. (Allen & Starr, 2017)
“Observability” of a real system does not mean it is being, or has been, observed. It simply requires information
about the system’s state and effects to be accessible, in principle, to a notional sensor or “meter”. What is
observed depends a) on what an “observer” can, and chooses to, measure; b) on the frame of reference
used for the observation; and c) (as Allen and Starr (2017) emphasize) on the scale of the measurement. Not
all phenomena of interest can be observed directly; in practice, many are observed indirectly, essentially by
inference due to cause-effect chaining.
CONCEPTUAL SYSTEMS
Conceptual systems are composed of information or knowledge. Information in a conceptual system can be
stored or transported in a physical system by being encoded into the matter or energy states of the physical
system. Thus:
A conceptual system is a “knowledge structure” and is composed of information and knowledge elements. The
elements of a conceptual system are related to each other but do not interact with each other. The conceptual
system interacts with physical systems which create, modify and interpret it. Its emergent property is meaning,
as intended by its creator or editor. This depends on the semantics (meaning of the elements) and syntax
(meaning of the relationships between the elements). The perceived meaning will match the intended meaning
only if the semantics and syntax are shared between creator, editor and interpreter. A conceptual system can
help us to interpret the state (past, present, or expected future) of the universe.
A conceptual system is an arrangement of parts or elements that together exhibit meaning that the individual
constituents do not.
Thus:
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A conceptual system only exists as long as it is hosted in a matter/energy carrier, whether that is, for example,
a computer memory, a book manuscript, tablets of stone, an idea in a biological consciousness, or information
stored in DNA. Once the last record, consciousness or preserved pattern of the concept has disappeared,
the concept has disappeared as well. (When the last copy of a book is burnt, the last le deleted, and the last
person who read it has died or succumbed to dementia, that “conceptual system” has ceased to exist.)
Thus, conceptual systems are generated, evolve and decay not unlike physical systems. A practical case in
point is computer software, an important kind of conceptual system, where the evolution of the code tends
to be accompanied by an increase in entropy until the code becomes unmaintainable. The term “entropy” is
often used in this context. The thermodynamic analogy holds well in terms of the increasing effort required to
maintain software and keep it working as it becomes more disorganized.
The appearance or behavior of physical systems often embodies and conveys meaning. For example,
poisonous animals may have distinctive markings as “warnings” to predators, and engineered products convey
meaning with labels, the relationships between parts, or provide obvious affordances for interaction.
PHYSICAL AND CONCEPTUAL COMPONENTS OF ENGINEERED SYSTEMS
Engineered systems include products, services and enterprises. Services and enterprises usually depend
on technological products but are essentially forms of socio-technical systems. “Engineered systems” may
include hardware, software, rmware, processes, people, organizations, governance structures, information,
knowledge, techniques, facilities, services, other support elements, and (usually modied) natural elements.
An important task in the “systems engineering” of engineered systems is therefore to establish or conrm
the operational concept: how the system will be used to create value, while avoiding unintended negative
consequences.
Thus, Systems Engineering involves both conceptual and physical systems; and engineered systems almost
invariably include both physical and conceptual elements. In such cases, an engineered system can be
thought of as a physical system and a conceptual system combined.
Even in the case of a pure “physical system”, we make our systems usable, for example, by overlaying
concepts that are embedded in the design as symbols, colors, shapes and other signs that convey meaning to
the user on how to use the system, how to turn it on and off, which parts of the system are safe to touch, when
is there some condition to be aware of, and so on.
Systems engineering often produces conceptual systems - models of the current “problem situation”, the
perceived problem or opportunity, and the envisaged future solution and the effect it will have on the problem
situation.
Once the conceptual model of the proposed solution is demonstrated to have sufcient likelihood of solving
or ameliorating the problem situation, that conceptual model becomes the blueprint for the physical system.
The conceptual model of the proposed solution can be used as a reference point for the “as intended” system.
