Problems In Systems Engineering Research Articles

System Engineering based on Remarkable Geometric Properties of Space

In this paper, we regard designing systems based on remarkable geometric properties of space, namely valuable rotational symmetry and asymmetry harmonious, using schematic and diagrammatic presentations of the systems. Moreover, the relationships are a way to comprehend original information to serve as a source of research and designing the systems. The objective of the future methodology is the advanced study of spatial geometric harmony as profiting information for expansion fundamental and applied researches for optimal solutions of technological problems in systems engineering. These systems engineering designs make it possible to improve the quality indices of devices or systems concerning performance reliability, code immunity, and the other operating indices of the systems. As examples, both up to 25% errors of lengths correcting code and high-speed self-error-correcting vector data code formed under a toroidal coordinate system are presented.

Multiobjective Optimal Control of Wind Turbines: A Survey on Methods and Recommendations for the Implementation

Advanced control system design for large wind turbines is becoming increasingly complex, and high-level optimization techniques are receiving particular attention as an instrument to fulfil this significant degree of design requirements. Multiobjective optimal (MOO) control, in particular, is today a popular methodology for achieving a control system that conciliates multiple design objectives that may typically be incompatible. Multiobjective optimization was a matter of theoretical study for a long time, particularly in the areas of game theory and operations research. Nevertheless, the discipline experienced remarkable progress and multiple advances over the last two decades. Thus, many high-complexity optimization algorithms are currently accessible to address current control problems in systems engineering. On the other hand, utilizing such methods is not straightforward and requires a long period of trying and searching for, among other aspects, start parameters, adequate objective functions, and the best optimization algorithm for the problem. Hence, the primary intention of this work is to investigate old and new MOO methods from the application perspective for the purpose of control system design, offering practical experience, some open topics, and design hints. A very challenging problem in the system engineering application of power systems is to dominate the dynamic behavior of very large wind turbines. For this reason, it is used as a numeric case study to complete the presentation of the paper.

Weight Induced Norm Approach to Group Decision Making for Multiobjective Optimization Problems in Systems Engineering

A final solution must be selected from a set of Pareto optimal solutions in the end when a multiobjective optimization problem is solved. Such selection becomes much more complicated for systems engineering when it involves multiple decision makers (DMs). This article proposes a weight induced norm (WIN) approach to group decision making from a systems engineering perspective. The importance of DMs and their preferences on objectives are associated with weighting coefficients using existing transformations. The weights are used to define a norm, introducing the concept of distance. Solution quality is assessed in the objective space. The final solution is the one that corresponds with the vector closest to a normalized ideal vector. Theoretical analysis is conducted to show a number of superior features of the WIN approach: backward compatibility, weighted-sum equivalence, Pareto compliance, invariability in normalization, and pairwise consistency. Numerical analysis illustrates that the WIN approach can produce a final solution reflecting the DMs’ importance and their preferences adequately; the WIN approach to solution selection can be interpreted using geometrical or algebraic arguments, which facilitates the DMs’ understanding of the decision process; it can readily distinguish the best solution from the remaining ones to avoid ambiguity.

Systems Engineering Problem in the Design of Earthquake Early Warning System (EEWS): A Comparative Analysis and Trial of Improvement in the Perspective of DoDAF

Based on the national earthquake intensity rapid reporting and early warning project, the architecture of earthquake early warning system is discussed in the view of DoDAF. By using the design of different viewpoints and modules of DoDAF, the main business unit and the data architecture model of earthquake early warning, the function orientation and business content of each unit, the contents and flow of data and control instructions, and the interface relationship between different systems are reviewed. Through the preliminary design of the top-level framework and the system architecture, the summarization and the summary information of the earthquake early warning system is clarified, with implication for understanding of the capacity vision, high-level operational, conceptual data, organizations relationships chart, operational activity and system interface of the EEWS.

