Transdisciplinary Perspectives on Complex Systems

The practice of complex system engineering has been hampered by a lack of rigorous and consistent language across disciplines. Terms such as “complexity” and “system of systems” have been subject to various verbal definitions that are inconsistent from author to author, and from field to field. Rich literatures in philosophy, management and engineering have the promise of mutual reinforcement and support, but the lack of consistency makes correlation difficult. In this Chapter, we provide a comprehensive review of the literature around the questions of system complexity and systems of systems (SoS). Extending previous work in this area, we offer a package of four set theoretic equations expressing the essential attributes used in constructing taxonomies of system types. They are consistent with the set of attributes evolved by system engineering researchers up to this point, and together they provide a complete description of the taxonomy of systems up to but not including complex SoS. Finally, we examine the attribute of emergence. It remains an open question whether emergence can actually exist in a system made up entirely of engineered components. This has eloquently been posed as the question of emergence versus ignorance—is an unpredictable result truly a feature of the complex system, or merely an artifact of our lack of understanding? We conclude by offering several mathematical approaches that may have promise in extending this system of definitions to include emergence as well.

Systems engineering is especially difficult today because the systems that are being engineered are more complex than ever before. But why does it matter that systems are complex, and what should the engineering community do about complexity? Although there is a great deal of discussion about precisely what complexity is, and how complexity can be identified and measured, this chapter skirts those issues to focus on how engineers should cope with complexity. The critical aspect of complexity to the systems engineer is the way it interferes with prediction of design outcomes, a fundamental obstacle to the essentially deterministic methods of systems engineering. Transdisciplinary strategies are proposed for engineering complex systems, particularly a structured approach that encourages experimentation, at least on a small scale, to win some insight into the outcomes of complex behavior.

This chapter [Portions of the analysis and results of this continuing research project were presented at the Fourth International Conference on Inverse Problems, Design and Optimization (IPDO–2013), Albi, France (Hilton and D’Urso, Paper ID 06290, 2013).] reports on a comprehensive optimized inverse analysis protocol that has been formulated at the complex multifunctional, multiphysics and multidisciplinary total system of systems (SoS) level leading to trans-disciplinary convergence for the entire designer vehicle with provisions for optimized/tailored aerodynamics, stability, control, materials, structures, propulsion, performance, sizing, weight, cost, etc. The protocol for these inverse problems is based on a generalized calculus of variations approach, including but not limited to Lagrange multipliers.

The possibility of achieving such a generalized unified approach has become a reality through the double advent of modern computer software and hardware. First, the availability of such programs as MATLAB™, MATHEMATICA™, MAPLE™, etc. make it feasible to carry out the detailed large scale analytical enterprises, such as multiple symbolic integrations, differentiations, matrix algebra, etc. Secondly, the online operational advent of the University of Illinois at Urbana-Champaign National Center for Supercomputing Applications/National Science Foundation (UIUC NCSA/NSF) Blue Waters™, the sustained peta-scale (10¹⁵ flops/s) computing system (Anonymous, http://​www.​ncsa.​uiuc.​edu/​BlueWaters/​, 2011; Anonymous, http://​www.​ncsa.​illinois.​edu/​News/​Stories/​Kramer/​, 2009; Anonymous, About blue waters, 2014; Anonymous, https://​bluewaters.​ncsa.​illinois.​edu, 2013), will allow efficient solutions of the necessary hundreds of millions of simultaneous nonlinear algebraic equations describing parameters for an entire air or space flight vehicle (Through this chapter the term vehicle is used to denote atmospheric and space flight vehicles unless otherwise specified.) or other large scale SoS that may contain numerous rigid, specified and/or flexible sub-systems as well as aerodynamics, cost, manufacturing, performance, propulsion, stability and control, etc.

Illustrative examples are limited to structures, solid mechanics and aero-viscoelastic examples that represent currently available solutions. Additional parts of the entire complex SoS are under investigation and will be reported in archival journals in future years.