The physical “as built” system can be compared to the conceptual model, and each may inform the other. The
relative timing of the model activity and the build activity will depend on the balance of risk and reward for each
project.
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Once the physical system is deployed, we examine the effects produced by the system in the real world, and if
necessary, update the conceptual models to reect reality. These updated conceptual models are then used as
the basis for changes to the system to meet changing needs and circumstances.
In the context of Systems Engineering, another very important form of conceptual system is the “Process
Instruction”. This includes computer software, and also policy and process documents that tell people how to
make, use, support and retire the system of interest. A process instruction is a conceptual system; whereas a
process is a transformation of matter, energy or information, done to or by a physical system.
THE CONSTRUCTIVIST PERSPECTIVE –
SYSTEMS AS CONCEPTUAL MODELS OF REALITY
In the constructivist worldview, a system is not something presented to the observer, it is something to be
recognized by an observer. In such cases, the word “system” does not refer to existing things in the real world
but rather to a way of organizing our thoughts about what is real and make sense. This constructivist view
of reality states that systems do not exist in the real world independently of the human mind. In this view, a
system cannot be understood by analysis of the parts because of their complex interactions and because
purpose or meaning can only be perceived in the whole. A system (from this perspective) is in itself always
an abstraction chosen with the emphasis on either structural or functional aspects. A system is then anything
unitary enough to deserve a name. A system is thus represented by a set of variables sufciently isolated to
stay constant long enough for us to discuss it as a coherent whole. This notion of a system is one way we,
as humans, can organize our thoughts about what we see, or conceptualize, about how relationships and
interactions between parts or elements result in outcomes.
OPEN AND CLOSED SYSTEMS
A system can be either closed or open:
This is the denition commonly used in the system literature, which we have chosen to follow. This is different
from the thermodynamics denition, which differentiates between systems that are “closed” (no material ow)
and “isolated” (no material or energy ow).
The physical universe, as we currently understand it, appears to be a closed system.
This a fundamental systems science denition. It differs from the meaning of “open system” in IT and related
elds, where the term is used in the sense of “open system architecture” that allows for a vendor-independent,
non-proprietary, computer system or device design based on ofcial and/or popular standards.
All physical systems of interest to systems engineering are open systems. However, there can be special
cases in systems engineering where it is convenient to treat a system as if it is closed, if there are no
signicant external relationships or interactions to contend with.
A closed system is a system that is completely isolated from its environment.
An open system is a system that has ows of information, energy, and/or matter between the system and its
environment, and which adapts to the exchange.
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Entropy increases in a closed system. In open systems, the entropy is kept low, or decreases, essentially
at the expense of entropy increasing somewhere else, so the entropy of the universe continues to increase.
Thus, systems tend to maintain their organization at the expense of increased disorder elsewhere, which is a
common cause of unintended consequences.
It follows that a more fundamental denition of “system” could be “a persistent region of low entropy (= high
organization) in physical or conceptual space-time”. Then, it would follow that “systemness is the phenomenon
that allows regions of organization to persist in a dissipative universe”.
NATURAL, ARTIFICIAL, AND HYBRID SYSTEMS
An articial system is a system constructed by human agents, or otherwise caused by them to come into
being.
A natural system is a system that occurs in nature without intervention by human agents.
We now introduce our preferred terminology to distinguish between naturally occurring and human-made
systems, while noting that many systems are a hybrid of the two, so this is not a binary classication.
Natural systems exhibit properties such as viability, resilience, and self-organization that offer exemplars for
engineered systems. Biomimicry refers to the practice of using natural systems as patterns for articial ones.
Human agents can be humans, or they can be processes, methods or tools created by humans that effect
change indirectly to create the articial system.
A hybrid system is a system with both natural and articial elements, or a natural system inuenced (e.g.. by
selective breeding) or modied (e.g.. by genetic engineering) by intentional agents.
An engineered system means a system - articial or hybrid, conceptual and/or physical - that was properly
systems-engineered in the sense of the denition. Otherwise a human-made system is articial or hybrid, but
not engineered. Of course, there can be the case of a badly engineered system – such as a system where the
operational environment is not well anticipated and the “applicable constraints” poorly selected.
