bluuebunny/crossref_metadata_2025_split huggingface dataset:
9.2.2 A Framework for a National Undergraduate Systems Engineering Stream of Studies in Discipline‐centric Degrees: Proposal Analysis
Authors: (Willy) Peng Yuan‐Shi , Ferris Timothy L.J. 
Published: November 2014

AbstractThe authors have developed a framework proposal for undergraduate systems engineering education as a stream of studies forming part of a Bachelor of Engineering program in any discipline of engineering. This proposed framework has been developed with the intention of use broadly across many universities, colleges, and in all engineering disciplines in Taiwan. The paper discusses the pedagogical background to the proposal and analyses the proposed structure from several educationally significant viewpoints. The broad fronted approach to curriculum presented in this paper includes Bloom's taxonomy of educational objectives, the concept of graduate outcomes, a contrast of the capability of engineers educated traditionally and through the proposed curriculum, the current cultural context of undergraduate students, and the national objectives to be served through the educational activity.
9.2.3 Architecting Synthetic Environments to Support the Systems Engineering of Capability
Authors: Battersby David 
Published: November 2014

AbstractValidating the link between an architecture framework representation of a capability and the systems which provide that capability is a substantial challenge. Synthetic environments are suggested as a method whereby this can be achieved. A traceable method for supporting this is provided through the mapping between architecture framework views, synthetic environments and the design lifecycle.The use of synthetic environments is also highlighted as a key method for the management of capability, through the ability to integrate human factors, process and technical issues. An iterative use of synthetic environments, with increasing levels of modeling fidelity, is suggested as an approach to supporting engineering and acquisition throughout the whole project lifecycle.
9.3.1 Trade Studies with Uncertain Information
Authors: Ullman David G. , Spiegel Brian P. 
Published: November 2014

AbstractDuring every stage of the design process, designers trade off performance, cost, and risk in an evolutionary process whose goal is to find a satisfactory solution. This paper explores a recent method to manage the trade study process especially when uncertainty is pervasive and decisions are a mix of quantitative and qualitative information. We believe that it is possible to support a trade study process that is sensitive to the uncertainties in evolving system information, a key ingredient in managing risk, robustness, changes and spiral development. In this paper we explore what is needed to support such activities. To do so we follow an example as it gets increasingly complex and realistic. As the issues addressed increase in computational need, we make use of Accord, a decision support system base on Bayesian Team Support methods.
9.3.3 Defining, Finding, and Hiring REAL Systems Engineers
Authors: Arnold Eileen P. 
Published: November 2014

AbstractDemand for skilled, knowledgeable, Systems Engineers in government, industry, and academia is increasing around the world. How would a hiring manager know if they are hiring a “real” Systems Engineer, unless the Manager is one, or is thoroughly versed as to what a real Systems Engineer is and does? There are thousands of open requisitions for Systems Engineers, yet little guidance as to how to identify, attract, and hire Systems Engineers. Defining, Finding and Hiring REAL Systems Engineers provides guidance as to how to acquire Systems Engineers. It first defines what is meant by a “real” Systems Engineer, discusses the writing of good quality requisitions (Seven Elements of a Great Requisition), provides insight into where to find “real” Systems Engineers, captures what to look for on resumes (resume keywords), provides favourable and less favourable examples of requisition content, and provides interview questions within the framework of Interview Question Steps, with tips as to what to listen for during the interview. Finally, a summary of how to retain the Systems Engineers you found and hired is included.
10.1.1 An Index to Measure and Monitor a System‐of‐Systems' Performance Risk
Authors: Garvey Paul R. , Cho Chien‐Ching 
Published: November 2014

AbstractThis paper extends an earlier published methodology [1] for measuring the technical performance risk of a system to that of a system‐of‐systems (SoS). The earlier work established an approach for combining an individual system's Technical Performance Measures (TPMs) into an overall measure of performance risk, defined as the Technical Risk Index (TRI). This paper extends this approach so a similar index can be developed for a system composed of many interdependent or connected systems that come together as a whole to provide an SoS capability.
10.1.2 Using Earned Value to Track Requirement Progres
Authors: Solomon Paul J. 
Published: November 2014

