bluuebunny/crossref_metadata_2025_split huggingface dataset:
11.5.2 Systems Engineering the U.S. Education System
Authors: Wells Brian H. , Sanchez H. Alex , Attridge Joanne M. 
Published: November 2014

AbstractThis paper presents the recent and on‐going activities that are applying systems engineering to the U.S. education systems to identify potential improvements that will increase student proficiency and interest in Science, Technology, Engineering and Mathematics (STEM). Because applying the methods of systems engineering to a complex human system, like the U.S. education system, is somewhat novel, system dynamics modeling, which is not typically used in aerospace systems engineering projects, was required. Also, because of a lack of systems specific expertise and the need for new and diverse ideas, the project was performed as a student project with competing teams. The complexity of the U.S. education systems required an examination of the total system and then focusing on a limited portion of the system. This paper shows how the complexity was dealt with and how the particular area for detailed examination was selected. Current activities and plans are also presented.
11.5.3 Systems Engineering Education for Civil Engineering Students
Authors: van Nederveen Sander , Ravesloot Christoph Maria , Braat Karel , de Ridder Hennes 
Published: November 2014

AbstractCivil infrastructure projects have become increasingly complex over the last decades. For that reason, systematic approaches such as systems engineering have been found very useful for making large and complex projects better manageable. This implies that civil engineers of the future must gain knowledge, insight and experience in systems engineering during their study. This paper discusses the use of system engineering concepts and methods in design project courses for civil engineering students. The use of system engineering‐related methods such as project decomposition, requirements management and interface management are discussed. Although only basic system engineering methods are used, it seems that students get a sound basis for the system engineering concepts that will be useful in their future lives as managers in civil engineering projects.
KR09 Using Historical Lessons‐Learned in the Systems Engineering Process
Authors: Ferreiro Larrie D. 
Published: November 2014

AbstractSystems engineers often do not have a way to systematically apply historical “lessons‐learned’ in their day‐to‐day activities, especially when applied to non‐traditional areas of engineering management. Risk analysis has become the standard systems engineering decision‐making tool to evaluate uncertainties in cost, schedule and performance. Therefore, such historical insights need to be modeled within that framework to be mutually comprehensible and useful to both historians and systems engineers. To demonstrate this framework, I examine historical “lessons‐learned” in several relevant areas: the implications of operational flexibility on system design; complex system‐accident theory; and the considerations of technological “reverse salients”. The insights developed through historical analyses can be used as a decision‐making tool for systems engineers, by developing a subjective “risk rating” assessment as a part of the overall set of decision aids to estimate uncertainty in performance, cost and schedule. This interface between historical insights and the priorities of systems engineers can enrich the basis of programmatic decision‐making.
KR17 Risk Cube Data Biases
Authors: Smith Eric D. , Siefert William T. 
Published: November 2014

AbstractRisk cubes used in industry characterize particular risks in terms of the likelihood of occurrence, and the consequence of the actualized risk. Human cognitive bias research led by Daniel Kahneman and Amos Tversky exposed systematic translations of objective probability and value as judged by human subjects. An examination of industry‐generated risk cube data reveals evidence of biases in the judgment of likelihood and consequence. In addition, other biases – including a ‘diagonal bias’ – are revealed in the risk cube data. The evidence presented could improve risk cube based risk analysis.
KR23 Value‐Focused Systems Decision Making
Authors: Parnell Gregory S. , West Paul D. 
Published: November 2014

AbstractThis paper presents the Systems Decision Process, a value‐focused systems engineering decision process used to support fact‐based decision making. The process provides analysis products to support major system decisions that are made at major decision gates in each system life cycle stage. The process has four phases: problem definition, solution design, decision making, and solution implementation. The process emphasizes defining, measuring, designing, and implementing solutions to achieve stakeholder and decision maker value. The process should be tailored to the system, the stage in the system life cycle, and the decision environment.
KR25 System of Systems Architecture Evaluation Using Evolutionary Computation
Authors: Simpson Joseph J , Dagli Cihan H. 
Published: November 2014