SOCIAL AND SOCIO-TECHNICAL SYSTEMS
Some authorities maintain that there are three kinds of system: natural, social and “articial”.
In this viewpoint, a social system is any system made up primarily of intentional agents, which is not driven
by natural forces but rather the force of willpower and cunning and various other intentional qualities; while an
articial system is one composed of deliberately created artefacts.
The term “human activity systems” is often used for social systems where the intentional agents are humans.
Groups of agents working to a common purpose are not unique to humans; many animals live in social
systems, and there is a spectrum of social systems, ranging from those composed of humans where the social
system is deliberately constructed and maintained and can adapt rapidly, to simpler ones such as ant colonies
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where the “intentional behavior” appears to be hard-wired in genetic material.
Systems Engineering takes place within a social system, and typically produces part or all of a socio-technical
system, a system with closely coupled social and technical parts.
There are many denitions in the literature for these and related system types; we do not attempt to offer rm
denitions for these categories.
SPECIAL CASES – SUBTYPES AND EXEMPLARS RELEVANT
TO SYSTEMS ENGINEERING
BIOLOGICAL AND LIVING SYSTEMS
Biological and Living systems (Miller, 1978) are examples of a large and important class of dynamic open
systems, which exchange energy and waste with their environment to maintain themselves, at the expense of
increasing entropy in their environment.
Living systems exploit matter and energy as well as information and knowledge elements. Their behavior
manifests itself through ows of material, energy, and information; but also through collective knowledge that
is transferred from generation to generation. Living systems have both conceptual and physical aspects, but
they are unique in that their emergent behaviors are associated with learning and adaptation. Human systems
are especially accomplished among living systems in their ability to express meaning in the form of complex
language and use that to drive emergent behaviors of other physical, conceptual, and living systems to their
goals.
VIABLE AND SELF-REPLICATING SYSTEMS
There is a signicant literature - Beer’s (1972) Viable Systems Model, Hitchins (2007) - on “viable systems”,
using the term in the sense of “capable of existence and development as an independent unit”, or “capable
of surviving or living successfully, especially under particular environmental conditions”. Successful biological
and organizational systems are viable in this sense. Viability in this sense is also a desirable attribute of many
engineered systems. Hence, we offer a denition:
A self-replicating system is an open system that, within certain life cycle limits, can: reproduce itself by
exchanging matter, energy and information either with its environment or with a second system of a compatible
type; and pass on its attributes to the reproduced child system.
A viable system is an open system that, within certain environmental limits, can: sustain itself by exchanging
matter, energy and information with its environment; detect and survive external threats; maintain and repair
its internal organization in the face of disruption; and adapt to a changing environment (e.g.. by evolving its
capabilities); while maintaining its internal equilibrium (homeostasis).
Living systems, as well as being “viable”, are also self-replicating and capable of adaptation and evolution:
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COMPLEX SYSTEMS
Of numerous ways of dening complex systems, this one seems useful and relevant to SE:
A complex system is a system in which there are non-trivial relationships between cause and effect: each
effect may be due to multiple causes; each cause may contribute to multiple effects; causes and effects
may be related as feedback loops, both positive and negative; and cause-effect chains are cyclic and highly
entangled rather than linear and separable.
The non-trivial nature of the relationships in a complex system make the whole system non- deterministic,
ambiguous or chaotic (in the mathematical sense that a very small change in initial conditions may produce a
very large change in outcome), even if the individual relationships within the system are well understood.
Complexity as dened above is a property of the system of interest. Complexity is also created in the wider
system comprising the system of interest and its stakeholders when the system is not fully understood, and
when different stakeholders have different partial understandings of the system and of other stakeholders’
concerns. A major goal of Systems Engineering is to reduce this “perceived complexity” by establishing shared
and valid models of the system, in order to improve stakeholders’ knowledge and understanding of the system
and its context.