AbstractIt is necessary to track the status of each requirement as it moves through engineering life cycle activities. Measures that reflect the status of the requirements are essential to monitor program status and serve as a scorecard to indicate that requirements are being implemented on schedule.This paper provides guidance to use the tools of requirements traceability to plan and measure the progress of the requirements management activities. The requirements traceability matrix (RTM) can be used as a scheduling source and as a set of base measures of Earned Value (EV). Finally, the importance and value of comparing the schedule variances of the requirements management and tracing activities with the variances of other project activities is discussed.
10.1.3 Reaching CMMI Level 5 is more than just having adequate metrics ©
Authors: Duckworth Jason F. , Lewis Robert O. 
Published: November 2014

AbstractAt first glance, the Capability Maturity Model Integration (CMMI) appears to be clearly divided into two advanced levels of maturity, Level 4 dealing with quantitatively managing products and processes using statistical methods, and Level 5 dealing with comprehensive corrective and preventive actions. However, underlying the four process areas, two of which belong to each level, is a closed‐loop system that encompasses both levels that if left unrecognized and unused makes reaching and sustaining Level 5 very difficult. This paper reveals and describes this closed‐loop system with its intricate feedback loops to the degree necessary for all who aspire to Level 5 to benefit. The paper is based on the actual experience of one of the larger Boeing sites and is written by two of the team that developed this system and then used it to reach CMMI Maturity Level 5 in September of 2005. Those implementing CMMI at advanced levels of maturity must be able to recognize and make good use of this embedded system and the high degree of integration that exists across the model at all levels.
10.3.1 The “Big Navy” Meta‐model as a Framework for Major Defense Development Projects
Authors: Ryder Christopher M. 
Published: November 2014

AbstractPatterns, frameworks, meta‐models: the utility of these tools for many systems architects and engineers is to avoid “heavy lifting”. Others will say that they use meta‐models to keep from “reinventing wheels.” Builders and structural engineers have utilized patterns, frameworks and meta‐models which include building codes and construction standards for thousands of years. In the realm of defense systems engineering, the “Mystical Land of DoDAF,” systems engineers have been slow to realize the full potential of meta‐ model applications. Instead, functional analysis teams performing work prescribed by the Joint Capabilities Integration and Development System (JCIDS) end up doing that “heavy lifting” in the course of developing JCIDS functional area, needs and solutions analyses. Analysis teams performing JCIDS Functional Area Analysis (FAA) assess hundreds of activities listed in the Universal Joint Task List (UJTL) for relevance to their functional domain. This paper does not intend to discount the importance of the review of the tasks and activities required in the FAA, yet it is highly desirable to utilize the precedent foundations provided by those functional area analysts who blazed the trail for predecessor systems currently operating within their operational domain. A systems engineering meta‐model provides such a foundation for a living engineering model from operational needs analysis through production and deployment. The framework described below, the “Big Navy” Meta‐model, is an example of one pattern that can be applied to facilitate the development of complex defense‐related systems. Systems models derived from Big Navy can be further refined over its life cycle to include requirements capture, functional analysis, architecture development, concept and engineering design and design validation which includes modeling and simulation.
Foundational Systems Engineering (SE) Patterns for a SE Pattern Language
Authors: Simpson Joseph J. , Simpson Mary J. 
Published: November 2014

AbstractPatterns are classically used to effectively capture large, complex bodies of information and knowledge. This paper outlines the current state of systems engineering (SE) pattern literature as well as proposing a foundational set of SE patterns for use in SE pattern languages. A pattern is defined as a solution of a specific problem placed in a specific context. A pattern language is a collection of interrelated patterns, with specific relationships binding individual patterns together. A collection of SE pattern relationship types are also introduced in this paper. Language is a fundamental aspect of any technical or scientific activity. The technical language used in technical activities impacts the concepts that can be addressed, the effort to express these concepts, and the precision with which these concepts can be expressed. Therefore it is important to consider the language requirements for conceptual expression and precision when designing a new language. In the case of an SE pattern language, the elements to be considered are the individual patterns and the relationships between the patterns.
Integrated Project Control Loop Concept
Authors: Laudan Timo , Mauritz Axel 
Published: November 2014

AbstractThe purpose of this paper is to provide a systems engineering approach in project management elaborated in the environment of a complex European aeronautical research project. This paper introduces to actual research activities in the area of preventive risk avoidance and proactive risk handling mechanisms in complex projects based on an Integrated Project Control Loop (IPCL) concept, as a means supporting the Project Management (PM) decision making throughout the project life cycle. First experiences from this European project provide a potential applicable and tool‐supported ICPL concept enabling continuous improvements for PM. The IPCL concept consists of uncertainty management in terms of a continuous support to monitor project performance and to steer project functions (cost, time, quality, scope and organization) and the referring requirement profile based on an information integration framework (tool integration concept). The integrated information framework allows the technology based implementation of distributed information to specific PM information models on a centralized level. As a result of the concept outlined above, quantitative and qualitative deciding factors for adequate contingency allowance are exposed and provide a better understanding and situation awareness for PM.
Heuristics and Genetic Algorithms
Authors: Mobley Michael D. , Dagli Cihan H. , Enke David 
Published: November 2014