AbstractEvolutionary computation and evolutionary algorithms represent a developing science and technology that can be effectively applied to the generation and evaluation of system of systems architectures. A general technique used by systems engineering professionals is a binary matrix representation of a system or system of systems. The specific meaning and semantics of the binary relationship depends of the type of representation used. Typical representations are, “N squared”, design structure matrix, dependency structure matrix, and implication matrix. A key feature of these typical representations is their direct relationship to the structure required in an evolutionary computational approach. Evolutionary algorithms can be applied to the evaluation and optimization of these matrix structures. A new evolutionary algorithm has been developed that applies specifically to the generation and evaluation of systems and system of systems. This new evolutionary algorithm incorporates a fuzzy inference system in the calculation of the best fit evaluation. The current industrial and social environment is populated with a vast array of existing and developing systems. Any new system must take this context into account. Evolutionary computation is applied to assist the system architect and engineer in the evaluation of these complex configurations and interface sets.The new evolutionary computing techniques are applied to system of systems architecting tasks using a well defined set of measures of effectiveness (MOE). The systems architecting task is divided into three general areas organized around the roles and responsibilities associated with the system architect, the system customer and the system engineer. The system architect is responsible for the complete system operation and MOE balance, focused on life‐cycle cost and risk. The customer is responsible for the mission profile and mission functions. Operational effectiveness and operational suitability areas are the responsibility of the systems engineers. Affordability, risk, operational effectiveness and operational suitability are the four MOE used to evaluate the candidate system of systems architectures.
KR26 A Systems Engineering Approach to Embedded Control System Implementation in Buildings
Authors: Yahiaoui Azzedine , Staal Rob 
Published: November 2014

AbstractSystems engineering (SE) is a comprehensive and structured approach for analyzing, designing, creating, and operating a system in a cost‐effective way. SE concepts are therefore concerned with the overall processes of defining, developing, operating, maintaining, and ultimately replacing quality systems. Whereas the building environmental performance concentrates on the details of individual aspects of building components and equipments (civil, mechanics, electronics, ergonometrics, etc.), SE concept needs to be integrated with all aspects necessary to realize efficient control systems in buildings. To explore this potential, the paper proposes a systems engineering approach for the design of distributed control and building performance simulation by run‐time coupling, over TCP/IP protocol suite. In particular, this paper involves a case‐study with two important steps; first consists of experiments obtained in TU Delft test‐cell in order to demonstrate a potential ability of using advanced control strategies in buildings, and then simulation results are obtained with the run‐time coupling mechanism.
1.3.1 Microcosm – A Systems Engineering and Systems Integration Research and Learning Sandpit
Authors: Mansell Todd , Do Quoc , Cook Stephen , Relf Phillip , Campbell Peter , Ross Christian 
Published: November 2014

AbstractThis paper describes the Microcosm program established by DSTO and UniSA to research and to promote good systems engineering and systems integration practice. The initial focus of the Microcosm project is research into the application of Model‐Based Systems Engineering (MBSE) in complex systems engineering and systems integration programs. The paper outlines what Microcosm seeks to achieve with particular focus on the high‐level architecture of the Stage 1 solution. The paper concludes by describing the Stage 1 implementation of the Microcosm ‘sandpit’ including the information management environment, the simulation, modelling and control environment, and the physical systems including unmanned ground vehicles, sensors, communications infrastructure and effectors.
1.3.3 Conceptual Model for Space Mission Systems Design
Authors: Mandutianu Sanda , Moshir Mehrdad , Donahue Kenneth , Laboratory Jet Propulsion 
Published: November 2014

AbstractModelling tools and methodologies without concerns about human understanding may not be suitable for communicating with stakeholders, customers, or management. There are many factors that can increase understandability. Using a generic systems engineering modelling language certainly helps but is not always enough. The understandability of modelling can be improved by using better modelling techniques and strategies, which might be part of a coherent methodology with a deliberate emphasis on communicability. The paper describes the application of Systems Modeling Language (SysML) to the design of a JPL mission using the Object Oriented System Engineering Method (OOSEM). Complementary formal modelling using the Web ontology language (OWL) has also been investigated. Using only traditional means, under increased demands on productivity and decreased resources, system integration may become high risk, and lifecycle support is expensive and may result in rapidly outdated components. Model‐based systems engineering (MBSE) is showing promise as a solution to this problem in addition to and enhancing more traditional approaches. The space mission systems models represent sciences and technologies including astrophysics, physics, electronics, mechanisms, hardware and software. Representations of system architecture specification, requirements, evaluation of alternative architectures and trade studies, including static simulation of the performance are grouped into views that represent different stakeholder viewpoints. The human understandability of the resulting models and how the modeling process can increase communication and understandability has also been addressed and observations are reported.
2.1.1 A System of Systems Approach to Warfighter Training
Authors: Parkinson David 
Published: November 2014

