W. Clifton Baldwin

Taxonomy of increasingly complex systems

Systems engineers are responsible for systems ranging from the very simple to the extremely complex. The various types of systems create a need for differentiation of properties and identification using some common nomenclature. While other system taxonomies exist, we propose a unique classification mechanism which utilises a finite set of characteristics. Well-defined attributes provide a basis to develop unambiguous mathematical descriptions in future work. Application of the classification scheme will help employ the appropriate systems engineering methodology to systems in development.

A typology of systems paradoxes

Philosophers have studied paradoxes for millennia. The term paradox is appearing increasingly outside of philosophy, and researchers seek to understand them in common situations. By understanding these phenomena, systems engineers may develop better strategies to deal with them when encountered in business or projects. However, what is meant by the term systems paradox and are there different types? Towards this goal, this paper will present definitions of systems from systems science and paradox from philosophy in a quest to define systems paradox. A paradox that impacts some objective of a system is designated a systems paradox. Then a typology of systems paradoxes will be proposed and described using set theory. Various examples provide a demonstration of the typology.

Revisiting “The Meaning of Of” as a Theory for Collaborative System of Systems

At the 2006 IEEE International Conference on Systems of Systems Engineering, Boardman and Sauser presented a set of characteristics based on an integrative review of the literature. These characteristics are the foundation of the Boardman–Sauser system of systems (SoS) theory. We accept this theory as the basis of collaborative SoS and desire a means to validate this assertion. While numerous simulations have been published, the target SoS is usually a specific implementation. These specialized simulations produce results applicable primarily to the system under study but not necessarily SoS in general. Simulating the mathematical model of the Boardman–Sauser SoS theory in the form of an agent-based model produces results that can be compared with chemical reactions. This paper contends that the formation of molecules from atoms is an analog of systems forming any collaborative SoS, which we call our molecule organization model. The result is a supported logical argument that validates the Boardman–Sauser SoS theory as definitive of a generic SoS with behavior applicable to collaborative SoS. This paper seeks to provide a unique contribution to the SoS body of knowledge by increasing our understanding of collaboration in an SoS, so we may better understand their health, maintenance, replication, and evolution.

Controlling Design Complexity with the Monterey Phoenix Approach

As system designs grow ever more complex, our ability to assimilate, process, and then make equally complex decisions is challenged to keep pace. Intricate relationships within each system, among interoperating systems, and between each system and the external elements of its environment are themselves challenged by the sheer number of moving pieces. The actual number of permutations of configurations and possible behaviors for our systems now far exceeds that which a human is capable of predicting without automated assistance. This paper demonstrates how the Monterey Phoenix (MP) approach can be used to decompose a complex problem into smaller, more manageable models. When taken separately (using human cognition), these models are easier to read and write, and when taken together (using automation), they increase awareness of the possible behaviors that are latent in a design, so that many more use cases can be exposed. Additionally, this paper utilizes a commercial flight scenario to provide an example of how a manually crafted, moderately complex activity model can be restructured into smaller, separate models that are simpler to work with, and that expose additional behavior in simulation, which is not present in the original activity model.