Systems Engineering Tools Research Articles

Human‐centered Smart Cities: An evaluation of a small community using the Smart Cities Initiative framework

AbstractIn September 2023, the INCOSE Smart Cities Initiative released a framework to evaluate and define smart city systems. The framework includes a human‐centered definition of a smart city and offers metrics of a smart city. The definition, metrics, and framework are based on a systematic process that allows consistent evaluation of city that focuses on providing for fundamental human needs.Many smart city applications still focus on technology, regardless of whether that technology provides a clear benefit to the stakeholders of the city. Systems engineering tools and practices offer potential for improving smart city implementations by improving the alignment of needs and solutions. Unfortunately, in new domains, such as the plethora domains involved with smart cities, systems engineering can be viewed as unnecessary overhead. Therefore, the usefulness of the systems engineering concepts that underlie the INCOSE Smart Cities framework could be overlooked unless it can provide immediate value. As a demonstration of how the new framework could be used by someone interested in engaging INCOSE Smart Cities concepts, a high‐level application of the definitions and framework was performed.The analysis demonstrated that a simple review of the city system, using the perspectives of the INCOSE Smart Cities initiative, could reveal strengths and weaknesses of a smart city and identify potential next steps for improvement. This paper is a case study of how to use qualitative analysis to apply the human‐centered definition and framework to evaluate a Smart City. The case study provides an opportunity to evaluate the strengths and weaknesses of the new INCOSE framework.

MBSE Analysis & Update of U.S. Infrastructure Data Taxonomy (IDT) Using U.S. National Critical Functions (NCFs)

AbstractIn this paper, we will demonstrate the application of Model‐Based Systems Engineering (MBSE) tools and techniques we have used to assist the U.S. Department of Homeland Security (DHS) / Cybersecurity Infrastructure Security Agency (CISA) in analysis of open‐source Infrastructure Data Taxonomy (IDT) data to analyze and contribute to the updates required for their IDT. We will show how we have used Functional Analysis, Logical Structure Taxonomies, and MBSE tools to analyze the IDT alongside the DHS National Critical Functions (NCFs) to recommend and improve these updates for their IDT. We have also proposed updates to the NCFs themselves where obvious improvements could be made. Our future recommendations are to continue this effort as a team of INCOSE Critical Infrastructure Protection and Recovery (CIPR) team members, along with other INCOSE Working Groups (WGs), and to explore other use cases based on this model data, as well as inviting other Subject Matter Experts (SMEs) to assist in the enhancements. This modeling effort demonstrated the use of these MBSE tools while working together with other organizations to enable improvements to the Critical Infrastructure (CI) space leveraging systems theory & thought leadership. We will outline further avenues for exploration using this provided MBSE capability in multiple areas that could be useful to the DHS, and will discuss a potential longer‐term engagement with DHS in an annual challenge. This challenge similar to those led by multiple other projects will include collaborations with universities and other CI / CIPR entities interested in this modeling of the CI space. Other opportunities to extend the model further include, but are not limited to security / cybersecurity, operational, and services modeling use cases, involving Industrial Control Systems (ICS) and much more. We have shown how these tools are effective and efficient for use in the water / wastewater sector, but will also yield similar benefits when applied across all identified sectors and across the international community as well (i.e., transportation, telecommunications, etc.). Interestingly we have seen in our initial analyses that the various taxonomies across sectors, subsectors, segments, subsegments, and assets vary slightly between regions and countries internationally for various reasons.

Model-based systems engineering examination of failures ontology in aircraft turbine blades

The concept of Systems Engineering (SE) is widely used in modern times, with approaches based on analyzing the levels and processes of a system. SE approaches are elaborate based on the interpretation of the system's levels and analyzing the whole process. Although such methods are usually used in the analysis of organizations or enormous systems, this effort attempts to show that the same SE analytical tools can be useable in the deepest level of a system. The study focuses on investigating the failure process of a turbine blade, which is considered a system component. The first essential issue in analyzing a system is its interactions with the environment and its effects on the system's internal cybernetics. The study identifies failure processes that cause structural damage as well-defined and tangible processes of microsystem interactions. The research provides a comprehensive architecture of possible failures in an aircraft's jet engine's hot section turbine blades, utilizing a systemic approach and SE tools such as SysML-based models and Domain Mapping Matrices (DMM) to allocate causes of these failures. This research aims to propose an allocated SE-oriented architecture of Failure-Causes in jet engine turbine blades that is more suitable for use in programming.

