Systems Science

This Knowledge Area (KA) provides a guide to the major developments in systems science which is an interdisciplinary field of science that studies the nature of complex systems in nature, society, and science. Grounded in systems thinking, and based on theory and practice, it aims to develop interdisciplinary foundations applicable in a variety of areas, such as engineering, biology, medicine and social sciences. This knowledge is not specific to Systems Engineering, but is part of a wider systems body of knowledge. We have not attempted to capture all of the system knowledge here, but to identify those aspects relevant to the systems engineering body of knowledge.

Topics

The topics contained within this knowledge area include:

• History of System Science
• System Methodology
• Groupings of Systems
• Complexity
• Emergence

Machine vs System Age Thinking

Many attribute the notion of thinking about the whole to the Greek philosophers, exemplified by the work of Aristotle in examining multiple discipline related aspects in what is termed metaphysics. The explosion of knowledge in the natural and physical sciences during the Enlightenment of the 18th and 19th centuries made the move away from this natural philosophy approach to the creation of specialist disciplines inevitable. The only way for science to advance was for scientists to become expert in a narrow field of study. As disciplines emerged they created their own models and views of reality, which become increasingly specialized and associated with a field of study. The creation of educational structures to pass on this knowledge to the next generation of specialists perpetuates the fragmentation of knowledge into the present day (M’Pherson 1973).

Along with this increasing specialization of knowledge and education, the majority of western scientific study in the 19th century was based upon Descartes' notion of reductionism and closed system , sometimes call Machine Age, thinking (Flood 1999). This approach forms models based on the study of things in isolation and the establishment of rules on how they relate to each other. Unfortunately, this also led to a rational science movement, popularized by Popper (Popper 1972), which rejects any phenomena which do not fit with this rational view as not worthy of study.

While these ideas of specialist knowledge and rational analysis have provided a useful model through which a vast amount of scientific knowledge has been gained, they can also be a barrier to our ability to gain knowledge across disciplines and outside of the closed system view. The systems movement has its roots in two areas of science: the biological-social sciences; and a mathematical-managerial base stemming first from cybernetics and later from organizational theory. Both of which have developed around an open system and systemic thinking approach.

Open system theory considers an organism as a complex entity composed of many parts with an overall integrity, co-existing in an environment. In an open system the organism's structure is maintained, or adapts, through a continual exchange of energy and information with its environment.

Development of System Thoery

systems thinking is an approach to understanding or intervening in systems, based on the principles and concepts of systems. In the Systems Thinking KA we give some basic definitions of systems thinking and the systems theory which supports it.

The development of these theoretical ideas to a point where they can be consider be part of the cannon of Systems Thinking is like any other branch of science not a straight forward of linear process. general system theory (GST) (von Bertalanffy, 1968) enables comparisons between systems that rely on different technologies, judging the goodness or completeness of a system, and developing domain-independent systems approaches which can form the basis of disciplines such as Systems Engineering. While many researchers and practitioners have created GST concepts, these tend to be a stepping stone to theories and approaches. This situation is made worse by the variety of domains and disciplines in which systems research is conducted and reported.

While the System of System-Concepts (glossary) presented in the Systems Thinking Knowledge Area is a powerful set of ideas for better understanding all kinds of systems it is not rigourous or complete.

This Knowledge area describes the most important movements in Systems Science and presents a guide to the overlapping and sometimes contraditory theories it has created and used.

Three specific areas of systems research have been highlighted and discussed in more detail as of particlar interest to the Systems Engineering community:

• Grouping of Systems and the idea of a System of Systems
• The different aspects of system complexity and how they after a systems approach
• The different views of emergence and how they affect a systems approach

References

Works Cited

Ackoff, R.L. 1971. "Towards a System of Systems Concepts". Management Science. 17(11).

Bertalanffy, L. von. 1968. General System Theory: Foundations, Development, Applications, Revised ed. New York, NY, USA: Braziller.

Flood, R.L. 1999. Rethinking the Fifth Discipline: Learning within the Unknowable. London, UK: Routledge.

M’Pherson, P, K. 1974. "A Perspective on Systems Science and Systems Philosophy." Futures 6(3) (June 1974): 219-239.

Popper, K. R. 1979. Objective Knowledge, 2nd edition. Oxford, UK: Oxford University Press.

Primary References

Checkland, P. 1999. Systems Thinking, Systems Practice. New York, NY, USA: John Wiley & Sons.

Hitchins, D. 2007. Systems Engineering: A 21st Century Systems Methodology. Hoboken, NJ, USA: John Wiley & Sons.

Hitchins, D. 2009. "What are the General Principles Applicable to Systems?" Insight. 12(4).

Page, S.E. 2009. Understanding Complexity. The Great Courses. Chantilly, VA, USA: The Teaching Company.

Sheard, S. A. and A. Mostashari. 2008. "Principles of Complex Systems for Systems Engineering." Systems Engineering. 12(1): 295-311.

Additional References

No additional references have been identified for version 0.75. Please provide any recommendations on additional references in your review.

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