An example of cyclic cause and effect is the biological process of mutualistic symbiosis, in which each of a
pair of systems uses the other’s waste as raw material for its own processes. The systems import energy from
the environment to sustain the symbiotic processes, so the second law of thermodynamics is not violated. The
“Circular Economy” takes this concept and applies it to industrial value chains, to turn them into value loops
that are closed cycle apart from import of energy. Waste from one process is the feedstock for the next. If the
energy comes from the sun, the value loop can be sustainable as long as energy is available from the sun.
The INCOSE Complexity Primer (https://www.incose.org/docs/default-source/ProductsPublications/a-
complexity-primer-for-systems-engineers.pdf) provides a concise introduction to complex systems.
The difference between Complicated and Complex is discussed in, for example, Snowden and Boone (2007),
and the INCOSE Complexity Primer (INCOSE, 2015). Complicated systems can be viewed as knowable
and deterministic, and once developed their conguration can be “frozen”; whereas complex systems are
not fully knowable or deterministic, may be dynamically recongurable, and continue to co-evolve with their
environment throughout their life cycle.
ANTICIPATORY SYSTEMS
Finally, systems covered by Rosen’s (1985, 2012) concept of “anticipatory systems” are ubiquitous in the
natural world, and increasingly relevant to SE as we move towards intelligent and autonomous systems. An
anticipatory system’s present behavior depends upon anticipated ‘‘future states’’ or ‘‘future inputs’’ generated
by an internal predictive model. The following denition is an interpretation, not Rosen’s original.
An anticipatory system is a physical system that has an internal model of itself and its environment and an
internal decision-making function, enabling it to anticipate potential changes in the environment and make
appropriate adaptations to be ready for the anticipated change.
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REFERENCES
Allen & Starr (2017) Hierarchy – Perspectives for Ecological Complexity, Chicago University Press, 2017
Beer S (1972) Brain of the Firm, Allen Lane, The Penguin Press, London, 1972
Hitchins D (2007) Systems Engineering – a 21st Century Systems Methodology, Wiley, 2007
INCOSE (2014) INCOSE Systems Engineering Vision 2025 – a world in motion, INCOSE, 2014
INCOSE (2015) Complexity Primer for Systems Engineers, INCOSE, 2015
Madni A (2018) Transdisciplinary Systems Engineering: Exploiting Convergence in a Hyper-Connected World,
Springer, 2018
Miller G (1978) Living Systems, McGraw-Hill, New York, 1978
Rebovitch & White (2010) Enterprise Systems Engineering - Advances in the Theory and Practice p.4, CRC
Press, Taylor & Francis, 2010
Rosen R (1985, 2012) Anticipatory Systems: Philosophical, Mathematical, and Methodological Foundations,
2nd Ed., Springer, 2012
Snowden and Boone (2007), A Leader’s Framework for Decision Making, Harvard Business Review, Nov 2007
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APPENDIX: TYPICAL FEATURES OF SYSTEMS ENGINEERING
Systems Engineering considers and balances the business, technical, personal and societal needs of the
system’s stakeholders, including customers, beneciaries, users, owners, and relevant third parties, with the
goal of providing a quality solution that is t for its intended purpose in real-world operation. The scope is the
total or “whole system” solution, not just the engineered artifacts that may be key elements of the solution.
Business needs deal with the factors that justify expenditure of time and resources on the activities that occur
during the various stages of a system.
