bluuebunny/crossref_metadata_2025 huggingface dataset:
6.3.3 Application of Patterns to Systems Engineering and Architecting
Authors: Cloutier Robert J. , Boardman John , Verma Dinesh
Published: November 2014

A system architecture pattern constitutes a high‐level structure that has been used multiple times in the same or multiple system architectures, appropriate to the design of the major components of a system. It expresses the relation between the context, a problem, and a solution. It documents attributes and usage guidance. It should be time‐proven in solving problems similar in nature to the problem under consideration. The existence of patterns is almost universal, and their use is evident in many domains. The human mind seems to perceive patterns without conscious thought ‐ we notice an individual's personal habits because they form patterns. Patterns are also used in a number of engineering disciplines – software engineering, requirements engineering and mechanical engineering to name a few. The purpose of this paper is to discuss motivations for using patterns in architecting complex systems. Further, research relating to this subject is examined and summarized.
7.2.2 Performing Functional Analysis/Allocation and Requirements Flowdown Using Use Case Realizations – An Empirical Evaluation
Authors: Eriksson Magnus , Börstler Jürgen , Borg Kjell
Published: November 2014

The FAR approach (Functional Architecture by use case Realizations) is a use case driven methodology for functional analysis/allocation, and requirements flowdown. The FAR approach is tailored towards the development of long lived software intensive defense systems, for example vehicles. In this paper, we present an empirical study where FAR is applied and evaluated in two large‐scale defense projects. Our results indicate that the FAR approach performs better than the previously used approach in the organization.
8.1.2 A Study of Applying Game Theoretic Concepts on Distributed Engineering System Design
Authors: Wang Hungjen , Frey Daniel
Published: November 2014

This paper considers the application of game theoretic concepts to the dynamics of interactions among the designers in an engineering systems design problem under a distributed decision making environment. Among all the possible distributed frameworks, we focus on two types of frameworks in the system design field, the simultaneous and the sequential response frameworks. In the investigation of the simultaneous response framework, we apply the concepts of learning theory to construct insights into the dynamics among the designers and to address convergence and other challenges of the decentralized design problems. We use a special class of games, the potential game, to demonstrate the effectiveness of the sequential response framework which points out a prospective application of game theoretic concepts to future distributed engineering systems problems.
8.3.2 Use of Technical Business Practices by Geographically Separated Teams to Facilitate Concurrent Engineering of Ultraquality Systems (LA‐UR‐05‐8500)
Authors: Neff Warren , Dagli Cihan
Published: November 2014

In 1997, the National Nuclear Security Administration (NNSA) undertook the development of an architecture of standards and requirements to standardize the engineering design and manufacturing of ultraquality weapon systems. This architecture, known as the Technical Business Practice (TBP) system, was implemented in 1999. The TBP system is centered around a concurrent engineering philosophy and based on a Product Realization Process methodology which is broken into four process steps: Definition, Development, Delivery, and Support.

The four‐step concurrent engineering approach is accomplished through multi‐disciplinary teams known as Product Realization Teams (PRT) which are comprised of managers and subject matter experts from across the Nuclear Weapons Complex. Depending on the breadth and complexity of the engineering tasks being executed, PRTs can be subdivided into sub‐PRTs or Task Teams. Both sub‐PRTs and Task Teams tend to have a “component‐focus” versus the “system focus” of the PRTs. Using the architecture of TBPs, focused around a concurrent engineering philosophy employed by PRTs, execution of nuclear weapon programs has become more efficient, consistent, and comparable across the Nuclear Weapons Complex.
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

The 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

Validating 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

During 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

Demand 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

This 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

It 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

At 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

Patterns, 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.
11.1.1 Technical Performance Measures
Authors: Oakes Jim , Botta Rick , Bahill Terry
Published: November 2014

Technical performance measures (TPMs) are tools that show how well a system is satisfying its requirements or meeting its goals. This paper presents the BAE National Security Solutions TPM process and a TPM template. It gives lessons learned from piloting it on a program.
Foundational Systems Engineering (SE) Patterns for a SE Pattern Language
Authors: Simpson Joseph J. , Simpson Mary J.
Published: November 2014

