bluuebunny/crossref_metadata_2025 huggingface dataset:
Model‐Based Systems Engineering (MBSE) Application in Nuclear Power Plants (NPP)
Authors: Kawamura Ken , Arifin Habibi Husain , Ong Ho Kit Robert , Brun Thomas , Chimplee Nasis , Wu Daphne
Published: September 2024

Companies in the nuclear power sector are constantly being challenged to improve their safety and reliability due to increasing complexity arise from evolving safety regulations, long production life, interdisciplinary collaboration, and the need for analyzing the impact of the changes in an operational life cycle. Recognizing these challenges, the paper proposes a transition to Model‐Based Systems Engineering (MBSE) as a transformative solution to improve the management of such complex systems. With this objective, this paper presents a workflow implementation that demonstrates the MBSE methodologies to define a concept model, system architecture, impact analysis, safety and reliability analysis, and operational decision‐making of Nuclear Power Plants (NPP). The paper concludes that MBSE provides a potent approach to managing NPP by employing graphical models to develop interrelated systems that has strong adaptability to heterogeneous environments and regulatory changes. The simulation results demonstrated an NPP life cycle, impact analysis, and a test case for model‐based safety and reliability analysis for regulatory compliance, operational efficiency, balance safety, and informed decision‐making in NPP. The study also leads to a number of interesting directions of future work such as synchronization through Product Lifecycle Management, integration with Building Information Modeling, Model‐Based Commissioning/Decommissioning, and Model‐Based Cyber System Security tailored for nuclear power systems.
Innovation Ecosystem Dynamics, Value and Learning I: What Can Hamilton Tell Us?
Authors: Schindel William D.
Published: September 2024

Held in Dublin, Ireland, IS2024 invites us to refresh understanding of contributions to systems engineering by Ireland's greatest mathematician–Sir William Rowan Hamilton (1805 ‐ 1865), Professor of Astronomy at Trinity College Dublin and Royal Astronomer of Ireland. His profound contributions to STEM deserve greater systems community attention. Supporting theory and practice, they intersect Foundations and Applications streams of INCOSE's Future of Systems Engineering (FuSE) program. Strikingly, key aspects apply to systems of all types, including socio‐technical and information systems. Hamilton abstracted the energy‐like generator of dynamics for all systems, while also generalizing momentum. Applied to the INCOSE Innovation Ecosystem Pattern as dynamics of learning, development, and life cycle management, this suggests an architecture for integration of the digital thread and machine learning in innovation enterprises, along with foundations of systems engineering as a dynamical system.
Providing tailored heuristic advice to Systems Engineers
Authors: Beale Dean , Oosthuizen Rudolph , Pickard Andy , McKinney Dorothy , Cureton Ken , Stewart Dave , Arnold Eileen
Published: September 2024

An INCOSE‐wide initiative has exposed at least 600 heuristics. Previous work indicates that rationalizing and simplifying this set to make it useful and memorable is difficult, if not intractable. Difficulty Assessment Tools (DATs) have been used for years to characterize the difficulty of a problem and provide tailored advice. This paper explores using a DAT to characterize the problem, and using the outputs to provide heuristic and other forms of advice. To test this approach, 50 heuristics and 10 principles were scored and embedded into an online DAT. An experiment was conducted to determine whether the DAT discussion, recommended approach, and heuristic/principles advice were useful. All teams considered the discussion very useful. As might be expected, the results indicated that the heuristic usefulness was a function of the teams' experience and familiarity with the task. The tool prioritization of suitable heuristics met developers' expectations, but was undetected by the users. This maybe because the heuristics were a hand‐picked set of 50 Heuristics from a set of 600+, meaning all were highly useful. Further work is proposed to check this assessment. The DAT usefulness results indicate that Systems Engineers should use the DAT to inform their approach throughout the lifecycle.
THE DIGITAL ENGINEERING FACTORY: CONSIDERATIONS, CURRENT STATUS, AND LESSONS LEARNED
Authors: Gregory Joe , Salado Alejandro , O'Neal Sharon , Larez Richardo , Reda CJ , Martell Niko , Martin Evan , Colson Matthew , Masterson John , Armenta David
Published: September 2024