Using the ARCADIA/Capella Systems Engineering Method and Tool to Design Manufacturing Systems—Case Study and Industrial Feedback

In a trend towards digital continuity, model-based systems engineering is becoming widely adopted for the design of complex systems, supporting system development from the very first stages. A narrow panel of methods and tools are available on the market; they offer different scopes and approaches, are more or less intuitive to follow, and are sometimes supported by tools. Among them, the Architecture Analysis & Design Integrated Approach (ARCADIA) is becoming popular and is gradually spreading in different industrial fields to model a wide variety of systems at different stages of their development and from different points of view. It is implemented using an open-source tool called Capella. Few feedback on its use in industrial settings have been published, while other feedback remains confidential. The goal of this paper is to analyze the interests and limitations of ARCADIA/Capella. To reach this goal, we experimented with ARCADIA/Capella in several projects and chose one to explain how the method and tool proceeded. In addition, we conducted a survey to obtain industrial feedback. As a result, the paper gives an overview of the relevance of ARCADIA/Capella in projects and of its usefulness, effectiveness, and adaptability in modeling different types of systems. It also provides some perspectives for the evolution of the method and the tool according to industrial feedback.

Considerations on Deploying Systems Engineering to Accelerate the R&D of New Nuclear Fuels

A project for the research and development (R&D) of new nuclear fuels is a system with the following characteristics: having large number of stakeholders, progressing through a set of life cycle stages, validated by advanced measures of effectiveness, integrating multiple disciplines and specialty groups, and facilitated by enabling systems, thus can be effectively managed with the approach of systems engineering (SE). In this paper, the deployment of SE in global nuclear industry including Russia, the U.S., France, Korea and China is reviewed. By learning the experience of SE deployment in global nuclear industry, the SE characteristics of projects for the R&D of new nuclear fuels are analysed based on systems science. The R&D projects of medical cobalt adjuster rod assemblies and mobile nuclear reactor in China North Nuclear Fuel Co., Ltd. (CNNFC) are discussed as SE practices. It is proposed that in order to accelerate the R&D of new nuclear fuels in nuclear fuel manufacturing plant, SE should be enhanced in the following aspects: adhering to systems science, making good use of SE engineers, introducing SE tools, and exploring SE characteristics.

Model-driven development for the seL4 microkernel using the HAMR framework

Verified microkernels such as seL4 provide trustworthy foundations for safety- and security-critical systems. However, their full potential remains unrealized due, in part, to the lack of application development environments that help engineers integrate the microkernel’s configuration and hosting of application code with modeling, analysis, and verification tools that address broader aspects of the development lifecycle.This paper presents a model-driven tool chain for the seL4 microkernel based on the open source High Assurance Modeling and Rapid engineering (HAMR) code generation framework for the Architecture and Analysis Definition Language (AADL). We describe how the semantics of AADL communication and threading can be realized in terms of the access primitives and strong spatial and temporal partitioning mechanisms provided by seL4. For AADL users, seL4 provides a high-assurance platform with formally verified enforcement of component boundaries and communication pathways. For seL4 users, AADL provides high-level abstractions for developing seL4 applications, along with an ecosystem of system engineering and analysis tools. We illustrate the framework by applying a model-based development environment for increasing resiliency against cyber attacks to an unmanned aircraft flight control system.

A Review of Process Systems Engineering (PSE) Tools for the Design of Ionic Liquids and Integrated Biorefineries

Over the years, the global process industry is continually improving in product development and process performances [...]

BOARD-AI: A goal-aware modeling interface for systems engineering, combining machine learning and plan recognition

Paper and pens remain the most commonly used tools by systems engineers to capture system models. They improve productivity and foster collaboration and creativity as the users do not need to conform to formal notations commonly present in Computer-Aided Systems Engineering (CASE) tools for system modeling. However, digitizing models sketched on a whiteboard into CASE tools remains a difficult and error-prone activity that requires the knowledge of tool experts. Over the past decade, switching from symbolic reasoning to machine learning has been the natural choice in many domains to improve the performance of software applications. The field of natural sketching and online recognition is no exception to the rule and most of the existing sketch recognizers rely on pre-trained sets of symbols to increase the confidence in the outcome of the recognizers. However, that performance improvement comes at the cost of trust. The lack of trust directly stems from the lack of explainability of the outcomes of the neural networks, which hinders its acceptance by systems engineering teams. A solution shall not only combine the performance and robustness but shall also earn unreserved support and trust from human users. While most of the works in the literature tip the scale in favor of performance, there is a need to better include studies on human perception into the equation to restore balance. This study presents an approach and a Human-machine interface for natural sketching that allows engineers to capture system models using interactive whiteboards. The approach combines techniques from symbolic AI and machine learning to improve performance while not compromising explainability. The key concept of the approach is to use a trained neural network to separate, upstream from the global recognition process, handwritten text from geometrical symbols, and to use the suitable technique (OCR or automated planning) to recognize text and symbols individually. Key advantages of the approach are that it does not resort to any other interaction modalities (e.g., virtual keyboards) to annotate model elements with textual properties and that the explainability of the outcomes of the modeling assistant is preserved. A user experiment validates the usability of the interface.