Systems do not simply pop into existence. They progress through lifecycle phases of creation, production, operations, and disposal. The issues leading to undesirable and unpredicted emergent behavior are set in place during the phases of creation and production and realized during the operational phase, with many of those problematic issues due to human interaction. We propose that the idea of the Digital Twin, which links the physical system with its virtual equivalent can mitigate these problematic issues. We describe the Digital Twin concept and its development, show how it applies across the product lifecycle in defining and understanding system behavior, and define tests to evaluate how we are progressing. We discuss how the Digital Twin relates to Systems Engineering and how it can address the human interactions that lead to “normal accidents.” We address both Digital Twin obstacles and opportunities, such as system replication and front running. We finish with NASA’s current work with the Digital Twin.

The purpose of this chapter is to explore a new approach to systems management through an adaptive method that informs systems competency. The approach is bundled into a management tool, the CX Tool^©. The CX Tool is a visual management method that measures and adapts between the reality of the current state and the desired condition of the future state for systems such as human and information. In managing these systems, the state of congruence between organizational thinking and doing is measured based on selected metrics and with consideration of the nature of systems as emergent, complex, adaptive and interrelated. Within the realms of thinking and doing, specific system elements are examined and measured for metric quality and the state of congruence in four tiers. For example, in Tier One, the CX Tool allows for visual diagramming of a system’s current and future states. It also enables analyses within, between and/or among system elements based on singular inputs. And further, in Tier Two, the CX Tool accounts for multiple inputs. In doing so, this tool informs specific points of improvement and draws also out the adaptive influences of specific changes in the system upon deployment. The CX Tool is based on the theoretical foundations of several scholars. In the following discussion of human-initiated systems, therefore, new consideration is provided in regard to management strategies for better agency to:

Theories of systems, systems management, organizational sense making and system dissonance/congruence are presented to frame the foundations of the CX Tool. In short, the CX Tool seeks to add to the body of knowledge on systems management.

This chapter reviews insights on complex sociotechnical systems theory and proposes that the theory can benefit by adopting and extending concepts and methods from complexity theory. Such expansion will better inform organizational analysis in the context of complex systems engineering. Sociotechnical systems theory integrates an understanding of group dynamics with an appreciation for the technical environment in which organizational work is carried out, pointing to the complex interdependencies among social dynamics and technical systems. This chapter will review sociotechnical systems theory and suggest extensions drawing on well-established research on the social psychology of groups, as well as contemporary research from network science, and emerging frameworks from epidemiological and sociophysics research to provide a more comprehensive perspective on complex systems. An explicit integration of complexity theory and sociotechnical systems theory reveals new strategies to enhance modeling and understanding of complex social and technical interdependencies that impact systems engineering.

Systems are increasing in complexity as the world becomes more globally connected. The pervasiveness of information, education, and connectivity has forced individuals to devise new ways to think about problems. Most complex problems no longer reside neatly within the boundaries of a single discipline. As a result, addressing these problems requires problem solvers to broaden their perspectives and to think across disciplines. This chapter explores the concept of complementarity as a motivation for seeking transdisciplinary solutions to problems. Through the lens of complementarity, the case will be made for the utility of adopting a transdisciplinary perspective to modern, complex problems unable to be addressed using a single discipline. It then provides three unique perspectives (engineering, global health, and education) through which to view the analysis of a singular problem, that of emerging health issues such as the current Ebola virus disease crisis in the world. Next, these perspectives will be examined using cognitive mapping, forming an approach to adopt a transdisciplinary perspective, which yields insights not possible by each of the disparate disciplines alone. This approach is then demonstrated on a sample problem. Finally, conclusions and recommendations for future research are identified.