Systems Engineering (SE) focuses on ten key activities:
1. establishing stakeholders’ success criteria and concerns, and dening actual or anticipated customer
needs and required functionality, early in the development cycle, and revising them as new information is
gained and lessons are learned;
2. investigating the solution space, proposing alternative solution and operational concepts, weighing their
value (viability, utility, benet at cost) and selecting the optimal or most appropriate concept(s);
3. architecting a solution or set of solutions based on the selected concept(s) while considering potential
concepts of employment and usage;
4. modelling (or otherwise evaluating) the solution at each relevant phase of the endeavor, considering both
normal and exceptional scenarios, and an appropriate diversity of viewpoints, in order to:
a. establish required capability and performance;
b. increase condence that the solution will work as expected and required, while avoiding or
minimizing undesirable unintended consequences;
c. ensure the solution is resilient and can evolve if required to adapt to anticipated or possible changes
in the user needs and operational environments;
d. provide ongoing prediction and assessment of system effectiveness and value;
5. dening and managing the interfaces, both within the system and between the system and the rest of the
world (noting that increasingly, systems engineering is conducted in a brown-eld rather than a green-
eld environment, so legacy systems may be a major or key part of the overall solution);
6. establishing appropriate process and life cycle models that consider complexity, uncertainty, change and
variety, and implementing system management and governance processes for both development and
through-life use and disposal;
7. proceeding with detailed design synthesis, integration, and solution verication and validation (ensuring
the solution is t for the intended purpose) while considering the complete problem (including aspects of
dependability such as safety, security, reliability, availability, logistic support, and disaster recovery), all
necessary enabling systems and services, and end-of-life processes (e.g.. transition to a replacement
system, recycling of the retired one, nuclear decommissioning and waste disposal…);
8. providing the SE knowledge and information required by all stakeholder groups to ensure coherence
of the whole endeavor – typically including a vision statement, operational concepts, business drivers,
analyses and recommendations for decision support and the business case, architecture denition,
organizational policies and processes, required properties and interfaces of the system and its elements
(including common standards to ensure interoperability), verication and validation criteria, analysis
and interpretation of test and evaluation results, anticipated operational usage, and appropriate system
congurations for different scenarios;
9. supporting transition to use, considering all aspects including people, processes, information and
technology;
10. periodically re-evaluating status, risks and opportunities, stakeholder feedback, observed or anticipated
unintended consequences, and anticipated system effectiveness and value, and recommending any
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appropriate corrective, mitigation or recovery actions to ensure continuing system success. Such
activities during the operational phase can include upgrade activities, obsolescence management,
maintenance and repair activities, manufacturing changes, changing operational processes, user
training, instituting metrics and incentives, assessing information quality and integrity, and making other
changes to the system.
SE provides guidance, facilitation and leadership to integrate all the disciplines and specialty groups into a
team effort, forming an appropriately structured and coherent development process that proceeds from concept
to production (if relevant), operation, evolution and eventual disposal.
SE is essentially collaborative in nature, working with and facilitating collaboration between all contributors to
system success, recognizing the need to respect diverse points of view.
• In some projects and in some organizations, SE may include a strong governance, technical
management and resource management component.
• In other projects and organizations, SE may have an almost entirely technical, advisory and “glue” role, if
appropriate management and implementation structures already exist.
• SE may need to be applied at multiple levels of a complex project, program or enterprise.
• The roles, responsibilities and accountabilities of SE, and how SE will interact with its internal and
external stakeholders, should be documented in a management plan.
Fundamentally, SE is a learning journey; and the output of SE is information, and shared models. SE
synthesizes and provides the information required to describe the solution system, and to enable its successful
realization and use.
SE aims to provide effective solutions to complicated, complex and unprecedented problems, integrating
the efforts of engineering and other disciplines and specializations. A high leverage task in the “systems-
engineering” of engineered systems is to establish or conrm the operational concept: how the system will be
used to create value, while avoiding negative consequences.
The difference between Complicated and Complex is discussed in, for example, Snowden and Boone (2007),
and the INCOSE Complexity Primer (INCOSE, 2015). Complicated systems can be viewed as knowable
and deterministic, and once developed their conguration can be “frozen”; whereas complex systems are
not fully knowable or deterministic, may be dynamically recongurable, and continue to co- evolve with their
environment throughout their life cycle.
Most 20th century engineered systems were complicated; most 21st century engineered systems will be
complex. In complex situations, we need to apply SE to the “ecosystem transformation” as well as to individual
projects.
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