AbstractGenetic algorithms are design tools used in generating optimal solutions. While they can often be shown to outperform various heuristic methods and hybrid approaches, using a combination of evolutionary algorithms and heuristic approaches can generate an optimal solution more quickly than either of the two methods independently. Our purpose is to provide an overview of genetic algorithms, to discuss the types of problems that lend themselves to being solved by genetic algorithms, and to identify heuristics that have been shown to aid genetic algorithms in their quest for optimal solutions. While the sample problems discussed in this paper are generally of textbook variety, genetic algorithms can be applied to problems of interest to systems engineers. Such problems include (1) up‐front trade studies to look for potential feasible concepts based on combinations of key system attributes within system constraints and (2) resource selection problems. A military example of a resource selection problem is autonomously recommending air attack resources to prosecute evolving targets. The decision space in this problem is bounded by available fuel, available number and types of weapons, current aircraft locations and current target priority rules of engagement.
Balancing Cost and Performance During Design
Authors: Cronin David M. , Ash Kenneth S. 
Published: November 2014

AbstractDesign and Production can take advantage of new developments in Critical Parameter Management (CPM) to manage the relationships between parts, assemblies, function, and cost. Elements in a WBS/BOM structure can be linked to function, cost, and performance definitions and viewed in a critical parameter tree. Through a series of transfer functions, a dynamic relationship is created to compute and track the results of parameter changes on cost and performance. Design For Six Sigma (DFSS) related techniques are also supported to allow engineers to make these connections and track the cost impact of designs based on performance decisions. This presentation will define the interconnected architecture including customer inputs, system requirements, critical parameters, the effect of parameter variations, transfer functions and the effect of multiple inputs on cost and affordability.
1.3.2 A Vision for Super‐Model Driven Systems Engineering
Authors: Piggott Stephen , Melanson Philip , Hartman Leo 
Published: November 2014

AbstractModel‐Based Systems Engineering (MBSE) has been developing for some time, and has recently acquired new impetus with the completion of the Systems Modeling Language (SysML). This paper envisions taking MBSE much further, to a future of highly integrated and automated design and verification coupled with advances in simulation and domain linkage to allow the synthesis of complete systems from requirements into mathematical models and then into physical realizations. This would permit the application of three of the most successful approaches from agile software development, namely rapid, iterative development of the system starting with the highest value functions, facilitating continual reassessment of the future direction, and continual regression testing to ensure that system bugs are identified and removed rapidly. We envisage the requirements and the model evolving together from proto‐requirements and proto‐model in increasing detail until the point at which the model can be realized with real hardware and software. Taking this further, the MBSE engine can perform trade‐offs and optimization on the design. Implementing this vision requires progress in a number of technologies, such as data exchange between domain tools. At this time, much engineering effort is consumed in people communicating and mediating information and translating it from one form to another (e.g. system design to mechanical design). If we can realize the vision proposed, we can remove much of the burden of information mediation and optimization, allowing engineers to focus on their expertise and larger issues. The potential savings in labour are huge.
1.5.2 Emerging Real‐Time Intelligent Agents In Space Launch Verification and Anomaly Resolution
Authors: Beshore David G. 
Published: November 2014

AbstractIn 1997, the Evolved Expendable Launch Vehicle (EELV) program, now under the auspices of the United Launch Alliance (ULA), began with fundamental goals to reduce cost and improve the reliability of launching satellites and interplanetary spacecraft. With payloads costing more that several billion dollars each, the reliability of launch vehicles mandates perfect launches. Subsequently, launch systems have become highly complex with increasing launch rates of satellites to perform surveillance, network‐centric command and control, and communications on the land, sea, air and space. Launch system Ground Computers, Command and Control (GC3) has grown exponentially in software capabilities, collecting and displaying data to domain experts, and transmitting real‐time data to world‐wide support teams. Rapid and accurate anomaly resolution with customers and contractors, especially for events leading up to day‐of‐launch (DOL) involves hundreds of personnel using these complex systems. This paper describes near‐term capabilities which are the building blocks of future intelligent agents: decision making, knowledge management; computer systems, control software and desktop PC tools. These agents are rapidly maturing into integrated systems decision making processes that are responsive within seconds. This near‐term development activity is compared with a 20‐year forecast of spaceport intelligent agent systems.
1.6.1 Using CORE Model‐Based Systems Engineering Software to Support Program Management in the U.S. Department of Energy Office of the Biomass Program
Authors: Riley Cynthia , Sandor Debra , Simpkins Philip 
Published: November 2014