Carbon dioxide utilization: A critical review from multiscale perspective

AbstractCarbon dioxide (CO2) emissions contribute considerably towards increasing greenhouse effect. Carbon capture and storage can reduce CO2 emissions to a great extent but lacks economic feasibility. The economic feasibility of CO2 capture could be boosted by utilizing the captured gas to produce valuable end products. CO2 is a highly stable molecule; therefore, special catalysts and elevated conditions of temperature and pressure are required for its conversion. This review presents the current status of CO2 utilization processes from various aspects, including thermodynamic, economic, and environmental impacts. The use of process systems engineering (PSE) tools and techniques in a broad spectrum, to improve the technical, economic, and environmental feasibility of these processes, is the major focus of this review. In this regard, a framework has also been presented showing the integration of various PSE techniques. All the related information in the form of tabulated data as well as qualitative and quantitative plots have been presented and critically analyzed.

Systems analysis and improvement approach to optimize outpatient mental health treatment cascades in Mozambique (SAIA-MH): study protocol for a cluster randomized trial

BackgroundSignificant investments are being made to close the mental health (MH) treatment gap, which often exceeds 90% in many low- and middle-income countries (LMICs). However, limited attention has been paid to patient quality of care in nascent and evolving LMIC MH systems. In system assessments across sub-Saharan Africa, MH loss-to-follow-up often exceeds 50% and sub-optimal medication adherence often exceeds 60%. This study aims to fill a gap of evidence-based implementation strategies targeting the optimization of MH treatment cascades in LMICs by testing a low-cost multicomponent implementation strategy integrated into routine government MH care in Mozambique.MethodsUsing a cluster-randomized trial design, 16 clinics (8 intervention and 8 control) providing primary MH care will be randomized to the Systems Analysis and Improvement Approach for Mental Health (SAIA-MH) or an attentional placebo control. SAIA-MH is a multicomponent implementation strategy blending external facilitation, clinical consultation, and provider team meetings with system-engineering tools in an overall continuous quality improvement framework. Following a 6-month baseline period, intervention facilities will implement the SAIA-MH strategy for a 2-year intensive implementation period, followed by a 1-year sustainment phase. Primary outcomes will be the proportion of all patients diagnosed with a MH condition and receiving pharmaceutical-based treatment who achieve functional improvement, adherence to medication, and retention in MH care. The Consolidated Framework for Implementation Research (CFIR) will be used to assess determinants of implementation success. Specific Aim 1b will include the evaluation of mechanisms of the SAIA-MH strategy using longitudinal structural equation modeling as well as specific aim 2 estimating cost and cost-effectiveness of scaling-up SAIA-MH in Mozambique to provincial and national levels.DiscussionThis study is innovative in being the first, to our knowledge, to test a multicomponent implementation strategy for MH care cascade optimization in LMICs. By design, SAIA-MH is a low-cost strategy to generate contextually relevant solutions to barriers to effective primary MH care, and thus focuses on system improvements that can be sustained over the long term. Since SAIA-MH is integrated into routine government MH service delivery, this pragmatic trial has the potential to inform potential SAIA-MH scale-up in Mozambique and other similar LMICs.Trial registrationClinicalTrials.gov; NCT05103033; 11/2/2021.

A Stochastic Network Approach to Modelling Ship Evacuation

This paper presents a development of a novel, efficient, and robust tool to conduct evacuation from maritime ships using multi-commodity network theory and graph search techniques. MSC/1533 (IMO, 2016) presents guidelines to conduct simplified/quasi-advanced analysis methods for the evacuation analysis of ships. The IMO techniques describe a prescriptive approach and don’t consider path variabilities or uncertainties associated with the dynamic nature of the evacuation environment. To enhance the work presented by the IMO, a linear programming multi-commodity graphing solution has been developed and implemented in Excel. This model is based on network and graph theory and specifies basic passenger characteristics, simulates ships geometry and specifies path constraints. The simulation determines the shortest route to the nearest safe point/muster station. Monte Carlo is used to characterise model uncertainties in the simulation. Initial experiments indicate this technique is feasible. As a Systems Engineering tool, it can be used in trade-off studies to finalise ship layout design and identify path delay/choke points and can be used to rank evacuation performance of existing ship configurations.

