The posed minor defect principle holds that minor system elements with defects may contribute to disasters if the elements are part of major system functionality. Eight cases, with nearly 2000 fatalities, all of which illustrate this principle. This conclusion calls for, at a minimum, increased emphasis on detailed design and system integration.

This paper reviews the literature and addresses an important topic and a frequently asked question on the differences, relationships, and causality of system adaptability and system resilience. It discusses areas that are potentially unique to each concept, and the significant common areas. We depict the relationship through a comparison chart and a Venn Diagram that addresses both the unique areas and areas of synergy. We present different types and representative case studies/examples for both adaptive systems and resilient systems. This is a comprehensive study from the Resilient System working group and System Adaptability working group in INCOSE for answering the frequent question on the difference and relationship between adaptability and resilience and will be useful to help the systems engineering community to understand each concept and apply techniques accordingly. We also identify the value of applicable resilience and adaptability techniques for stakeholders and show directions for further investigations and subsequent studies.

INSIGHTVolume 18, Issue 1 p. 14-18 SPECIAL FEATURE A Generic State-Machine Model of System Resilience Scott Jackson, Scott Jackson jackson@burnhamsystems.net Search for more papers by this authorStephen Cook, Stephen Cook stephen.cook@incose.org Search for more papers by this authorTimothy L. J. Ferris, Timothy L. J. Ferris timothy.ferris@incose.org Search for more papers by this author Scott Jackson, Scott Jackson jackson@burnhamsystems.net Search for more papers by this authorStephen Cook, Stephen Cook stephen.cook@incose.org Search for more papers by this authorTimothy L. J. Ferris, Timothy L. J. Ferris timothy.ferris@incose.org Search for more papers by this author First published: 21 April 2015 https://doi.org/10.1002/inst.12003Citations: 11AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Citing Literature Volume18, Issue1April 2015Pages 14-18 RelatedInformation

ABSTRACT The application of systems engineering (SE) to commercial aircraft presents a set of requirements and processes unique to the commercial aircraft industry. SE can be applied to new, derivative, and change‐based aircraft design. The concept of an aircraft system extends beyond the aircraft itself. The hierarchy of the aircraft architecture is embedded in present‐day processes. Aircraft life‐cycle functions follow the classical life‐cycle functions. The aircraft‐level functions can be flowed to aircraft and subsystem level functions and requirements. Requirements which receive more attention than others include performance, safety, cost, reliability, and weight, not necessarily in that order. Economic requirements include both market‐driven and particular customer requirements. Certification guidelines for the aircraft, including its software, incorporate SE principles. Strong SE management is required for the successful development of commercial aircraft. This paper is based on the author's book Systems Engineering for Commercial Aircraft (1997).

There has been a heightened awareness of an increased risk of suicidality among individuals with autism spectrum disorder (ASD) due to high rates of suicidal ideation (SI) in this population (11–66

Systems engineering (SE) is a transdisciplinary discipline that links all the engineering disciplines involved in defining a system throughout its lifecycle. As such, SE involves heuristics to a significant extent. A heuristic relates to a formulation based on experts' experience serving as a guide in the investigation or solution of a problem. To be usable, heuristics should be memorable and pithy. A team of INCOSE Fellows created the INCOSE Systems Heuristics Application Repository , or I‐SHARE in short, in which over 600 SE‐related heuristics are curated and shared, covering subjects that include SE competencies, lifecycle stages, expertise, operational domains, and system attributes. In this paper, we describe the I‐SHARE, the motivation and stages of its creation and compilation, and ways through which this knowledge base can be an invaluable service to the SE community.

This research note presents an approach to assure that a system meets the basic property of holism. Holism is the principle that the whole is different from, and may be greater than, the sum of its rationally separable parts. This approach suggested in this research note focuses on the functions of the system and on the parts of the system. The approach incorporates the basic property of a system, namely, its hierarchy, and the functions, requirements and solutions for each layer of the hierarchy. The approach then integrates the system layers through their primary property, their functions. The premise of the paper is that a system is holistic if its functions are integrated into a single set of functions. This approach is consistent with the accepted concept of the systems approach because it incorporates the basic system concepts of functions and hierarchy and integrates those with the accepted properties of requirements and solutions. The approach is grounded in practicality because it provides a methodology to show that any real-world system meets the criterion of holism. The approach is applicable to physical systems, abstract systems and systems of systems.

Individuals with autism spectrum disorder (ASD) engage in less physical activity than typically-developing peers. This can result in serious negative consequences for individual well-being and may contribute to the physical, behavioral, and emotional challenges associated with ASD. This study explored the potential benefits of trainer-led, individualized, physical fitness sessions specialized for ASD. Eleven individuals (ages 7–24 years) with ASD were assessed at baseline and following 15 fitness sessions. Participants demonstrated improvements in core and lower-body strength and reductions in restricted and repetitive patterns of behavior, along with non-significant but marked reductions in issues with daytime sleepiness. Results suggest the merit of specialized fitness programs and emphasize the need for larger and more rigorous research studies on this topic.

