bluuebunny/crossref_metadata_2025_split huggingface dataset:
How Systems Thinking Provides the Foundation for A W‐Shaped Model of an Effective Technical Leader
Authors: Wozniak Michael 
Published: September 2024

AbstractTechnical Leadership is a relatively new subject that has not been adequately addressed in literature. Behaviors and skills of effective technical individuals and leaders are defined and cited often, including various shape models of individuals. However, a Systems Thinking approach for combining these two mindsets has not been documented. This paper's goal is to provide a background on effective technical and leadership behaviors and skills, relate them to the various shape‐based models of individuals, and ultimately present a novel W‐shaped model describing an effective Technical Leader whose foundation is a Systems Thinking mindset.
A Model for Trust and Distrust: The System Dynamics Approach
Authors: Matsuura Takashi , Shirasaka Seiko 
Published: September 2024

AbstractThe dynamics of trust have evolved from a reliance on human interactions to a newfound dependence on the seamless integration of automation and artificial intelligence (AI) in relationships. Because trust is still treated as elusive in prior research, in this study, we consider a society that utilizes trust as a system and present a panoramic perspective of trust in social systems using the causal loop of systems thinking. The perspective of systems thinking is holistic (integrative) and focuses on the interrelationships among components rather than on the components of the system. Thus, the architecture was presented by integrating the trust and distrust models identified in previous studies. To overcome the challenges presented in previous studies, a model for trust and distrust was developed using a system dynamics approach. By utilizing systems thinking, the dynamics of trust are clearly illustrated among individuals, between individuals and automation, and between individuals and AI. In addition, it will allow for a perspective on the dynamic relationship among trust, reliance, and dependability, which is being investigated in “Humans” and “Automation and AI,” and will contribute to trust research.
TOWARDS A SYSTEMS ENGINEERING ONTOLOGY STACK
Authors: Gregory Joe , Salado Alejandro 
Published: September 2024

AbstractSemantic Web Technologies (SWTs) provide an approach to the structuring and understanding of data. SWTs utilize ontologies, reasoners, and query languages to structure existing knowledge, validate knowledge, and infer new knowledge. Ontologies in particular play a central role in enabling reusability and interoperability between domains. A common way to organize ontologies and their dependencies is in a layered ontology stack. These layers often incorporate top‐level, core and domain ontologies. Libraries of standard instances can also be used. Federating the conceptualization of a domain across upper‐ and lower‐level ontologies improves the reusability of higher‐level terminology in other domains, and therefore improves interoperability between them. The University of Arizona Ontology Stack (UAOS) is a layered, modular ontology stack that has been developed to support digital engineering activities at the University of Arizona. It is based on the Basic Formal Ontology (BFO), and currently comprises five core ontologies and 12 domain ontologies. The UAOS reuses existing ontologies and standards wherever possible. The core ontologies, for example, are based on the Common Core Ontologies, developed at CUBRC, and the Provenance Notation (PROV‐N), a W3C standard. Domain ontologies include the System Architecture Ontology, based on ISO 42010, and the Orbits and Trajectories Ontology, based on CUBRC's Space Object Ontology. In this paper, we report on the development of the UAOS, present examples of how it has been used to support digital engineering research, discuss the challenges of integrating ontologies from multiple sources into a cohesive stack, and highlight topics of interest for future research.
Enabling Digital Engineering with Federated PLM – Experiences from the Heliple‐2 Project
Authors: Herzog Erik , Nilsson Robert , Crockford Judith , Berezovskyi Andrii , Holm Torbjörn , El‐khoury Jad , Ringenhall Tord , Gery Eran , Albinsson Stefan 
Published: September 2024

AbstractImplementing a digital engineering infrastructure is a strategic endeavour for any organisation. In this paper an investigation in the feasibility of federated Product Lifecycle Management is presented, starting from a presentation of the guiding architecture pattern and an evaluation of implementation alternatives. Interoperability standards from Open Services for Lifecycle Collaboration (OSLC) are introduced along with presentation of tool infrastructure for automatic generation of OSLC interfaces. Implementation experience validates that this is a viable and attractive alternative for implementing digital engineering.
Enable Effective Digital Engineering Information Exchange using Digital Viewpoint Model (DVM) Framework
Authors: Lam Jack , McGervey Sean , Zhang Leqi (Ken) 
Published: September 2024