This chapter explores the burden of complexity by considering the possibility that the system design community has been struggling with the consequences of a deep-rooted assumption concerning our core definition of a system.Recent research into individual and organizational mindsets suggests that “big assumptions” represent beliefs in our mental models of the world that are viewed as accurate representations of the way things are and are taken for granted as true. The intent of this chapter is to offer an alternative treatment of complexity in system design by extracting our community’s viewpoint—the mental construction we perceive the world through—such that we are able to look at it less subjectively. To do so, the chapter frames a normative comparative study to assess the ability of any viewpoint to successfully facilitate system design. The assurance of the design process and the correctness and completeness of the solution to resolve the need form the basis of the evaluation criteria. The study compares two viewpoints against the evaluation criteria: a prevailing viewpoint derived from our deep-rooted assumption, and a viewpoint built around an alternative view of systems. The results show that the prevailing viewpoint becomes increasingly unsatisfactory as systems exceed the capability and capacity of the practitioner to comprehend, and therefore brings into question the validity of our deep-rooted assumption for the design of complex systems. The analysis further suggests that the system design community has been actively compensating for the insufficiency of its models, which can create a perception of complexity as significant to design. On the other hand, the alternative viewpoint demonstrates theoretical agreement with the evaluation criteria regardless of scale and scope and shows the potential for systematic solution derivation, suggesting that the alternate definition of systems might form a more suitable basis for the design of “complex” systems. The seemingly insurmountable problems we experience with the burden of “complexity” may have a path to resolution, but only if we choose to accept the implications that our struggles may be self-imposed.

Offering a broad external market variety at competitive prices is one of the main challenges in the global competition among mechanical engineering branches. Reducing variety and thus variety induced complexity cost has evolved to become one of the crucial global success factors. The aim of this study is to get insights on variety induced complexity cost effects and to elaborate on how these effects can be influenced by modular product development. Firstly, general causes and effects of variety are described portraying their trans-disciplinary nature. Next, the state of the art in reducing variety by modular product development is explained. Hypotheses on cost effects of variety induced complexity are introduced; and industrial cases from Germany are evaluated in order to support the hypotheses. During these empirical case studies, an integrated approach for developing modular product families by including various corporate disciplines is applied. This trans-disciplinary procedure aims to reduce variety over the whole product life by modularization. The results obtained and their potential effects on complexity cost are presented and discussed. Based on the analysis of these cases, an approach for Early Phase Estimation of Complexity Cost (EPECC) is developed. This approach helps assess trans-disciplinary complexity cost effects of different modular concept alternatives in early design phases. Furthermore, the effect of branch specific lot sizes on complexity cost is illustrated. Factors related to the successful use of these effects in branches and segments with high and low lot sizes are shared from industrial and consultancy practices. This contribution is authored by a team of academicians, consultants, and industrial executives.

In complex systems the need to solve problems is constant. Numerous techniques for solving specific problems developed in various areas are clearly insufficient. Humanity needs multidisciplinary generic methods to find solutions to specific problems. Organizations need to learn to use and develop their ability to solve problems in an objective way. The use of certain methodologies and analytical techniques for problem solving allows to analyze larger number of possible solutions, create more creative solutions, saving time and resources.

Problem solving is an iterative process, assuming a solid base of trans-disciplinary scientific principles complemented by empirical data, creativity, good sense, familiarity with problems that arise in practice, knowledge of the laws, rules and regulations. In the modern world, a process of decision making should take into account, in varying proportions, the combination of traditional parameters with some other concerns as well as security, economic, environmental factors, social impact and other related ideas.

It is absurd to require a “correct solution” to any problem. In fact, a “good” solution today may well turn out to be “bad” solution tomorrow, either because of the development of knowledge in a given period of time, either due to other structural or social change.

The concept of "Ideality” is one of the fundamental principles of the Theory of Creative Problem Solving, better known by its acronym TRIZ. The ideality is the goal that drives organizations improve all organizational systems, making them faster, better and at lower cost. Any system comes close to more and more from ideality when the number of beneficial functions increases and/or when the number of harmful functions decreases.

Some techniques and analytical tools of TRIZ methodology can contribute to accelerate and improve the process of problem solving and to increase an ideality of complex systems in almost all human activities.