AbstractAn essential role of systems engineering is to aid in overcoming complexity during development. As system complexity increases, a greater number of organizations are being asked to contribute architecture/design content for systems development. An essential challenge to overcome is how to ensure digital continuity in connecting system models to form systems of systems (SoS) models. Leveraging recent developments in digital engineering (DE) and model‐based systems engineering (MBSE) this paper presents a SysML model federation methodology enabling multiple collaborating organizations to contribute system models and form a descriptive SoS architecture model. Systems engineers applying this methodology are able to reuse constituent system model content to describe the larger SoS behavior and structure while promoting reusability and commonality and are therefore better able to ensure correctness and consistency across development. First, a background through the review of SoS engineering (SoSE) and DE/MBSE literature is provided. Then an MBSE process along with specific methods tailoring the use of SysML within the Cameo Enterprise Architecture tool is presented. This work builds upon a previously published Systems Architecture Model (SAM) development method and is designed to permit style diversity across peer constituent models and ensure that every piece of data has an authoritative source of truth (ASOT) within the federation. This paper then presents the application of this methodology to the Ranger Lunar Rover system by making use of its openly published SysML model. Finally, the benefits and challenges of this methodology are discussed prior to drawing closing conclusions and identifying future areas of research.

AbstractOne of the impediments to transforming urban cities into smart cities is the security and privacy concerns that arise due to use of Internet of Things (IoT) devices in various smart city applications. While IoT device vendors publish their security and privacy policies, manual evaluation of these policies is tedious and prone to misinterpretation as there is a lot of variability in the language used across IoT vendors. Local administrations and policy analysts are faced with understanding the implications of integrating IoT devices with differing security and privacy characteristics but lack methods that support them in analysis of privacy characteristics from a holistic perspective. In this paper, a methodology for knowledge elicitation from textual information is outlined to evaluate privacy characteristics of IoT devices. The methodology includes natural language processing and deep learning techniques to evaluate the relevance of IoT privacy policies to the National Institute of Standards and Technology (NIST) security and privacy framework 5. Based on the analysis, text similarity scores are calculated for each IoT privacy policy document and each section of the policy document is labeled to NIST categories and functions. Analysis of these resulting labels and scores helps analysts to gain insights on each privacy policy as well as provide a holistic perspective of the privacy characteristics of IoT devices used in smart city applications. For example, all the policy documents used in the study talk about Protect domain and half of the documents cover Detect domain. However, most of the policies contain gaps regarding the Identify, Respond, and Recover domains. The study has implications for policy analysts, IoT vendors, and smart city administrators in terms of understanding the privacy gaps in IoT devices with respect to the NIST framework which can ultimately support policy alignment to address privacy concerns for smart cities.

AbstractIncreased demand on rail, due to climate initiatives and passenger numbers, places significant pressure on existing railway operations; specifically on capacity, operational flexibility, and network robustness. These pressures are exacerbated by constraints, which prevent the construction of new track and infrastructure. This results in the need to use existing infrastructure and operating processes. One proposed solution is digitalization, which results in autonomous rail, where automated and connected intelligent transport systems facilitate smart traffic management. However, this generates the challenge of integrating autonomous trains and their associated technologies with existing infrastructure and operations. To understand this issue from an enterprise level, this paper has applied Brian Wilson's Soft Systems Methodology (a variation of Checkland's methodology) to the problem situation. This methodology explores and investigates the existing rail system in Great Britain (UK less Northern Ireland) and its stakeholders. The paper aims to propose a solution into how to transform the legacy system into one which incorporates autonomous operations and ultimately becomes fully autonomous. It culminates in a series of models that are relevant to those with a legitimate interest in the system. The models identify the activities required to analyze whether autonomy is worthwhile and if it is, how to successfully integrate it with legacy operations. Additionally, the models provide the basis for which a formal stakeholder analysis can take place.

AbstractAs humans play a significant role in maintaining, supporting, and operating systems, it is important to include humans in digital engineering models to ensure that the sociotechnical system is capable of meeting stakeholder requirements. The current research proposes a taxonomy of metrics and taxonomic nomenclature useful for representing humans in systems engineering and integration. This taxonomy is intended to provide a structure for considering metrics in frameworks such as the Objectives and Metrics portion of the human view architecture, as well as in trade studies which may be represented in MBSE models. The proposed taxonomy categorizes human‐centered metrics into four categories, including those affecting system performance, system readiness, interface fitness, and occupational health and safety. It is further recognized that many of these metrics can be affected by the mental or physical state of the human, which are commonly captured in human factors metrics, such as workload or situation awareness. It is proposed that this taxonomy can guide the selection of human‐centered metrics which affect the system's ability to meet system stakeholder requirements.