AbstractBiomass research has been a cornerstone of the U.S. Department of Energy's (DOE's) renewable energy development and deployment efforts during the last 25 years. Today, as the true cost of the nation's reliance on imported oil becomes increasingly clear, the DOE Biomass Program is poised to bring biomass‐derived biofuels to the market as a sustainable, domestic alternative to petroleum‐derived fuels. To ensure that the program is focused on the activities critical to achieving this goal, the program is implementing systems engineering processes, practices, and tools to guide informed decision‐making as biomass‐to‐biofuel systems are advanced from concept to commercial adoption. The program is using CORE, a Model‐Based Systems Engineering (MBSE) software tool, to organize, coordinate, and document the program goals, milestones, and project tasks in a central repository. CORE is facilitating management and communication of program status, through the automated generation of accurate and up‐to‐date custom reports, Gantt charts, and tables in Microsoft Word, Microsoft Project, and Microsoft Excel formats, which are widely available to all program participants.
1.6.4 Synthesizing the Organizational System
Authors: Arnold Eileen 
Published: November 2014

AbstractAll Change is inevitable. The pace at which change transpires and the complexity of that change is dependent upon the:
Number of concurrent change drivers
Degree to which the drivers are instituted
Cultural acceptance of the drivers
Capacity (Resources) to implement the change, and
Application of system synthesisAt BAE Systems Land & Armaments, Armament Systems, the realization that the numerous initiatives and business drivers required for our business unit to become world class, required the combining of separate elements to form a coherent whole; system synthesis. Synthesizing the organization is a key to intelligent enterprise, since it is lean, adaptive, and agile.The major initiatives and business drivers used for illustration of our organizational system in this presentation include:
Armament System's Business Process Model
International Standards Organization (ISO) Standards
BAE Systems corporate flow down of their Life Cycle Management processes, and
Capability Maturity Model Integrated (CMMI®)This presentation addresses how CMMI® acted as an enabler, to help drive the synthesis of our business initiatives in pursuit of an integrated organizational system. The interaction of these multiple forces results in a combined effect that is greater than the sum of their individual effects. CMMI® has acted as the change agent to drive cooperative interaction among our internal groups and is aiding in our business units' transition as a recently acquired BAE Systems unit. CMMI® provides a common language of communication and lays the foundation for the interconnected links among the elements.
3.1.1 System of Systems Engineering Model by Multistage Analytical Target Cascading
Authors: Kim Harrison M. 
Published: November 2014

AbstractThis paper presents a multilevel, multistage approach to system of systems engineering optimization where a system design/selection is linked with system allocation along the multistage decision making horizon. The approach is composed of two parts: pseudo‐hierarchical formulation (i.e., how to model the stages of multiple, separate decision making processes), and multistage coordination (i.e., how efficiently the proposed model would perform). The pseudo‐hierarchical formulation expands the analytical target cascading previously developed by the author into multiple stages to capture level‐by‐level and stage‐by‐stage system of systems design optimization. The multistage coordination is based on the alternating directions method that is incorporated as an efficient means to solve this inherently large‐scale optimization problem. An airline example validates the methodology where an airline plans to introduce multiple new aircraft to capture dynamically changing future demand of the customers. The proposed methodology is validated against the all‐in‐one approach and the sequential approach.
3.1.2 Architecture‐Based Drivers for System‐of‐Systems and Family‐of‐Systems Cost Estimating
Authors: Wang Gan , Wardle Philip , Ankrum Aaron 
Published: November 2014

AbstractAs the industry undergoes a paradigm shift from a system‐based procurement model to a capability‐based acquisition model with a focus on integration of legacy systems and interoperability of systems of systems and families of systems, new challenges have emerged for the field of cost estimating. What is the cost of an operational capability in a net centric environment based on enterprise architecture? This paper explores a set of enterprise architecture‐based drivers for estimating the life cycle cost or total ownership cost of operational capabilities from integration of complex systems of systems and families of systems. It attempts to extend the traditional systems engineering practices and to address the new challenges from capability‐based engineering and interoperability of systems of systems.