AbstractThe objective of the Digital Viewpoint Model (DVM) framework is to characterize the content and relationships involved in the exchange of digital artifacts and its curation for stakeholder use and consumption. The DVM Framework structures the characterizations in four inter‐related ontological concepts — Stakeholder, Digital View, Digital Artifact and Process. The Stakeholder concept focuses on the definition of stakeholder needs in terms of perspectives. The Digital View concept focuses on the construction of views that relate inter‐disciplinary data that conforms to stakeholder needs and constraints. The Digital Artifact concept focuses on ensuring the quality and trustworthiness of data being used to construct the digital views. The Process concepts provide a construct to define necessary work activities to extract data to use. Applications of the DVM Framework are described in form of use cases to demonstrate its utility in facilitating effective digital engineering information exchange.
Cultural Differences in the Professional Competencies and Their Implications for Systems Engineers
Authors: Hahn Heidi Ann 
Published: September 2024

AbstractSince 2018, the International Council on Systems Engineering has promulgated a set of competencies for systems engineers. It is organized in a framework structure that describes the knowledge, skills, abilities, and behaviors that are important to systems engineering effectiveness. There are five “levels” of competence, that span from awareness to expert. The five categories of competencies are Professional, Core, Technical, SE Management, and Integrating. This paper focuses on culturally‐based characteristics of systems engineers relative to the Professional Competencies. It includes a discussion of culturally‐based research and conclusions regarding their implications for how to use them in selecting systems engineers, forming and developing systems teams, and making design decisions.
Evolving Roles in Systems Engineering —‐ Insights from Germany's Mechanical and Plant Engineering Sector
Authors: Kaiser Lydia , Wilke Daria , Förster Felix , Köhler Ingmarie , Dumitrescu Roman 
Published: September 2024

AbstractSystems Engineering is developing differently in each sector and region. In German industry, especially in mechanical and plant engineering, Systems Engineering is of major importance. The introduction of Systems Engineering raises the question of which roles and competencies are required. This article examines the evolution of roles in Systems Engineering from a German perspective. Based on a literature review, the evolution of the identified Systems Engineering roles over time is shown, starting with the seminal publication by Sheard in 1996. It points out that only minimal adjustments and occasional role renaming have occurred. However, the review shows a common understanding of essential areas of responsibility within the SE and changes over time. The next step is to examine the current understanding of Systems Engineering roles in the industry. A quantitative analysis of job postings in Germany reveals a diverse interpretation of the term 'Systems Engineer; more than half of the positions cannot be categorized according to the INCOSE definitions. The job postings are used to determine which tasks are associated with the job, how often they occur, and in what combination. The primary responsibilities of systems engineers include creating and managing requirements, architecture processes, validation, and verification processes, and coordinating with customers and stakeholders. Finally, three representative companies from the mechanical and plant engineering sector were selected to analyze existing roles and tasks. From this, a common understanding of tasks and responsibilities is combined and organized into clusters. These are used by the companies to locate and thus derive their roles. The result is in an integrative approach that enables companies, especially in the midsize and medium sectors, to design the introduction in line with stakeholder demands. In summary, the industry's ongoing adaptation necessitates the evolution of Systems Engineering roles and competencies for successful and sustainable development and implementation of systems.
A Rapid Review of How Model‐based Systems Engineering is Used in Healthcare Systems
Authors: Xames Md Doulotuzzaman , Topcu Taylan G. 
Published: September 2024

AbstractThis study presents the results from rapid review of how model‐based systems engineering (MBSE) is utilized in healthcare systems (HSs). We conduct a review of the last twelve years and find that MBSE adoption in HSs is accelerating, with use of various MBSE languages and tools, as well as their integration with other simulation and modeling techniques. We find that similar to engineered systems, the most common MBSE language is systems modeling language (SysML), followed by unified modeling language (UML) and others. Additionally, we observe that MBSE methods are frequently used in conjunction with other analytical techniques, such as simulation and co‐simulations, to analyze and enhance various HS operations, or to assist with making tradeoffs between HS attributes such as quality and cost. Moreover, we provide a non‐exhaustive classification of current research based on two dimensions: healthcare applications and MBSE use cases. Notably, MBSE is being implemented generally with patient‐centric objectives in various HS domains, including IoT‐enabled smart healthcare, clinical medicine, medical device development, healthcare process enhancement, and healthcare facilities management. While the primary MBSE use case involves modeling different aspects of healthcare operations, there is a significant number of studies that pursue requirements engineering, systems analysis, integration, verification and validation, as well as risk analysis and management. Furthermore, we identify two promising research gaps. First, there is a need for the integration of MBSE with state‐of‐the‐art data‐driven analytical methodologies such as hybrid simulation and artificial intelligence techniques. Second, HSs could greatly benefit from representing the cognitive functions and processes of human decision‐makers in the loop, such as healthcare providers (e.g., doctors and nurses), who are instrumental in sustaining the HS performance and functionality. We contend that MBSE and other SE methods and techniques could improve HSs design, operations, and management; while fostering resilience and long‐term sustainability.
Model‐Based Architectural Patterns for Teaching Systems Engineering
Authors: Lohar Bhushan , Cloutier Robert 
Published: September 2024