AbstractSystems engineering can be applied in a broad spectrum of sectors, but only its analysis tool has been applied in the field of water resources management. Because systems engineering has a separate community of practice from water resources, there is little crosstalk between the two fields. As a result, the systems engineering functions that support planning, design, production, procurement, and customer support are not being applied to water systems. Meanwhile, water systems exhibit complexities that have generated a separate field named Integrated Water Resources Management that continues to confuse its followers after several decades. Its methods are applied to a broad spectrum of water issues that affect multiple stakeholders with conflicting interests and involve distinct subsystems, such as water supply or hydropower, as well as combinations of them. Use of systems analysis for such water issues began six decades ago, but it is still a work in progress. Evolving methods of systems engineering offer new possibilities to address problems of water resources management, but they must extend beyond systems analysis, which belongs to multiple disciplines. Examples show possibilities to apply systems engineering methods when water issues exhibit attributes of engineered systems and do not involve social and environmental complexities that cannot be included in system boundaries. Collaboration among systems engineering and water resources management would offer a fertile test bed to advance both fields.

AbstractThe implementation of Fourth Industrial Revolution technologies at a manufacturing site requires analysis of the site status based on real‐time information, optimization of the processes, and onsite execution. However, in labor‐intensive industries, such as the garment‐manufacturing industry, it is extremely difficult to develop smart factories based on real‐time onsite information because such industries are accustomed to managing labor using empirical expert judgment; moreover, they require rapid production circulation and are dependent on human‐related factors. In this study, we developed an optimization simulator using onsite real‐time production information that provides decision‐making support to maximize the productivity of a garment production plant. As an optimization method, a genetic algorithm was used to incorporate operator relocation into various garment production line variables. Through the developed simulator, field managers can predict and optimize productivity with simple operation in connection with production information. The application of the simulation optimization process to an actual production line in an Indonesian garment factory indicated that the simulator can improve productivity by 34.8%. The results of this study will provide guidance regarding the application of industrial information integration in labor‐intensive industries using methods that can systematically support decision‐making to achieve optimal productivity.

AbstractMilitary program management and system engineering re quire the expression of costs and delay trade‐off with respect to system architecture. If architecture frameworks (AF) such as NATO (NAF) were designed to fill this common need, their current state is essentially descriptive. As it turns out, building defense systems architectures using those frameworks in a properly anticipated cost/delay budget envelope would require to have all system engineering already solved, because the architecture frameworks are designed to provide an explicit representation of the operational domain that can be used in analysis, for articulation of issues and requirements, as support to planning, and as a means of solution design and validation, among other things. Thus Quality‐Resource‐Time <Q,R,T> optimality in a regularly evolving environment cannot be represented in acceptable delay without automated optimization assistance. Our contribution in this article explores coupling architecture framework with operation research (OR) models to enable computer assisted design and evaluation of heterogeneous views in NATO Architecture Framework (NAF). Our illustrative example is a Linear Programming based bridge between program management and system engineering to anticipate <Q,R,T> optimal trade‐offs. This article presents promising results, with which we hope to show how OR and AF will be indivisible in architecture evaluation process.

AbstractRemote work is becoming increasingly common, a trend accelerated by the global COVID‐19 pandemic. Existing remote work research fails to address the challenges and needs of engineers working remotely in Complex Aerospace System Development (CASD), the field responsible for creating and operating aerospace systems. This article presents an exploratory study to understand the challenges, benefits, and strategies when working remotely in CASD. We interviewed 12 CASD engineers working remotely at a major aerospace corporation. We ground our findings in six characteristics of CASD work (complex systems; design paths and feedback loops; relationships with suppliers, customers and regulators; distinct knowledge and skills; one‐off innovation; and high cost of experimentation) and discuss how each of these characteristics challenges remote work. The findings show that CASD requires many teams to work together, and this is encouraged through informal communication, which almost disappears in a remote setting. CASD requires frequent feedback, and we found that feedback was slow when working remotely. Participants found it challenging to demonstrate systems to customers and verify drawings with suppliers, and the interpersonal relationships, which help to bridge disciplinary divides, were harder to maintain remotely. The one‐off nature of the systems designed meant that conceptual work was important, but participants lacked the virtual tools to do this effectively. Lastly, testing hardware components required close virtual communication between technicians and engineers, which was tricky in a detail‐oriented context. This study motivates areas for future work to better understand and address the nuances of remote work by engineers in CASD.

AbstractLessons learned through MBSE adoption efforts is one of the key ways of communicating best practices and recommendations for MBSE. This study compiles lessons learned from published case studies and practitioner interviews. Lessons are summarized into categories such as adoption strategy, modeling practices, and communication. This paper provides a source for future adopters of MBSE to review best practices and recommendations from a multitude of different experiences. This should improve the adoption and implementation of MBSE.

AbstractSignificant contributions in the existing literature highlight the potential of softgoal interdependency graphs towards analyzing conflicting non‐functional requirements (NFRs). However, such analysis is often at a very abstract level and does not quite consider the run‐time performance statistics of NFR operationalizations. On the contrary, some initial empirical evaluations demonstrate the importance of the run‐time statistics. In this paper, a framework is proposed that uses these statistics and combines the same with NFR priorities for computing the impact of NFR conflicts. The proposed framework is capable of identifying the best possible set of NFR operationalizations that minimizes the impact of conflicting NFRs. A detailed space analysis of the solution framework helps proving the efficiency of the proposed pruning mechanism in terms of better space management. Furthermore, a Dynamic Bayesian Network (DBN) ‐ based system behavioral model that works on top of the proposed framework, is defined and analyzed. An appropriate tool prototype for the framework is implemented as part of this research.