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The Representations and Practices of the Discipline of Systems Engineering 2016 Conference on Systems Engineering Research The representations and practices of the discipline of systems engineering Stephen B. Johnson* Department of Mechanical and Aerospace Engineering, University of Colorado, Colorado Spings, Colorado Springs, CO 80918, USA Dependable System Technologies, LLC, Broomfield, CO 80020 Abstract This paper is the second of two publications that define the motivations, theoretical foundations, representations, and processes for a formalization of systems engineering (SE) called the “Discipline of Systems Engineering (DSE).” The first paper, called “Theoretical Foundations for the Discipline of Systems Engineering,” describes the problems of Traditional Systems Engineering (TSE) that this new approach strives to improve upon, the core ideas of the new approach summarized as a set of theoretical “bases,” and then derives a set of principles from these bases. From these bases and principles, this paper defines the goals and strategies of the new approach. It then describes the representations required for the new approach. Finally, this paper explains how to use these representations to reproduce with higher quality some typical products of current SE, and to create new knowledge and products that TSE either has difficulty producing, or does not produce. © 2016 Stephen B. Johnson. Keywords: state; model; goal; requirement; control; value; knowledge; constraint; preference; intention; organization; institution; failure; anomaly; system health management; traceability. 1. Introduction This paper is the second of two publications that define the motivations, theoretical foundations, representations, and processes for a formalization of systems engineering (SE) called the “Discipline of Systems Engineering (DSE).” The first paper, called “Theoretical Foundations for the Discipline of Systems Engineering,”1 describes the problems of Traditional Systems Engineering (TSE) that this new approach strives to improve upon, the core ideas of the new approach summarized as a set of theoretical “bases,” and then derives a set of principles from these * Tel.: 720-887-6246 E-mail address: [email protected] ® 2016 Stephen B. Johnson Stephen B. Johnson 2 bases. From these bases and principles, this paper begins by defining the goals and strategies of the new approach. It then describes the representations required for the new approach. Lastly, this paper explains how to use these representations to reproduce with higher quality, lower cost, and reduced schedules some typical products of current SE, and to create new knowledge and products that TSE either has difficulty producing, or does not produce. The “Theoretical Foundations” paper is assumed as a foundation for the concepts, models, and processes described in this publication. That paper argues that with ever-increasing system complexity, TSE provides insufficient system dependability, which is directly related to development cost overruns and schedule slips. This is a symptom of its dependence on natural language documentation. By contrast, classical engineering disciplines (CEDs) such as control theory and electrical engineering use formal physical/mathematical theories applied to the system in question through in models and simulations. Within their domains, CEDs produce results that are typically much more reliable, on schedule and within budgets much more frequently than occurs for the entire system when integrated by TSE. Postulating that this difference is largely due to the formal nature of CEDs and how this improves communication compared to TSE, DSE strives to emulate CEDs. To do this, DSE uses seven theoretical bases: Systems Theory, Value Theory, Model, State, Goal, Control, and Knowledge. From these DSE elaborates a suite of 25 principles, which will not be listed here. However, these will be used to form a set of strategies, representations, and practices in this paper. 2. Predictive Basis and Principles Since the publication of the Theoretical Foundations paper, one new “basis” has been identified: the “predictive basis.” The purpose of engineering, to paraphrase Karl Marx, is not to understand the world, but to change it. Engineering is a means by which a vision of a novel product that does not yet exist is created and built. As engineering inherently intends to create a “new future,” predictions about that future are inherent and essential. Several kinds of prediction are common, particularly for the familiar quad of cost, schedule, reliability (or more generally, dependability), and performance. As the future is inherently uncertain, a direct implication is the use of probabilistic techniques that can account for uncertainties about the system, its environment, and its “internal and external contexts.” These “contexts” refer to the organizations that design and build the product (the “internal” context) and external factors as policy, law, economics and culture that influence how the product is built and used. Conversely, the new product can influence these external factors, but cannot control them. As this “predictive basis” is new to the theory of DSE (though obviously not new in TSE or engineering in general), the principles are also new. Two have been postulated. These include the following. Prediction of the future is necessary to enable control of the means by which the envisioned future system is realized. Typical predictions required for DSE are of performance, dependability, cost, and schedule. 3. The purposes of systems engineering Historically, engineers created SE primarily to reduce the probability of complex system failure, and secondarily to create a better or ideally optimal design to achieve a system’s goals, all while attempting to develop the system as quickly as possible.2,3 Later, SE was integrated with systems management, which also supported management’s desire for predictable costs and schedules. TSE and DSE have similar purposes, which are denoted next. A primary purpose of SE is to optimize system performance against given system preferences and constraints. A primary purpose of SE is to integrate knowledge across institutional and disciplinary boundaries. A primary purpose of SE is to prevent system failure. A primary purpose of SE is to develop a system as quickly as possible, given a set of resources. A primary purpose of SE is to support effective cost and schedule prediction. 4. The strategies of DSE With the purposes, bases, principles, and goals described above, DSE applies a variety of strategies, which are described in this section. Stephen B. Johnson 3 4.1. System theory strategies DSE applies the following strategies derived from system theory. DSE divides its space of representation into the system, the system’s environment, and the system’s internal and external contexts. In hierarchical representations, DSE concepts are typically applied recursively to each level of the hierarchy. The system is the item being designed, assessed, built, and operated. It is the entity engineered to achieve one or more purposes. The environment is the physical, logical, and human environment in which the system is operated. The internal context includes the organizations that design, assess, build, verify and validate the system; these are controllable by project management and systems engineers. The external context refers to organizations that provide guidance and resources to these organizations, and other factors often beyond direct control of any organization, such as economic and political influences and constraints. Over the life of a system, there can be changes to the system itself, to its operational environment, and to its internal and external contexts. All of them influence a system’s purposes, and to the judgment of how well or poorly those purposes are being achieved. The recursive strategy is typical of systems. One frequently finds the same idea, such as what “the system” actually is or what constitutes cause or effect, being applied in different ways to the same physical components or behaviors. This is often due to people having control of, or being interested in different parts of the system. As an example, for an organization that builds a system component, that component is “the system” of most relevance for them. They can and should apply DSE strategies and concepts to their component in a manner equally valid as those in charge of the entire larger system. DSE’s concepts, practices, and terminology must allow for these differences of point of view and should enable accurate communication of information across them. 4.2. Value theory strategies DSE applies the following strategies related to value theory. DSE prefers to construct von Neumann-Morgenstern (vN-M) utility functions whenever possible. When it is not possible to construct vN-M utility, other goals, constraints, or uses of the system can be used to define system goals and preferences. Specification of requirements should be delayed as long as practicable during system design and development, in favor of negotiable preferences. Von Neumann-Morgenstern utility functions4 were the starting point for the development of game theory, and is now the basis for an active thread of engineering research in what is often called value theory. This research is based on the idea that to make rational decisions from human preferences, one must create a metric of value that is based on a single axis of scalar numbers. For example, money measured in dollars, euros, or some other currency is a common way in which humans use a single
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