Among the most advanced concepts in the twenty-first century is systems science. The principles of systems science can be used to describe any large scale and complex systems such as offshore platforms, their design, their management, and their operation. The premise of systems science is that the entire system and the associated organization is a single system operating as a whole and whose parts interact with each other to accomplish a purpose. The purpose of the offshore system is the recovery of petroleum and natural gas (using stringent and proven health, safety, and environmental controls) to meet the world energy needs.

The concepts below have been synthesized from a number of sources, which are themselves summaries of concepts from other authors. Ackoff (1971) proposed a system of system concepts as part of general system theory (GST); Skyttner (2001) describes the main GST concepts from a number of systems science authors; Flood and Carlson (1993) give a description of concepts as an overview of systems thinking; Hitchins (2007) relates the concepts to systems engineering practice; and Lawson (2010) describes a system of system concepts where systems are categorized according to fundamental concepts, types, topologies, focus, complexity, and roles.

ion 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). Boundary 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). 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). Dualism Recognize dualities and consider how they are, or can be, harmonized in the context of a larger whole (Hybertson 2009). Encapsulation Hide internal parts and their interactions from the external environment (Klerer 1993; IEEE 1990). 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. Holism 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, capabilities, and behavior of a system are derived from its parts, from interactions between those parts, and from interactions with other systems (Hitchins 2009 p. 60). Layer Hierarchy 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). Leverage 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). Modularity Unrelated parts of the system should be separated, and related parts of the system should be grouped together (Griswold 1995; Wikipedia 2012a). Network 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). 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 to operations and requirements. Regularity Systems science should find and capture regularities in systems, because those regularities promote systems understanding and facilitate systems practice (Bertalanffy 1968). 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 of the system (Odum 1994). Separation of Concerns A larger problem is more effectively solved when decomposed into a set of smaller problems or concerns (Erl 2012; Greer 2008). 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. 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). Synthesis 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, so solving the problem that prompted its creation” (Hitchins 2009: 120). View Multiple views, each based on a system aspect or concern, are essential to understand a complex system or problem situation. One critical view is how concern relates to properties of the whole (Edson 2008; Hybertson 2009). 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 propert ies, dependencies, and tradeoffs among these principles. Edson (2008) related many of the above principles in a structure called the conceptagon, which he modified from the work of Boardman and Sauser (2008). Edson also provided guidance on how to apply these principles. Not all principles apply to every system or engineering decision. Judgment, experience, and heuristics (see below) provide understanding into which principles apply in a given situation. Several principles illustrate the relation of view with the dualism and yin yang principle, for example, holism and separation of concerns. These principles appear to be contradictory but are in fact dual ways of dealing with complexity. Holism deals with complexity by focusing on the whole system, while separation of concerns divides 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; specifically, as a way to understand opposing concepts. Derick Hitchins (2003) produced a systems life cycle theory described by a set of seven principles forming an integrated set. This theory describes 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. Stability is limited by allowable relations, resistance to change, and patterns of interaction. Hitchins describes how interconnected systems tend toward a cyclic progression, in which variety is generated, dominance emerges to suppress variety, dominant modes decay 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 topic Synthesizing Possible Solutions, as well as in System Definition and other knowledge areas in Part 3 of the SEBoK. Prerequisite Laws of Design Science John 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 1. embodies a variety that must be matched by the specifications. The variety includes the diversity of stakeholders. This law is an application of the 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 2. organized and presented in a way that prevents human information overload. This law derives from Miller’s findings on the limits of human information processing capacity (Miller 1956). Warfield’s structured dialog method is one possible way to help achieve the requisite parsimony. ‘’Law of Gradation’’: Any conceptual body of 3. 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, states that a body of knowledge should be applied to a design situation at 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: 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 International Council on Systems Engineering (INCOSE) working group (INCOSE 1993) defined a set of “pragmatic principles” for systems engineering (SE). They are essentially best practice heuristics for engineering a system. For example: Know the problem, the customer, and the consumer Identify and assess alternatives to converge on a solution Maintain the integrity of the system Hitchins defines a se

This chapter examines how human-created systems in civil and organizational domains maintain their required capability to function effectively in the face of adversity and identifies the factors that enable these systems to remain resilient. Typical civil systems include power grid systems and transportation systems, such as aircraft. Organizational systems include enterprises and governments. Adversities include natural disasters and terrorist attacks. A recurring pattern in all domains is the ability to anticipate and prepare for adversity. Another recurring pattern is the ability for the system to adapt to the adversity. Some resilient systems can withstand adversity and then degrade gracefully to a satisfactory state, return to a prior state, or change to some new state. Both domains utilize a set of techniques to achieve resilience. These recurring patterns are common to both domains and are essential to the resilience of diverse systems.

This topic is part of the Systems Approach Applied to Engineered Systems knowledge area (KA). It describes knowledge related to the deployment, sustainment, and use of a solution that may have been developed through the activities described in the Implementing and Proving a Solution topic. Discussion of how a deployed system fits into commercial and acquisition relationships is present in Introduction to System Fundamentals. Any of the activities described below may also need to be considered concurrently with other activities in the systems approach at a particular point in the life of a system-of-interest (SoI).