In industry, the advancement of digital engineering and the digital thread aims to reduce the impact of knowledge ‘siloes’ by providing a way to integrate data across the entire system lifecycle and across multiple domains. In a typical engineering curriculum, however, courses are still treated as ‘siloes’, and students often do not have the opportunity to experience this industrially relevant approach to engineering. The Digital Engineering Factory (DEF) is a digital engineering environment under development at the University of Arizona to support engineering students. The DEF supports students by providing access to multiple engineering tools and is structured using a ‘hub‐and‐spoke’ approach to consolidate data from these tools. Through this connected architecture, students can transfer data generated in a particular course to tools for use in other courses. Connecting course activities in this way enables students to experience a complete end‐to‐end system lifecycle. At its ‘hub’, the DEF uses Violet to integrate data from multiple sources, create a digital thread, and generate a graph representation of the dataset. This knowledge graph, written in the Ontological Modeling Language (OML), can be viewed in OML Rosetta and is structured according to the University of Arizona Ontology Stack (UAOS). The use of the UAOS and OML Rosetta allows instructors to leverage semantic web technologies to support teaching activities such as grading. In this paper, the authors review the objectives of the DEF, discuss the status of the project, and highlight current limitations and lessons learned with regards to its deployment. These may be useful to inform similar developments in industrial settings.
A Model for Cybersecurity Education through Challenge Events
Authors: Daily Jeremy , Span Martin (Trae)
Published: September 2024

The INCOSE Vision 2035 sets an important Cybersecurity goal: “Cybersecurity will be as foundational a perspective in systems design as system performance and safety are today”. A critical enabler of achieving this vision is educating cyber informed engineers and professionals. Across industries, the demand for talented cybersecurity professionals is high, which means the personnel and students need inspirational education and training to fill these opportunities. This is particularly the case for complex systems in transportation, maritime, agriculture, aerospace, energy, and industries that rely on operational technology implemented with embedded systems. This broad category of sectors need talent and community to address cybersecurity concerns. Often these economic sectors have systems with long lifecycles, regulations, market forces, or other constraints that preclude security solutions envisioned for information technologies. To address the needs for cybersecurity personnel for these industries, a model for developing talent and building community is explained in general terms with specific examples as it relates to automotive, heavy duty, maritime, and agriculture. The model describes the CyberX Challenge, where X is an industry sector, such as the CyberAuto Challenge, CyberTruck Challenge, CyberBoat Challenge, and CyberTractor Challenge. These Challenge Events are described in detail with a focus on the characteristics of what makes those successful or difficult. The successful events have strong industry support, elite instructors, and motivated students. The model for the event is described in detail, with the intention that other industry verticals may inspire additional students and further build communities able to address cyberthreats to our modern way of life. This work directly contributes solutions to addressing the needed foundational concept of Security Education and Competency development as highlighted by the INCOSE FuSE working group.
The Electric Revolution: Fully Electric Transportation System on An Urban College Campus
Authors: Sharifi Zabi , Mansouri Mo
Published: September 2024

This paper offers a comprehensive exploration of the implementation of fully electric transportation systems within urban college campuses. Urbanization and environmental concerns have intensified the need for sustainable transportation solutions, and college campuses serve as ideal testbeds for innovative mobility initiatives. The paper begins by establishing the context through background research, which highlights the adverse effects of urban air pollution and the role of electric vehicles (EVs) in mitigating these issues. The driving forces behind the adoption of fully electric transportation systems are discussed, Benefits, challenges, and implications of implementing electric transportation systems are meticulously examined. The anticipated benefits encompass improvements in air and noise pollution, reduced operational costs, and enhanced campus reputation. Nevertheless, the challenges of infrastructure costs, charging management, and operational intricacies are acknowledged. The paper underscores that successful implementation goes beyond immediate advantages, positioning campus electric transportation systems as living laboratories for research and innovation in sustainable mobility. Additionally, these systems serve as models for neighboring communities and influence regional transportation policies. The paper concludes by laying the groundwork for forthcoming discussions. It highlights the subsequent sections' focus on planning, stakeholder engagement, technological integration, and operational management, which collectively shape the implementation. The paper will employ the application of Systems Thinking approaches, tools, and techniques in order to properly analyze and tackle the problem statement at hand.
Evaluating the Eco‐Efficiency of Urban Air Mobility: Understanding Environmental and Social Impacts for Informed Passenger Choices
Authors: Hoffmann Raquel , Silva Fabio , Nishimura Hidekazu
Published: September 2024