AbstractThis paper explores the traditional Systems Approach to Training (SAT) for the Warfighter, suggesting improvements for complex large‐scale, live, and virtual training systems. Such systems are required to deliver military effectiveness and enable Readiness & Sustainment (R&S). It has long been accepted that the proper way to design training is by adopting a systematic approach to assessing the training gap, the design of the syllabus, and the evaluation of the performance improvement. This Systems Approach to Training (SAT) parallels Instructional Systems Design methodology, the latter also being a model to aid in the design, development, and delivery of a training program. The paper discusses the complexity of such large‐scale military training systems and presents a case for designing them using Systems Engineering (SE) principles. The traditional SAT method applies, but does not cope with the overall requirements capture, architecture design or interoperability; nor was it designed to do so. Complex large‐scale training systems are human centric and consequently should be designed using the most appropriate Systems Engineering (SE) processes, methods and toolsets.
2.3.2 An Architecture‐Centric Approach for Systems Design
Authors: Neill Colin J. , Sangwan Raghvinder S. , Paulish Daniel J. 
Published: November 2014

AbstractThe most critical requirements for the lifetime value of a system are its non‐functional requirements such as reliability, security, maintainability, changeability, etc. These are collectively known as the ‘ilities’ and are typically addressed in system design once the functional architecture has been developed. In this paper we propose the use of architecture‐centric design that modifies this standard workflow so that those non‐functional requirements, which actually reflect the true business needs, are addressed first. This ensures that the final system better reflects and embodies those architecturally‐significant requirements rather than having them addressed secondarily. This is an important change since the ‘ilities’ are systemic properties (properties of the system as a whole) rather than systematic properties (properties of individual components or sub‐systems) and are therefore difficult to address once the functional architecture has been determined and the separation of concerns is already somewhat completed. We provide an example of the approach based around a simplified case study of an online, on‐board health monitoring system for shipboard gas turbine electricity generators that collects, filters, analyzes, transmits, and mines sensor data from the generators subsystems.
3.2.4 Study on the Influence of Component Uncertainty on Reliability Estimation of Multi‐State Systems with Continuous States
Authors: Zhang Chi , Mostashari Ali 
Published: November 2014

AbstractExisting reliability evaluation methods rely on the availability of accurate component states data. They will become ineffective when the states themselves are uncertain or unknown, which usually happens during the early stages of the development of new systems. In such cases it is important to understand how uncertainties will affect the system reliability measures. Another drawback of current methods studying reliability of Multi‐State System (MSS) is that they only considered the systems whose components have several discrete states. For those whose components have continuous states, these methods are not effective either. This paper considered the continuous distribution of components states during the approximation of Multi‐State System (MSS) reliability and proposed a method to assess the reliability of this kind of system using Monte‐Carlo simulation. This method will also be useful when we have no enough data to know the exact discrete states and related probability, and can only estimate components states distribution types and related parameters. Two examples were employed to illustrate the method. Comparison of the two examples shows that component state uncertainty has significant influence on the assessment of system reliability. Our effort will make the reliability approximation more realistic compared with existing methods.
3.3.1 Divergent Thinking in Systems Engineering Practice: Is There a Shortfall?
Authors: Armstrong James R. 
Published: November 2014

AbstractDivergent thinking produces an expanded definition of both problem and solution space. Convergent thinking leads to the selected solution. A balance of the two is an essential element of effective systems engineering practice. A significant predominance of convergent thinkers and shortage of divergent thinkers has been noticed in a group of systems engineering students. A negative impact on exercise results was also noticed. If this is a valid observation of the general systems engineering field, there are serious implications that must be addressed in training and at work. This paper outlines the initial observation, impact, and potential for future research.
3.5.0 Can We Engineer the Emergent Behavior of A System‐of‐Systems?
Authors: Hsu J. C , Axelband E. , Madni A. M. , Dagli C. , McKinney D. 
Published: November 2014

AbstractEmergent behaviors exist in biological systems, physical systems and human performance. It is an inherited nature of a System‐of‐Systems (SoS). SoS displays a global complexity that cannot be adequately managed by hierarchical structures and central control; therefore, traditional systems engineering and management approaches are necessary but insufficient for a SoS.Little is currently known about constructing an interoperable network of systems and the incorporation of emergent behaviors. The purpose of this panel is to explore the possibilities of developing an architecture model including the emergent behavior.The challenge is how to understand the initiation mechanisms of the emergent behaviors for a particular system architecture model so that the resident beneficial or harmful emergent behaviors can be enhanced or mitigated with selected changes in the model. Is model‐based the only feasible approach to develop the architecture model with emergent behavior? If this is the answer, what kind of modeling methodology? Should it be solely based on agent‐based modeling or a combination of SysML and agent‐based? Is SysML ready to deal with emergent behavior?For a non‐modeling consideration, can we plan for the beneficial or harmful emergent properties? How do we overcome development friction that is bound to arise when there are complex, independent, overlapping governances, for example, the customer requirements for a SoS evolve over time, etc.? There may only be SoS modeling at the level of the government agency, which actually procures but does not build, and not at the level of contractors who build the next generation of technologies.
4.1.2 Product Upgrades Based on Minimum Expected Quality Loss
Authors: Langford Gary 
Published: November 2014