Evaluating the Systems Engineering Problem Management Process for Industrial Manufacturing Problems

ABSTRACTProblems are ever‐present in nearly all engineered systems. A Systems Engineering Problem Management Process (SEPMP) has been proposed, and this research presents empirical evidence to support its validity. In order to evaluate the SEPMP, which uses a risk management style matrix to monitor problem timeliness and impact, it is necessary to determine the importance of communicating these components of the SEPMP model. A correlation and regression analysis is employed using existing empirical problem data and an analysis including communication of impact and timeliness components as independent variables. The dependent variable is the effectiveness of problem management, modeled as a measurement of the problem timeliness, implemented process improvements, training completed, and process delay as a result of the problem. Communication of timeliness and communication of impact are demonstrated to be significantly predictive of effective problem management. Finally, a plan for continued research is presented, including suggested future analyses to include additional empirical research and case studies of the implementation of a comprehensive problem management process, all of which may encourage acceptance of the SEPMP as a standard systems engineering tool.

A Theory of Information Quality and its Implementation in Systems Engineering

This paper introduces a theory of information quality to explain requirements engineering behavior observed during the systems engineering (SE) process. Requirements are technical statements that inform system design, implementation, and integration. The meaning of requirements information is relevant to the SE problem. The requirements entropy framework (REF) implements the theory and accounts for the meaning of requirements information in terms of its cumulative quality. The requirements quality distribution reflects the cumulative quality and determines the requirements entropy, the number of possibilities, and the additional information needed to reach the desired end state. The desired end state is occupied by requirements having all specified quality attributes. The requirements entropy, uncertainty, and needed information decrease as engineering effort is input into the process. The impact of added, revised, and deleted requirements can be estimated or measured from the change in entropy, uncertainty, or information. Results from computer simulation experiments suggest that the REF is a useful method for monitoring requirements trends, forecasting when the desired end state will be reached, and estimating requirements engineering effort for system development programs.

Use of Bayesian Networks for Qualification Planning: A Predictive Analysis Framework for a Technically Complex Systems Engineering Problem

Abstract This paper discusses the viability of using Bayesian Network (BN) models to support qualification planning in order to predict the suitability of Six Degrees of Freedom (6DOF) vibration testing for qualification. Qualification includes environmental testing such as temperature, vibration, and shock to support a stochastic argument about the suitability of a design. Qualification is becoming more complex and restricted yet available new technologies are not fully utilized. Technology has advanced to the state where 6DOF vibration shakers and control systems capable of high frequency tests are possible, but the problem using these systems is far more complex than traditional single degree of freedom (SDOF) tests. This challenges systems engineers as they strive to plan qualification in an environment where technical, environmental, and political constraints are coupled with the traditional cost, risk and schedule constraints. New technologies are also available for systems engineers to combine technical understanding with cost, risk and schedule factors to aid in decision making for complex problems such as qualification planning. BN models may provide the framework to aid Systems Engineers in planning qualification efforts with complex constraints. This paper discusses related work, the current approach and results of this research.

Systems Engineering Problems Related to Slope Ecological Protection Engineering

From the basic concepts and principles of systems engineering, the course system related to the slope ecological protection engineering is analayzed, which is a typical systems engineering. Talking the rock slope ecological protection engineering at Guizhou Guangzhao Hydropower Station for example, the application of systems engineering in the slope ecological protection engineering is researched. Using the technology of vegetation-growing concrete, the plan of protection and revegetation for this slope is turned out. It shows that systems engineering has a good applicability to slope ecological protection engineering.

7.4.2 “Meta” Matters

AbstractMisunderstandings related to “meta” often cause serious problems in systems engineering. This paper attempts to elucidate some of those misunderstandings, particularly as they apply to systems architectures. It examines how standards can provide discipline and clarity, suggesting how standards themselves must be done without falling into similar “meta” traps.

