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An Introduction to Reliability and Maintainability Engineering. Hawkins, D. Kiemele, M. Schmidt, and R. Most civil infrastructure systems are service systems. Systems engineering focuses on analyzing and eliciting customer needs and required functionality early in the development cycle, documenting requirements, then proceeding with design synthesis and system validation while considering the complete problem, the system lifecycle.
This includes fully understanding all of the stakeholders involved. Oliver et al. Depending on their application, although there are several models that are used in the industry, all of them aim to identify the relation between the various stages mentioned above and incorporate feedback. Examples of such models include the Waterfall model and the VEE model. System development often requires contribution from diverse technical disciplines.
In an acquisition, the holistic integrative discipline combines contributions and balances tradeoffs among cost, schedule, and performance while maintaining an acceptable level of risk covering the entire life cycle of the item. This perspective is often replicated in educational programs, in that systems engineering courses are taught by faculty from other engineering departments, which helps create an interdisciplinary environment. The need for systems engineering arose with the increase in complexity of systems and projects,   in turn exponentially increasing the possibility of component friction, and therefore the unreliability of the design.
When speaking in this context, complexity incorporates not only engineering systems, but also the logical human organization of data. At the same time, a system can become more complex due to an increase in size as well as with an increase in the amount of data, variables, or the number of fields that are involved in the design. The International Space Station is an example of such a system. The development of smarter control algorithms , microprocessor design, and analysis of environmental systems also come within the purview of systems engineering.
Systems engineering encourages the use of tools and methods to better comprehend and manage complexity in systems. Some examples of these tools can be seen here: . Taking an interdisciplinary approach to engineering systems is inherently complex since the behavior of and interaction among system components is not always immediately well defined or understood.
Defining and characterizing such systems and subsystems and the interactions among them is one of the goals of systems engineering. In doing so, the gap that exists between informal requirements from users, operators, marketing organizations, and technical specifications is successfully bridged. One way to understand the motivation behind systems engineering is to see it as a method, or practice, to identify and improve common rules that exist within a wide variety of systems.
Such studies are underway to determine the effectiveness and quantify the benefits of systems engineering. Systems engineering encourages the use of modeling and simulation to validate assumptions or theories on systems and the interactions within them. Use of methods that allow early detection of possible failures, in safety engineering , are integrated into the design process. At the same time, decisions made at the beginning of a project whose consequences are not clearly understood can have enormous implications later in the life of a system, and it is the task of the modern systems engineer to explore these issues and make critical decisions.
No method guarantees today's decisions will still be valid when a system goes into service years or decades after first conceived. However, there are techniques that support the process of systems engineering. Examples include soft systems methodology, Jay Wright Forrester 's System dynamics method, and the Unified Modeling Language UML —all currently being explored, evaluated, and developed to support the engineering decision process.
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Education in systems engineering is often seen as an extension to the regular engineering courses,  reflecting the industry attitude that engineering students need a foundational background in one of the traditional engineering disciplines e. Undergraduate university programs explicitly in systems engineering are growing in number but remain uncommon, the degrees including such material most often presented as a BS in Industrial Engineering.
Widespread institutional acknowledgment of the field as a distinct subdiscipline is quite recent; the edition of the same publication reported the number of such schools and programs at only 80 and , respectively. Education in systems engineering can be taken as Systems-centric or Domain-centric :. Both of these patterns strive to educate the systems engineer who is able to oversee interdisciplinary projects with the depth required of a core-engineer.
Systems engineering tools are strategies , procedures , and techniques that aid in performing systems engineering on a project or product. There are many definitions of what a system is in the field of systems engineering.
Below are a few authoritative definitions:. The systems engineering process encompasses all creative, manual and technical activities necessary to define the product and which need to be carried out to convert a system definition to a sufficiently detailed system design specification for product manufacture and deployment. Design and development of a system can be divided into four stages, each with different definitions: .
Depending on their application, tools are used for various stages of the systems engineering process: . Models play important and diverse roles in systems engineering. A model can be defined in several ways, including: . Together, these definitions are broad enough to encompass physical engineering models used in the verification of a system design, as well as schematic models like a functional flow block diagram and mathematical i.
This section focuses on the last. The main reason for using mathematical models and diagrams in trade studies is to provide estimates of system effectiveness, performance or technical attributes, and cost from a set of known or estimable quantities. Typically, a collection of separate models is needed to provide all of these outcome variables.
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The heart of any mathematical model is a set of meaningful quantitative relationships among its inputs and outputs. These relationships can be as simple as adding up constituent quantities to obtain a total, or as complex as a set of differential equations describing the trajectory of a spacecraft in a gravitational field. Ideally, the relationships express causality, not just correlation. Initially, when the primary purpose of a systems engineer is to comprehend a complex problem, graphic representations of a system are used to communicate a system's functional and data requirements.
A graphical representation relates the various subsystems or parts of a system through functions, data, or interfaces. Any or each of the above methods are used in an industry based on its requirements. For instance, the N2 chart may be used where interfaces between systems is important.