AbstractThe need to maintain or sustain a product's usefulness to or beyond its initial lifecycle expectancy is often driven by investment costs, market share, sales revenues, new product release schedules, standardization, uninterruptable usage, or declining budgets. A question then arises as to how often to upgrade a product. Aside from these typically discussed rationales, the paper concludes that a viable approach is to consider the upgrade cycle that results in the minimum cost based on quality. A general quality loss function was developed to investigate the expected quality loss for quality characteristics such as nominal‐the‐best, smaller‐the‐best, and larger‐the‐better. It is shown that when a shape parameter is introduced into the loss function, product upgrade cycles can be managed to minimize the expected losses.
4.1.3 System Architecture Entropy
Authors: Cloutier Robert , Verma Dinesh , Bone Mary , Sommer Kim 
Published: November 2014

AbstractThis paper will introduce the concept of Architecture Entropy in the context of systems engineering and complex systems. Entropy has been explored and discussed in other domains, drawing an analogy to its origins in physics. In its original context, entropy describes the degree of randomness, or level of chaos, that occurs over time. The purpose of this research is to explore application of the concept of entropy for understanding the vitality of legacy system architectures. The discussion is supported by examples of current architecture challenges that may be attributed to architectural entropy. Specific examples are presented to better understand the applicability of architectural entropy.
5.1.3 Testing Solutions through SysML / UML
Authors: Richards Dave , Stuart Andrew , Hause Matthew 
Published: November 2014

AbstractAs systems become increasingly complex and the time to market decreases, systems engineers have to develop novel solutions to testing. The scenario is particularly acute when dealing within the safety critical domain. This paper will seek to highlight how UML and in particular, improvements introduced by SysML can aid the testing process in terms of verification, validation and simulation of software, firmware and mechanical systems. This paper will highlight how UML and SysML constructs can aid testing and is based on many years experience of building and testing systems as well as the experience gained by client companies during consultation. It will highlight on a practical basis how clients have integrated testing into their UML/SysML models to improve their processes and products.
5.3.3 A Method for Analyzing Fundamental Kinesiological Motions of Human Body by Applying Interpretive Structural Modeling (ISM)
Authors: Kayo Munehiro Michael , Ohkami Yoshiaki 
Published: November 2014

SummaryThe objective of this paper is to analyze interconnectedness of kinesiological motions by applying a well‐known systems modeling approach called the Interpretive Structural Modeling (ISM). This approach is applied to the previously proposed Somatic Balance Restoration Therapy (SBRT), developed by one of the authors and offers a safe way in correcting imbalances and distortions that occur in the human body. The human body is a complex system composed of over 200 bones and 630 muscles that comprise the musculoskeletal system, which works not only as the frame for the human body, but as the engine of human kinetic motion as well. As a practitioner, one of the authors developed a visually identifiable diagnosis system through many years of accumulated therapy data. Although the authors attempted to find a more methodical approach to justify the SBRT by inventing the unique “Motion Diagram”, a more systematic approach was required for a more efficient and homogeneous treatment. In this paper, the fundamental patterns produced by the SBRT are mapped into an n‐square matrix of dimension 70, based on the Fundamental Body Motions and analyzed by the ISM. This will be followed by graphical representations and classification of the body motions into several categories based on the degree of interaction and activeness. The results has revealed a priority of the fundamental motion patterns which helps find the most effective motions to be used for identifying imbalanced or distorted parts from the larger dimension set.
6.1.1 A structured approach to planning and managing systems engineering capability evolution in a complex through‐life business space
Authors: Harding Alan , Mollett Jennifer , Touchin Malcolm 
Published: November 2014

AbstractThis paper presents ongoing work to structure how we transform systems engineering capabilities to address the how to engineer with a focus on operational capabilities rather than just systems. The paper is based on BAE Systems capability development work, informed by engagement with UK MOD as they move towards managing for capability outcomes.The approach taken has been to construct a concept model and a management process:

Model – the priorities for the model are clarity and simplicity. The model describes a framework divided into cells in which to describe the systems engineering capabilities necessary to conceive, develop, support and operate systems to realise operational capability.
Process – the process covers both the early discovery stage, and the predicted longer term phase of capability evolution.The paper discusses results to‐date and potential future work towards a more rigorous description and assessment tool, intended to have wide applicability.