Patterns 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

The 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

Genetic 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

Design 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

Model‐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

In 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

Biomass 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

All 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 synthesis

At 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

This 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

As 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.
3.2.1 An Enterprise Architecture Framework for Developing Command and Control Systems
Authors: Yeoh Lean‐Weng , Syn Hon‐Beng , Lam Choon‐Vu
Published: November 2014

In recent years, the way in which military operations are being conducted has changed dramatically. This has largely been driven by advancements in technology that now allow faster communications, better situation assessment and more effective decision‐making. Military forces are now striving to realise the next stage of transformation by harnessing new technology to create a network‐centric enterprise that takes advantage of pervasive knowledge in order to achieve greater war‐fighting capability. Integrated Knowledge‐Based Command and Control (IKC2) is an integrated, network‐enabled and knowledge‐based approach to warfare that bears similarities to the intelligent enterprise. It is a force multiplier that will enable military forces to achieve their desired mission objectives. However, there are many challenges to the successful development of IKC2 systems.

The traditional approach to developing command and control systems is inadequate because it typically views systems in a stovepipe fashion with minimal interactions with other systems. An Enterprise Architectural Framework for developing command and control systems is necessary to address these shortcomings. This Framework includes a governance process to ensure that systems developed by the various parties, including government and industry, are able to interoperate and to leverage technologies both developed and commercial‐off‐the‐shelf.
3.2.3 Divergence: The Impact of Lifecycle Changes on Commonality
Authors: Boas Ryan , Crawley Edward
Published: November 2014

Sharing common parts, processes, interfaces and infrastructure offers the potential to increase the overall efficiency and effectiveness of an enterprise through reductions in costs, lead times and risks associated with the development of product/system families. While the benefits of commonality have attracted much interest across industry, the government and academia, the current practice and research fail to account for a significant challenge associated with commonality: the natural reduction of commonality over time, a phenomenon termed “divergence.” Divergence occurs due to requirements changes; learning in development and operations; the availability of new technologies; obsolescence; program timing; and for reasons associated with corporate culture. The impact of divergence is an overestimation of the benefits of commonality: planned benefits aren't realized through the course of development while the penalties of pursuing commonality (cost, time, risk, performance) are incurred. The TFX (F‐111) fighter aircraft program of the 1960's is provided as a historical example of divergence and its impacts. Accounting for divergence will improve multi‐system program planning and execution.
3.4.3 The Value‐Based Theory of Systems Engineering: Identifying and Explaining Dependencies
Authors: Boehm Barry , Jain Apurva
Published: November 2014

The Value‐Based Theory of Systems Engineering brings together many interdisciplinary theoretical lenses into a state of synchrony and allows reasoning about systems in different dimensions, and at various levels of abstraction. The theory's primary strength is in its ability to identify and work through the dependencies of most socio‐political‐technical systems and explain success in such contexts by situating the success‐critical stakeholders at the forefront. In this paper we present the 4+1 theoretical lenses of the Value‐Based Theory of Systems Engineering with a core emphasis on the Dependency Theory – the first and most complex of the four component theories.
4.3.0 Panel 4.3.0: Discovering a Strategy for Whole Systems Modeling
Authors: Ring J. , Bahill T. , Blackmon T. , Cloutier R. , Clymer J. , Hodgson R. , Jacoby C. , Krane S. , Lloyd K. , Newman R. A. , Orr J. , Rose C. , Skipper J. , Sorenson R. , Steiner R.
Published: November 2014

Practitioners actively involved in modeling systems today generally agree that our profession does not construct a unified model of a median system let alone an adequate, accurate and timely model of the larger, more complex systems, especially those in which humans are active elements. Ironically, knowledge about and technologies for modeling are progressing faster than their rate of adoption. This emerging gap indicates a lack of strategy and perhaps willpower. This panel/experiential workshop is intended to discover a strategy that is equal to the challenges ahead. This means a strategy that not only ensures languages, methods, tools competencies and standards of care but also one that motivates systems practitioners to be accountable for results.
4.5.2 Knowledge Management A Key Element of Success
Authors: Long Leon P. , Dagli Cihan H.
Published: November 2014