Full electric aircraft with zero CO2 emissions during operations are a promising pathway towards achieving the Fly Net Zero by 2050 goal proposed by the International Air Transport Association (IATA). In this context, Urban Air Mobility (UAM) expects to offer an environmentally friendly alternative through electric Vertical Takeoff and Landing (eVTOL) aircraft. While eVTOLs produce no greenhouse gas emissions, the comprehensive eco‐efficiency of UAM goes beyond the flight phase. This paper delves into evaluating UAM operation's environmental and social impacts, considering the urban space, public perception, operational profiles, and power consumption. Employing causal loop analysis, the study uncovers the relationships that add value or increase impact, assessing UAM passenger transportation's eco‐efficiency. Moreover, the Unified Architecture Framework is used to model the UAM ecosystem and to propose strategies to balance values and impacts in achieving eco‐efficiency. By shedding light on the sustainability viewpoint, this study emphasizes the importance of holistically understanding UAM's operational impact and empowering users to make eco‐efficient choices when opting for UAM transportation. Finally, strategies to provide sustainability awareness to the user are discussed in the Mobility‐as‐a‐System (MaaS) context.
Impact Analysis of using Natural Language Processing and Large Language Model on Automated Correction of Systems Engineering Requirements
Authors: de Oliveira Arthur H. M. , Reis Pedro Almeida , Júnior Fernando Sarracini , Cavalcante Mairon Sena , de Lima Jonathan V. C. , Soares Luis F. C. , Marchiori Lucas Henrique
Published: September 2024

The increasing complexity of Electronic Control Units (ECUs) in the Automotive Industry due to the integration of more sophisticated vehicle features has made the Systems Engineering (SE) application a necessity to define and implement efficient solutions. In this context, requirements emerge as a critical part of the communication between cross‐functional teams. Thus, the more complex systems become, the more requirements are needed to define them. However, lack of information, misalignment and ambiguity on requirements impact the entire development process, resulting in issues later, harder to be fixed. Some studies are being applied to evaluate techniques using Natural Language Processing (NLP) and how it can replace extensive peer reviews, identifying weaknesses in requirements earlier in the process, avoiding wasted time and large financial losses. Normally, NLP is combined with templates such as Easy Approach Requirements to Syntax (EARS), or other rule‐based techniques such as INCOSE's requirements writing best practice rules to define metrics and assess the compliance of the requirements syntax automatically. The focus of this work is to enhance the use of requirements syntax assessment algorithm by combining NLP techniques with Large Language Models (LLMs) to provide automatically corrected requirements.
Role‐Based Structuring of Systems Engineering Teams
Authors: Wozniak Michael
Published: September 2024

There is little documented information on how Systems Engineering (SE) teams are structured with respect to the various SE subdisciplines. This paper provides five possible role‐based structures to aid in filling this knowledge gap and in helping projects structure their own SE teams for success. The five structures range from a simple, single‐role structure to an advanced embedded SE with lead. The paper defines, illustrates, and presents key advantages and disadvantages for the structures. It also presents two real‐world examples to show the value of organizing or reorganizing SE teams to these structures. One focuses on large‐sized and complex waterfall project with a separate SE team restructuring for efficiency and growth opportunities and the other focuses on a medium‐sized and complex Agile project where the SE team restructures for better design definition and schedule efficiencies. Both show how a restructuring helped improve the overall quality of work, the integration with others in the project, and the overall understanding of the systems.
Mean dependency length — a new metric for requirements quality
Authors: Barbosa Leonardo de Mello , de Oliveira Igor Cardozo Amaral , Cerqueira Christopher Shneider , da Cunha Antonio Eduardo Carrilho
Published: September 2024