Optimal HEV cooling system design through a computer-aided virtual development chain

To reduce CO2 and pollutant emissions, automotive manufacturers tend to turn increasingly toward electrified powertrains solutions, such as Hybrid Vehicles (HEV). Model Based System Engineering (MBSE) and computational tools are useful to support the development of HEV systems. System architectures need to be investigated to find optimal solutions regarding multiple possible goals constraints (fuel consumption, CO2 emissions, etc.). In this study, a novel global optimization framework is proposed to enable an automated cooling system optimization. The methodology starts with a set of components, design rules, and system requirements to search and automatically generate all the admissible cooling system architectures. System architectures are generated by a concept of decision tree. The decision tree algorithm is coupled to a design rules database to avoid exploring solutions that do not satisfy system requirements. Hydraulic models are automatically built for each system architecture generated to optimize head losses and minimize the pump consumption. For the most interesting solutions, 3D piping geometrical data (lengths, angles, and curve radius) are automatically drawn by a 3D optimization tool. Piping geometrical data are integrated in GT-SUITE thermo-hydraulic simulation models automatically built to evaluate the most interesting cooling system architectures generated. The best candidates are identified by a multi-criteria decision-making strategy. A first case of conventional vehicle cooling system is studied. Results on the given example indicate that the difference of energy consumption on WLTC cycle between the best performing architecture and the worst one is 69%.

Use of Model-Based System Engineering methodology and tools for disruption analysis of supply chains: A case in semiconductor manufacturing

In the age of complex and large-scale systems, Model-Based System Engineering (MBSE) is increasingly becoming a sine qua non in industry due in large part to a wider use of software applications and an increased move towards standardization. In this study, we research the application of the MBSE methodology (definition, design, analysis, and synthesis) to disruption management with a specific focus on a semiconductor supply chain case study. Within this methodology we use three MBSE tools, namely OWL, BPMN, and SysML, with the main focus being on definition of the problem to ensure that the “correct” problem is solved. The article does not report on any new research into the MBSE tools, but applies the available tools. Many of these tools have limitations, especially in the area of analysis and synthesis, that have been overcome if not widely adopted, in the area of product design (i.e., finite element analysis and simulation, etc.), which is a limitation in the type of systems studied here, i.e., a supply chain system which is a discrete event system. Through the application of the MBSE methodology and the application of the three MBSE tools, a comparison is provided that highlights further opportunities and obstacles, but which ultimately demonstrates a positive proof that the MBSE methodology is necessary for revealing sources of systematic disruptions within a complex integrated industrial information system.

Requirements Management Tools for Software Systems: A Systematic Tools Review

This article contains a systematic review of Requirements Management tools (RM tools) for Software Systems. A research question was defined as the following: requirements development process of large-scale software system (with thousands of requirements) and an interaction problem during this process (communication, coordination and control). The problem is caused by the fact that the requirements development process is a cross-disciplinary task and it involves multiple parties — stakeholders, domain experts, and suppliers with own goals and constraints, and thus, the interaction between them seriously slows down the overall requirements development process more than writing the requirements specification itself. The tools were classified into the following classes: Requirements Management Tools, ALM/PLM/SDLC Tools, Model-based System Engineering tools with Requirements support, Natural Language based tools for Requirements Engineering, WYSIWYG-prototyping and Requirements platform, Open Source tools, and tools developed by Russian vendors. Each tool class was described and represented with list of relevant tools — including feature-rich solutions, and a description of key features. A contribution of functionality from each tool into the research question was analyzed and summarized including potential further improvement steps. Advantages and disadvantages of the existing RM tools were represented in this work. To approach the research question, further potential directions were described.

Design of an IoT System for the Palletized Distribution Supply Chain with Model-Based Systems Engineering Tools

In recent years, Internet-of-Things technology (IoT) has been the subject of research in diverse fields of applications. IoT plays an essential role in transitioning enterprises towards a more interconnected paradigm of manufacturing, logistics, services, and business, known as Industry 4.0. This paper presents an operational concept for a system that implements IoT technology in pallets, which are used to move products along supply chains. These sensors will help us gain insight into the conditions experienced by products and unit loads. Having this capability will allow us to obtain the information necessary for better control of product distribution along the supply chain, and to design packaging that is more efficient and effective in protecting products during distribution. In this paper, we show how Model-Based Systems Engineering (MBSE) can be leveraged to create models that capture the required system behaviors, and we address the complexity of an IoT system within the domain of packaging and logistics applications.