Knowledge Management is a complex and elusive goal that is becoming more and more important to organizational success. Modeling Knowledge Management in today's organizational environment requires the consideration of not only integrated domains of various knowledge agents but also the realization that in order to construct knowledge (and ultimately intelligence) you must consider the aspect of time variance, data/information value, and knowledge recognition and placement. An individual can not stand fixed in the present and expect the data and information collected in the past to represent the same knowledge when projected into the present. Knowledge (and Knowledge Value) is relative to the position on the historical time line at which it was initially established. The act of collecting data and information is insufficient for knowledge generation. If you apply a time‐knowledge model relationship then the value of knowledge will have a different increasing value all along the timeline, thus helping to ensure that today's knowledge is more capable of meeting the needs of the present as well as establishing a stronger foundation for the future.

As products increase in complexity and manufacturing is distributed among a multitude of stakeholders, the knowledge of how to maneuver through the maze of system integration and product life cycle dynamics while maintaining a margin of profitability have significant commercial advantages.

The need for successful Knowledge Management is essential to maintaining a competitive edge in the business environment. Understanding the relationships between data, knowledge and the intra‐related processes which represent the collective knowledge for success can be complex. In the paragraphs that follow, the reader is encouraged to follow the knowledge model that relates the elements of organizational knowledge management as it models data & knowledge, and processes to establish a set of solutions from which one optimum solution emerges to satisfy the initial goal or Program.
4.6.1 Applying Creativity in Modelling and Simulation
Authors: Cropley David H
Published: November 2014

This paper examines the application of concepts and principles of creativity to the domain of modelling and simulation. The paper will start by examining the background to modern views of creativity in technological enterprises. This culminates with a functional model of creativity that focuses not only on characteristics such as novelty, but also on the pre‐requisite characteristic of relevance and effectiveness. This means that for a product or system, or indeed a model or simulation, to be regarded as creative, it must not only be original and novel, but must, as a pre‐requisite, do what it has been designed to do. For this reason, issues such as fidelity, and other quality metrics applied to models, will be relevant. The paper then examines reasons for endeavouring to build creativity into modelling and simulation. The paper will study potential benefits and penalties associated with creativity in this domain, and will offer suggestions about the appropriateness, or otherwise, of attempting to build novelty into the process of modelling and simulation.
5.1.2 Integrating the Intelligent Enterprise
Authors: Dixon Keith , Brown Samantha , Keirl John
Published: November 2014

The need for enterprise intelligence continues to grow in response to increasingly complex and dynamic organizational environments. However, an intelligent enterprise is comprised of more than a collection of intelligent resources. Like an effective team the whole is made greater than the parts by the manner in which they integrate. Enterprise intelligence enables an organization to both fully exploit existing opportunities whilst remaining capable and ready to respond to future change. In this paper we focus on the contribution made to this dynamic stability by the systemic integration of resources. Using a multi‐level systems model we develop a framework, drawing on the concept of intellectual capital, to examine data from a case study of a UK government funded research organization. The findings provide an important insight into the interplay between the social and structural aspects of the linkages that integrate resources and the implications this has for creating enterprise intelligence.
5.2.0 Panel 5.2.0: Tailoring to Transit: Case Studies Applying SE to the Rail/Transit Domain
Authors: O'Neil A. , Gharatya K. , Hutchison B. , Kouassi A. , Price D.
Published: November 2014

When an industry with 100‐year history of silo‐based operational domains introduces widespread technological advancements, generating exponential numbers of new interfaces that cross organizational boundaries – how does it respond to this new risk? For the rail/transit industry, the answer has been to adopt a systems engineering approach to manage the risk!