This paper proposes the mean dependency length (MDL) as a metric for measuring natural language requirements quality. Dependency length is a linguistic feature based on dependency grammar, which natural language researchers have traditionally used to evaluate syntactic complexity in other contexts. In this study, aided by MATLAB‐based algorithms, the authors assessed MDL over a requirements set composed of 249 original statements, rephrased into five pattern systems. Null hypothesis and effect size testings revealed that MDL is sensitive to the application of pattern rules and to the differences among the patterns, both in an absolute approach and in comparison with other metrics. Furthermore, it was also demonstrated that MDL is aligned with users' values, especially for understandability issues, and can be measured automatically. Finally, the work concluded that MDL is a convenient metric for assessing the quality of natural language requirements.
Traceability – A vision for now and tomorrow
Authors: D'Souza Adriana , Wheatcraft Louis S. , Katz Tami , Gurule A. Larry , Ryan Michael J. , Przybylo Aleksander
Published: September 2024

Traceability has been addressed in the past from the perspective of relationships between the digital artifacts within the data and the information model of the system of interest (SoI) being developed. This paper enhances this view from a project management (PM), systems engineering (SE), and a configuration management (CM) perspective. The paper discusses what traceability is today and how it can help PM and SE practitioners meet future needs to realize the INCOSE Vision 2035 and satisfy all needs and requirements baselined for a SoI, including compliance with standards and regulations. Provenance and pedigree are two aspects discussed of how traceability enhances the management of digital artifacts from a CM point of view. This paper provides a vision of how traceability can aid PM and SE practitioners to develop quality products that deliver what is needed, within cost and schedule, with the needed quality.
Model‐Based Systems Engineering (MBSE) Methodology for Integrating Autonomy into a System of Systems Using the Unified Architecture Framework
Authors: Torkjazi Mohammadreza , Raz Ali K.
Published: September 2024

Stakeholders of Systems of Systems (SoSs) are seeking new capabilities provided by autonomous systems empowered by Artificial Intelligence (AI). This requires the integration of these autonomous systems into SoSs, resulting in Systems of Autonomous Systems (SoASs). SoAS architecting is different from SoS. An autonomous system can have various Levels of Autonomy (LoA) depending on its AI algorithm. Each LoA has a different impact on the organizational and technical aspects of SoAS architecting. The organizational aspect covers concerns such as managerial and operational policies, whereas the technical aspect highlights issues such as integration compatibility between systems. Failure to address the LoA impact on these aspects in the architecting phase results in an ineffective integration. In this paper, we propose a methodology that follows the SoS hierarchical lexicon, builds upon the steps of the Object‐Oriented Systems Engineering Method (OOSEM), and leverages the Unified Architecture Framework (UAF) for modeling autonomy integration. The proposed methodology adds detailed sub‐steps to OOSEM in order to make it suitable for SoS evolution into SoAS. We also introduce the required UAF views for modeling each aspect of the SoAS architecture. This methodology lays the foundation for the trade study analysis that helps stakeholders decide on suitable LoAs for SoAS. We also present an illustrative example to demonstrate the implementation and effectiveness of the proposed methodology.
One Model to Rule them All … and Through Emergence, Bind Them
Authors: Bhalla Jawahar , Cook Stephen C. , Harvey David J.
Published: September 2024

Models are central to understanding systems and to the engineering of systems. Systems engineers employ various types of models to communicate shared understanding, through system life‐cycle models that enable the transformation of functional models to physical models, that are then realized as tangible systems of benefit to society. The recognition of the central nature of models to the engineering of systems resulted in the forming of Model Based Systems Engineering (MBSE) wherein the essence of the system of interest is contained within a system model in contrast to traditional documents. However, the evolution of model‐types employed, both to understand and to engineer systems, appears to largely have been a pragmatic activity driven by the needs of the numerous individual engineering and management subdisciplines. This paper briefly examines extant taxonomy of systems models used in the engineering of systems and in understanding operational systems and considers the question of whether there is a suitable system “meta‐model” that naturally “contains” all types of systems models used therein. It explores this question through a systems‐thinking lens, in conjunction with concepts on mental models from biology and philosophy. This analysis gives rise to framework for systems models and to the proposition that all (systems) models take on one of two forms: as reference models that aid in the engineering of systems or as representative models that aid in understanding operational systems. The paper concludes that it is possible to propose an emergent “model of systems models” that combines these two classes in an evolutionary way. This construct is offered for consideration and refinement by the systems community.
Modeling Principles to Moderate the Growth of Technical Debt in Descriptive Models
Authors: Noguchi Ryan A.
Published: September 2024