System of Systems Engineering Requirements: Challenges and Guidelines

:Traditional systems engineering (SE) has been successful in developing requirements that are objective, verifiable, and definitive. These requirements are chiefly related to technical or technological issues necessary to achieve a desired level of system performance. In contrast, System of Systems Engineering (SoSE) engages a more complex and holistic problem space, including organizational, managerial, policy, human/social, and political dimensions that exist in conditions of emergence, ambiguity, and uncertainty; therefore, the traditional SE requirements paradigm must be called into question. At present, the SoSE requirements paradigm has not reached the level of maturity or sophistication experienced by traditional SE. It is a miscalculation to expect successful approaches for SE requirements development to enjoy the same level of success when applied directly to the SoSE problem domain. The purpose of this article is to explore the nature of requirements from an SoSE perspective. First, the article establishes a foundation for differences between the SE and SoSE problem domains. Second, the traditional SE paradigm governing requirements is developed. Third, the specific nature of the SoSE problem domain implications for requirements is established. Fourth, guidelines for requirements within SoSE efforts are provided. The article concludes with key implications for the development and use of requirements in the SoSE field by practitioners.

Satisfying Business Problems

Successful requirements engineering is about more than just managing requirements. It's also about the relationship to and management of specifications. Typically, traceability structures capture the relationships between requirements, specifications, and domain statements. Traceability is therefore about more than just the relationships between requirements, stakeholders, and designs. At Praxis, we've started to apply these principles to solving business problems as well as systems-engineering problems. As an example we introduce the staff recruitment process in this article

6.1.2 Using Cognitive Engineering to Improve Systems Engineering

AbstractEnterprise Systems Engineering (ESE) must go beyond the hardware and software of systems to address Human‐Systems Integration (HSI). Towards that end, we propose that Cognitive Engineering techniques can and should play a key role in Systems Engineering efforts. In this paper we survey various methods in Cognitive Engineering, showing where these methods apply to specific problems in Systems Engineering from Concept Definition and Requirements Analysis, through Function Allocation and Performance Estimation, to Training Development and Performance Assurance. We also describe several uses of selected methods, including Cognitive Task Analysis, Computational Cognitive Modeling, and Critical Incident Analysis, to tackle specific problems in air traffic control. Taken together, these specific cases along with our general survey offer a roadmap for using Cognitive Engineering to improve Systems Engineering.

A Roadmap for Cognitive Engineering in Systems Engineering

We are concerned with three challenges in the design of military Command and Control (C2) systems, namely: the demand for “smaller” organizations, the demand for “better” coordination (human-system, human-human and system-system) and the demand for “faster” execution. Driven by these demands, we performed a survey of Cognitive Engineering techniques with an eye towards how they can improve Systems Engineering efforts. This paper outlines our three challenges (smaller, better, faster) and reviews three successful applications by other Cognitive/Systems engineers faced with similar challenges. The applications employ Computational Cognitive Modeling (to address a demand for smaller), Cognitive Work Analysis (to address a demand for better) and Goal-Directed Task Analysis (to address a demand for faster). These three successes provide a practical roadmap for using Cognitive Engineering methods to address Systems Engineering problems in C2 as well as other domains.

7.1.2 The Systems Engineering Sandwich: combining requirements, models and design

AbstractAs Systems Engineering problems and solutions become more complex, it is harder for engineers to describe them and harder for reviewers and other stake‐holders to understand the descriptions. What is needed is a more powerful way of describing both problems and solutions, which combines the textual approach with the diverse world of modeling, including the use of visual representation. The result would be more accurate and complete system descriptions that are easier to understand and communicate for all stakeholders involved.In the Systems Engineering “sandwich”, requirements management is the “bread and butter” of the development cycle, and system modeling provides the “filling“. The role of the filling provided by modeling is to hold the requirements layers together, and provide richer rationale for relationships between those layers.In our opinion, the key to integrating requirements management with system model is the recording of design rational in an organized way. Such rationale explains why requirements have been decomposed in particular ways, and how one layer of requirements is intended to satisfy the layer above. The focus for such information is the “design document“.The following benefits are identified as accruing from an effective process integration of requirements management and system modeling: System modeling adds formality to the design process that lies between each layer of requirements. System modeling supports the construction of a consistent vocabulary for the textual expression of requirements. The design rationale gathered around the system model becomes the rationale for tracing between layers of requirements. The structure of the system model can be used to give structure to the requirements document. System models can be embedded in system design documents. These can provide textual context for the system model, giving rationale for design choices, explanations of diagrams, etc. Impact analysis can be carried out uniformly through requirements and models. Non‐functional and performance requirements not captured in the model can be managed as textual statements.