Tailoring an SE approach for application to a new commercial domain has had its challenges. These case studies contrast and compare applications of SE across rail/transit projects to evaluate risk reduction and other benefits realized. Explore results across projects differing in scale, goals and asset type as well as in SE management strategies applied. Can the transit industry reach consensus and establish common systems engineering best practices, process and approaches? What tactics are being employed to facilitate shift in the cultural mindset to manage new interfaces and integration demands?
6.1.1 Principles of Complex Systems for Systems Engineering
Authors: Sheard Sarah A.
Published: November 2014

This paper shows how three systems of types well‐known to systems engineers can be understood as complex systems. This is important because research in complex systems sciences is vibrant and provides critical insight, but if systems engineers do not understand the complex aspects of the systems they work with daily, they may not be able to use these research results. To date, systems engineering has been looking only at exploiting the “order” side of the order‐to‐chaos spectrum, and it is time now to understand and begin to utilize principles from the middle and from the chaos side of the spectrum.

The three examples are INCOSE, the systems engineering process (such as a company's standard process), and air traffic control. INCOSE represents most volunteer organizations and social groups. Most systems engineers do not realize that the systems engineering process for a company is a network that can be studied by complex systems methods. Air traffic control may come closest to many systems engineers' definition of a system.

This paper provides principles of complex systems based on a variety of sources, and shows the application of complex systems to one of the examples.
6.4.3 Architecture Frameworks in System Design: Motivation, Theory, and Implementation
Authors: Richards Matthew G. , Shah Nirav B. , Hastings Daniel E. , Rhodes Donna H.
Published: November 2014

This research examines the underlying rationale of architecture frameworks and their use in acquisition with the goal of identifying best practices to improve system development. Three key questions are addressed: (1) What is the role of artifacts in system design? (2) What are the benefits provided by architecture frameworks? And (3) what are the best measures‐of‐effectiveness for assessing the value of architecture frameworks? To address the first question, we review relevant literature on collaborative design and propose a rationale for using artifacts as communicative and illustrative tools. Second, we enumerate the motivations for their use in system design and acquisition. Third, eight measures‐of‐effectiveness of architecture frameworks are derived from the literature and our experience with the Department of Defense Architecture Framework.
7.1.1 NO VEHICLES ON THE MALL!
Authors: Pringle Charles O. , Carson Ronald S.
Published: November 2014

Systems Engineering methods are applied to address symptomatic problems associated with pedestrian‐vehicle interactions on a university campus. Through discovery techniques a more accurate picture of the true problem is obtained. Using system modeling, potential consequences associated with proposed solutions are identified. An optimized solution was identified which maximized benefits without incurring unacceptable costs. This application of Systems Engineering shows the value of problem definition and analysis prior to solution implementation in the domain of public policy.
7.1.3 The story of Verdal – how one intelligent community uses systems engineering to enable sustainable development
Authors: Haskins Cecilia
Published: November 2014

Verdal is a small community in mid‐northern Norway, with a culturally significant historical tradition dating back to 1030. The town has reinvented itself to keep abreast of changing times; moving from an agriculturally based economy to an industrial region. The changes have been mostly evolutionary and unscripted until 1999 when a downturn in the business of the largest employer threatened the welfare of the entire community. Today, Verdal is one of the most stable and admired communities in Norway. To remain that way, they are embarking on a new initiative using systems engineering to ensure sustainable growth. This is their story.

This paper provides a case history of how systems engineering is being applied to a non‐traditional application domain ‐ sustainable development ‐ in the context of an “intelligent community” in Norway. The case is allegorical and has relevance for practitioners in city planning and manufacturing.
7.6.4 Some Powerful Systems Engineering Heuristics
Authors: Gilb Tom
Published: November 2014

This paper recommends some fundamental heuristics that aim to characterize the essential spirit of systems engineering. These heuristics should be used when teaching systems engineering.
8.1.2 Human Factors Integration for MODAF: Needs and Solution Approaches
Authors: Bruseberg Anne , Lintern Gavan
Published: November 2014