Model‐Based Systems Engineering (MBSE) is the next step in the evolution of systems engineering (SE) in which documents are replaced by descriptive models as the authoritative embodiment of SE knowledge. These descriptive models possess a unique combination of the features and characteristics of documents, software, and data. Conscientiously applying appropriate modeling principles and practices is essential to make informed decisions to moderate the accumulation of model technical debt. This paper briefly explains the concept of technical debt and its adaptation to the domain of descriptive models for MBSE. The paper then describes 18 foundational modeling principles that model architects should consider when making architectural and implementation decisions about their models and describes some of the key model technical debt tradeoffs that result when these principles are not followed. These principles address commonly observed challenges regarding model federation architecture, the selection and use of model layers, the modeling of the domain, and the semantics of modeling constructs. Applying disciplined model architecting practices to conscientiously manage the accrual and payoff of technical debt can make the difference between an enduring model that provides substantial value throughout the life cycle of the modeled entity and a model whose value collapses under the weight of uncontrolled technical debt.
A Model‐Based Systems Engineering Approach for Trucking Fleet Replacement
Authors: Bumgarner Sean , Rudder Sarah , Daily Jeremy S.
Published: September 2024

Heavy vehicles operating for less than truckload (LTL) carriers are utilized to the maximum extent possible for the operator to maximize vehicle return on investment. However, the decision to purchase new vehicles, reallocate the vehicle, or retire the vehicle is based on complex and interacting factors like performance degradation, total cost of ownership, new regulatory pressures, and maintenance costs. The problem of optimizing fleet capacity is well suited to a model‐based systems engineering approach. Using SysML as the language and MagicGrid as the method, a model for fleet vehicle replacement and utilization was built to understand the best way to maximize and grow shipping capacity. The process started with identifying stakeholders and their needs and ended with system parametric models capable of computing costs. This model has the potential to optimize operating costs for fleets and maximize the use of the vehicle assets. Not only do these optimizations improve company financial performance, they reduce the need to unnecessarily replace expensive equipment, which is a more sustainable business practice.
AI Systems Modeling Enhancer (AI‐SME): Initial Investigations into a ChatGPT‐enabled MBSE Modeling Assistant
Authors: Johns Brian , Carroll Kristina , Medina Casey , Lewark Rae , Walliser James
Published: September 2024

As artificial intelligence (AI) becomes integral across industries, there is a growing opportunity to transform the generation of models for systems engineering. This research investigates the integration of OpenAI's GPT‐4 Turbo into CATIA Magic for Model‐Based Systems Engineering (MBSE), resulting in the creation of AI Systems Modeling Enhancer (AI‐SME). This study explores the comparison between models generated by AI, specifically OpenAI's GPT, and those crafted by human systems engineers. While recognizing challenges in AI‐generated models, this research underscores the potential of AI assistants to enhance the speed and accuracy of SysML model creation. Results demonstrate AI‐SME's successes in generating requirements, block definition diagrams, and internal block diagrams. Despite identified limitations such as redundancy and lack of cohesiveness in AI‐generated models, the study concludes that AI‐SME represents a notable advancement in AI‐assisted systems engineering.
A Technical Approach to the Digital Signature of MBSE Models
Authors: Gorospe Risa , Dubicki Shannon
Published: September 2024

To fully realize the benefits of Model‐Based Systems Engineering (MBSE), users of an MBSE model need to be able to verify its authenticity and integrity. A digital signature is a common cryptographic technique that enables users to sign digital content and verify the integrity of the signed content. This enables users to verify that the signed content is truly from the author who signed the content and is a common practice in digital documentation. MBSE models have unique qualities that separate themselves from other digital documentation, thus specific digital signature approaches need to be implemented for MBSE models.