AbstractSystems Engineering (SE) may be one of the fastest‐evolving engineering disciplines today. With each technological innovation, the practice of systems engineering is challenged to adapt. Two such practices that have been appearing in university curricula are Model‐Based Systems Engineering (MBSE) and Architectural Patterns. The combination of MBSE and patterns has proven to be a powerful construct. This paper looks at the use of a space‐based patterns library (language) in a graduate‐level system engineering curriculum to teach MBSE. The International Council On Systems Engineering (INCOSE) “Systems Engineering Vision 2035” defines, that by 2035, the systems engineering practices will be based on a set of theoretical foundations and other general principles that are continuously taught as part of a systems engineering curriculum. This paper provides an approach and a solution to the needs of academic coursework for teaching model‐based systems engineering. The method presented in this paper details the usage of the pattern library concept developed for NASA and its usage by the systems engineering graduate students that eases the development of new space‐based systems architectures. Again, our objective is to incorporate INCOSE Vision 2035 in academia using Model‐Based Architectural Patterns for Teaching SE.
INCOSE Systems Engineering Competency Assessment Guide Systems Modeling Language (SysML) Model Description
Authors: Amenabar Juan P. , Whitcomb Clifford A. 
Published: September 2024

AbstractThe INCOSE Systems Engineering Competency Framework (SECF) and INCOSE Systems Engineering Competency Assessment Guide (SECAG), published in 2018 and 2023 respectively, provide a requirement definition for 37 systems engineering competencies each with knowledge, skill, ability, and behavior (KSAB) indicators across 5 different proficiency levels along with sample evidence against each of these indicator requirements. These publications form a static representation of the framework structure and associated database. This paper describes the development of a Systems Modeling Language (SysML) model that provides a digital representation of the architecture framework and associated requirement and evidence entry databases. A description of the metamodel and data structure is presented as well as a tailoring approaches for use and a series of evolving model use cases.
Automating Rule‐Checking to Identify SysML Modeling Errors: A Preliminary Study in a Classroom Environment
Authors: Vinarcik Michael J. , Jung Sukhwan , Salado Alejandro 
Published: September 2024

AbstractAmong other benefits, the adoption of Model‐Based Systems Engineering (MBSE) or Digital Engineering (DE) is expected to decrease the number of escaped errors in a project by enabling early error detection within the modeling environment. This contributes to reducing the costs associated with corrective activities, which are generally greater in later phases of development. This paper provides an empirical insight into error detection through a study of models developed by students in a graduate MBSE course, where they leveraged the use of automated rule checking within the modeling tool. The dataset covers 10 editions of the course, spanning 2016‐2023, and contains 601 models. The study shows that the term project models resulted in nearly zero latent errors when non‐stylistic rules are concerned, with most of the latent errors categorized as stylistic rather than fundamental violations.
Excuse me Sir/Madam, which Model?
Authors: Hällqvist Robert , Herzog Erik , Axehill Johanna Wallén , Palmer John R. 
Published: September 2024

AbstractDevelopment of complex systems through the application of Model‐Based Systems Engineering (MBSE) will require the creation and maintenance of multiple models, created using multiple languages. Hence, structuring the models such that there is efficient support for incremental development requires some foresight. Having models with multiple or unclear purposes may introduce situations where parts of the organisation will ask for modification for representing a desired future system state, whereas other parts of the organisation require it to remain unchanged in order to represent the present state. This paper introduces a structure with associated terms and characteristics of the different model types in order to provide guidance to an organisation. In particular, it extends previous work on model tenses, capturing different time perspectives/purposes on the models, to also include model usage for keeping track of the actual state of a realised system instance. For example, the concepts of Digital Twin and Digital Shadow are discussed and conceptualised. As such, the contributions made in the paper allows an organisation to reason about the completeness of their modelling methodology and its applicability to support incremental development. Above all, the paper spells out clearly that for a complex heterogeneous system, any request for an update to “the model” will prompt the response “Excuse me Sir/Madam, which model?”.
A Case Study of AI Usage within the INCOSE Technical Process
Authors: Chagnon Pete , Forney Rachelle , Harkenrider Kenneth , Wood Emily , Zhang Yiyang , Weaver Jonathan 
Published: September 2024