The design of complex, large‐scale, socio‐technical systems such as Network‐Enabled Capability (NEC) requires collaboration of diverse disciplines since it needs to embrace all areas of systems design. One approach to dealing with such complexity is the use of Architectural Frameworks such as MODAF. There is a concern however, as to the extent to which MODAF is able to address Human Factors Integration (HFI) issues that should be applied as an integral part of socio‐technical system design. Equally, the discipline of HFI may not sufficiently consider concerns from the Systems Engineering domain. This paper provides an assessment of the adequacy of MODAF in addressing HFI design issues and summarizes recommendations and initial solution approaches.
8.4.2 Exploring Concurrent Activities: Using State Machines to Understand Net‐Enabled Operations
Authors: Sorensen Richard , Funk Ronald , Ball Mark
Published: November 2014

The Defence Research and Development Canada (DRDC) Centre for Operational Research and Analysis (CORA) is developing capability engineering analysis tools to help build and assess architectures to support net‐enabled operations. This paper describes research into State‐Machine (SM) models to simulate job workflows that are typically done serially using the Task, Process, Exploit and Disseminate (TPED) cycle or concurrently using the Task, Post, Process, Use (TPPU) cycle.

Classical behavioural models cannot simulate TPPU beyond simple cases due to all the possible permutations in the job flow. SM models overcome this by storing the status of activities and products and then using them in the next time step as inputs to change the status through an action or an output. The SM approach shifts the modeling perspective to an instant in time so the interrelationships of concurrent activity can be simulated in more detail than is feasible for classical architecture models. Sample results and analysis tools for the current SM model are presented.
9.1.1 Human Functional Analysis of Lean Staffing: Extensions to the Department of Defense Architecture Framework (DoDAF)
Authors: Lintern Gavan , Bruseberg Anne
Published: November 2014

We address the problem of lean staffing with a review of the Department of Defense Architecture Framework and conclude that the human system aspects of the relevant Organizational and Systems Views need to be informed by special analytic methods from Cognitive Systems Engineering. We describe a systematic framework for Human Views in a companion paper. In this paper, we illustrate how selected knowledge acquisition methods of cognitive engineering can be used to generate supplemental information for the Human Views needed to resolve the issue of lean staffing.
9.2.1 Optimized Airport Security Infrastructure System (OASIS)
Authors: Castaneda Elizabeth , Gonzalez Jamie , Harris Shannon , Kim Joon
Published: November 2014

It has been suggested that the current security measures being implemented in airports around the country produce “soft targets” in the form of lengthy queues. These soft targets heighten the risk of a terrorist attack within airport premises that could potentially have the same impact as destroying a commercial flight. Using Washington Dulles International Airport as a case study, this study examines the security measures being implemented in the airport and designs a methodology that will result in improved allocation and usage of security resources. Two alternatives are designed that make use of layered, defense‐in‐depth security measures that aim to deter terrorist attacks by using the concept of unpredictability. Models of these alternatives are built and the best alternative is selected by analyzing simulation outputs and evaluating them based on a value function. At the end of the study, an Optimized Airport Security Infrastructure System (OASIS) that will provide a more efficient and reliable method for screening passengers and their luggage is proposed.
10.3.0 Panel 10.3.0: Modeling the Enterprise: Case Studies and Approaches
Authors: Griego R. M. , Dove R. , Krane S. , Lloyd K. , Martin J.
Published: November 2014

Topics: Eliciting and capturing the enterprise understanding Methods and Tools for Representing the Enterprise Case Study Examples and Results

Description:

This panel will present work that has been done modeling actual enterprises. They will discuss the approach taken to elicit, capture, and model an enterprise. The discussion will include rationale, lessons learned, tools, and techniques that helped them build a successful model. Results of their modeling will be presented including how the enterprise derived value from the model as well as the exercise of modeling the enterprise.
1.3.2 Using Performance‐Based Earned Value® for Measuring Systems Engineering Effectiveness
Authors: Carson Ronald S. , Zlicaric Bojan
Published: November 2014

Performance‐Based Earned Value®1 concepts have been applied to the development of a systems engineering metrics architecture to measure systems engineering effectiveness. Metrics for desirable program outcomes of cost, schedule, and technical quality are identified and also decomposed into their contributors. Focusing on SE work products provides a basis for ensuring that the closed‐loop operation of the SE management function provides measurements of the work products, not just the processes. Specific examples of requirements quality and compliance metrics and data are provided.