This paper describes an approach to apply digital signatures to MBSE models. The approach explores some characteristics of MBSE models and enables the digital signing of a portion of a model using a signer's digital certificate. The approach allows for the verification of the signed model content against the signature and indicates if information is altered from what the signer intended. This paper captures the technical challenges and lessons learned applying this approach as a prototype to an existing MBSE modeling tool. These findings from this paper can be used to guide the development of a digital signature capability in MBSE modeling tools.
A System Dynamics Model of Organizational Resilience
Authors: Taylor Ivan W. , Hossain Niamat Ullah Ibne
Published: September 2024

Resilience is the ability to avoid, withstand, and recover from adversity. In this paper, we examine organizational resilience using a case study of an organization that suffers from a series of scandals that lead to problems with its reputation as an inclusive organization, which results in difficulties in recruiting and retaining employees. We suggest some policies involving leadership efforts to change the culture in the organization and thereby restore its reputation. Based on the results of a System Dynamics Model that mixes quantitative and qualitative measures, we find that changing organizational culture is difficult. There can be inertia and long delays before the leadership sees results in improved recruiting and retention statistics.
Architecture of Nature‐Based Smart City Introducing BaaS by Utilizing UAF
Authors: Chen Weiwei , Iwamura Atsushi , Nishimura Hidekazu
Published: September 2024

Smart cities collaborate with various technological systems, including Internet of Things (IoT), artificial intelligence (AI), and drones, to fulfil the expectations of stakeholders and the needs of individuals and society. The use of such advanced technological systems may impose a burden on the natural environment, posing a risk to the sustainability of nature. We have already proposed the concept of biophilia as a service (BaaS) that is a service contributing to human well‐being and the sustainability of nature by emphasizing the relationship between humans and nature, promoting actions that safeguard nature, and collaborating with various organizations. In this paper, a smart, sustainable, and resilient city in harmony with nature is referred to as a nature‐based smart city (NBSC) and BaaS is introduced to NBSC. We define the architecture of NBSC introducing BaaS using the Unified Architecture Framework (UAF) and extract drivers, opportunities, and challenges of the NBSC. Requirements of BaaS for NBSC are derived from the goals and the capabilities. Also, the iterating operational processes of BaaS in the context of NBSC are described and defined. Furthermore, we discuss some findings from description of the architecture of NBSC introducing BaaS to promote the nature safeguard activity, and necessity to make a balance between human well‐being and sustainable natural environment.
Synergizing Structure and Agility: A Comprehensive Analysis of SAFe Agile Framework through the Lens of Stafford Beer's Viable System Model
Authors: Cadena Juan M. , Kenley C. Robert
Published: September 2024

This paper presents a novel examination of the SAFe® (Scaled Agile Framework®) through the theoretical framework of Stafford Beer's Viable System Model (VSM). By applying the principles of VSM, renowned for its systemic and cybernetic approach to organizational management, we offer a unique perspective on the structural and functional aspects of SAFe® in its various configurations: Essential, Large Solution, Portfolio, and Full. The study employs functional modeling to delineate the congruencies and divergences between VSM and SAFe®, aiming to illuminate how VSM's systemic insights can enhance the implementation and efficacy of SAFe® practices. This interdisciplinary approach not only contributes to a deeper understanding of SAFe's® capabilities and limitations but also demonstrates the practical applicability of VSM in contemporary agile environments. The findings propose actionable insights for organizations seeking to optimize their agile practices through a more structured, systemic lens, thus bridging a crucial gap in agile and systems thinking literature. This paper is poised to benefit practitioners and theorists alike, offering a fresh perspective in the agile systems domain.
How Systems Thinking Provides the Foundation for A W‐Shaped Model of an Effective Technical Leader
Authors: Wozniak Michael
Published: September 2024

Technical 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

The 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

Semantic 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

Implementing 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

The 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

Since 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

Systems 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

This 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

Systems 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

The 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

Among 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

Development 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

The 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.