AbstractThe purpose of the research described herein is to analyze the use of AI platforms by a user implementing a generic Product Development Process (PDP) mapped onto the INCOSE Technical Process (ITP) and to identify the advantages and disadvantages of doing so. The team's original work on a previously finished project, which followed the PDP without using AI tools, served as a crucial benchmark for conducting a comparative analysis with responses from the AI platform. It was found that only some of the stages of the ITP currently allow for effective template prompts. Much of the useful work requires an open, somewhat extensive two‐way dialog with the AI platform, not a simple plug‐and‐play approach. The wording is important for each prompt, so the user must understand the aspects of the problem they are trying to solve. While the two Al platforms utilized produced comparable responses, the output depended heavily on the prompt context. Evaluating the AI platform performance is difficult because the AI platform response (output) and the prompt inserted by the user (input) are not mutually exclusive. The team found that AI can be more useful in customer needs definition and stakeholder identification, and less useful in concept selection and search internally steps. The recommendation is to employ AI as a supplement to the ITP rather than as the exclusive contributor. As technology continues to advance, we can expect to see new applications emerge, and the team expects that AI's impact will likely be quite significant.
Models, Models Everywhere! A practitioners view on the reality of modeling
Authors: Kemp Duncan , Hoffman Christopher , O'Neil Meaghan 
Published: September 2024

AbstractThis paper addresses three of the most common real‐world challenges to modeling. The INCOSE Vision 2035 correctly states that the future of SE is Digital and Model Based. Achieving this requires significant development of the state of the art in Digital Engineering and Modeling. The focus of this paper is, however, the significant gap between the current potential of today's models and the actual practice. As practitioners each with over 20+ years of industrial experience, the authors describe problems that plague current modeling practice. The paper: describes the different types of models and their uses; provides a high‐level generic model development approach; and addresses some of the real‐world challenges that modelers and their managers need to address.
Empowering Model‐Based Systems Engineering Through Metamodeling
Authors: Wise Richard , Zimmer Rhett 
Published: September 2024

AbstractA critical enabler for Model‐Based Systems Engineering (MBSE) and Digital Engineering (DE) is the generation of coherent and consistent views of a system‐of‐interest based on information within a system model. In practice, system model development is facilitated through domain‐specific profiles, style guides, reference models, and low‐fidelity meta‐models to create coherent and consistent system information. Each of these approaches are useful but are insufficient for robust and automated verification of system models to an ideal. Furthermore, the expression of domain‐specific concepts and semantics relies on the proliferation of non‐standard, domain‐specific profiles as standard system modeling languages like the Systems Modeling Language (SysML) are general purpose. This paper proposes a novel approach to creating precise, machine‐interpretable metamodels implemented as a lightweight Unified Modeling Language (UML) profile. The profile includes numerous features that allow model architects to quickly specify context and domain‐specific modeling constructs without creating non‐standard stereotypes to apply domain‐specific meaning and usage rules. Three kinds of constraints can be inferred based on the relationships between meta‐model elements: type, multiplicity, and default value. Applications of well‐formed metamodels include a shared understanding of the intended model format and structure, as well as the one‐time programmatic generation of an encompassing suite of validation rules to evaluate a system model against the inferred constraints, thus ensuring consistency. Additional applications include programmatic generation of model analysis metrics, system models from metamodels, metamodels from reference models and element finding queries, and the ability to update a system model based upon the updated metamodel automatically. Use of the approach results in reduced time in system model development and analysis and ensures coherency and consistency of information thus increasing stakeholder use and confidence in the system model.
The Importance of Being Björn – Experiences from Five Age Cohorts of Female Systems Engineers
Authors: Johansson Marianne , Axehill Johanna Wallén , Larsson Åsa Nordling , Cederberg Linda , Chiesi Stephanie Sharo , Palmer Erika 
Published: September 2024

AbstractThis paper gives an overview of the situation for Swedish female systems engineers at an engineering‐dense company (Saab Group) and societal factors of impact for their situation. We have interviewed five age cohorts of female systems engineers and let them share their personal experiences. Some key findings are that the older age cohorts have paved the way for the younger, but that has in many cases been costly for the individuals. Changes in society have in general contributed to better conditions for female engineers, e.g., parental leave compensation and possibility for childcare at a low cost. A remaining problem is the lower proportion of female technical leaders compared to female systems engineers. Females are often encouraged to take roles as project manager or line manager, and therefore technical leadership roles still are heavily male dominated.