System Analysis of Counter-Unmanned Aerial Systems Kill Chain in an Operational Environment

The proliferation of Unmanned Aerial System (UAS) capabilities in the commercial sector is posing potentially significant threats to the traditional perimeter defense of civilian and military facilities. Commercial Off-The-Shelf (COTS) UAS are small, cheap, and come with multiple types of functions which have growing interest among hobbyists. This has prompted the need for facility commanders to have a methodology to conduct quick evaluation and analysis of the facility and the existing Counter-Unmanned Aerial System (CUAS)’s effectiveness. This research proposes a methodology that follows a systems engineering perspective to provide a step-by-step process in conducting evaluation and analysis by employing Model-Based Systems Engineering (MBSE) tools to understand the CUAS’s effectiveness and limitations. The methodology analyzes the CUAS’s operating environment and effects of the dominant factors and impacts that CUAS may pose to other stakeholders (e.g., adjacent allied forces, civilians, etc.) within the area of operation. We then identify configuration candidates for optimizing the CUAS’s performance to meet the requirements of the stakeholders. A case study of a hypothetical airport with existing CUAS is presented to demonstrate the usability of the methodology, explore the candidates, and justify the implementation of a candidate that fits the facility and the stakeholders’ requirements.

Model based systems engineering—A text mining based structured comprehensive overview

AbstractAn observed increase in systems scale and complexity has led to a significant momentum in exploring, identifying, and adopting model based systems engineering (MBSE) tools and techniques amongst research communities and industry practitioners. Several attempts to transform systems design and engineering practices through the use of MBSE in academia and industry has led to a considerable increase in the number of articles published containing the keyword “MBSE.” This growth serves as the motivation in this paper to explore the MBSE landscape with the help of text mining techniques to identify the most often used key terms, tools, and languages, in the context of research in MBSE and the thematic aspects defining the use of MBSE by researchers and practitioners. The objective of this paper is to provide a structured comprehensive overview of research contributions across the MBSE landscape by employing text mining techniques for: (a) identifying the concepts and methodologies inferred upon in relation to MBSE, and (b) classifying the literature published to identify commonalities across academic researchers and practitioners using MBSE tools and methods. For this purpose, the abstracts of 2380 relevant articles published in the period of the last two decades from five different databases are mined. It is found that the terms “SysML,” “Cyber Physical Systems,” and “Production” are the most used terms among researchers across the MBSE landscape with SysML being the most widely used modeling language. Further, six major thematic topics are identified that classify articles from over the last two decades with an increasing interest observed in the use of MBSE to support manufacturing and production engineering activities, especially in the cyber physical systems domain. The contributions of this paper provide a leeway on using text mining techniques to understand the research directions that are currently of interest in the field of MBSE and thereby identify potential future research directions.

OPTIMIZATION OF CONSTRUCTION PRODUCTION DUE TO SYSTEM-TECHNICAL AND LOGISTIC APPROACHES

Goal. Study of methodological and practical aspects of the development and functioning of the construction industry using the platform of logistics and systems engineering tools as a modern basis for solving organizational and technological problems, taking into account the transformation of market conditions in the construction sector. Methodology. Construction plays an important role in the complex economic system of Ukraine. The current state of construction requires significant changes and reforms, which are able to activate the development of one of the most significant sectors of the country. The way out of the difficult situation is the use of modern approaches on the platform of logistics tools and systems engineering, this will lead to an improvement in the organization of construction production, due to effective management of material flows, and will make it possible to reduce the production cost of construction and installation works, and timely commissioning of facilities. Results. This work reflects the scientifically substantiated results of the introduction of logistics and systems engineering as modern innovative platforms for solving organizational and technological problems of increasing the efficiency of the construction sector. The management of the triad of construction processes (organization, technology, economics) is determined, taking into account the logistic and systems-technical approaches. Scientific novelty. A theoretical and methodological direction has been formed, on the basis of a modern tool of Logistics and Systems Engineering, for solving organizational and technological problems of construction production, taking into account the effective management of material flows, which allows to reduce the production cost of construction and installation works and timely commissioning of facilities. The presented model reflects the unity of the entire intersystem cycle: raw materials – transport – production – distribution – demand – floating prices. Practical significance. The use of modern approaches on the platform of logistics and systems engineering tools, which makes it possible to form a mechanism for choosing rational management approaches aimed at solving organizational and technological problems of construction production taking into account the transformation of market conditions. The model has proven its high efficiency, removed all difficulties in the practical implementation of the tasks of organizational and technical development of construction production, the method can be used to solve similar problems in other regions of Ukraine.

Analyzing Standard Operating Procedures Using Model‐Based Systems Engineering Diagrams

AbstractStandard Operating Procedures (SOPs) are critical for the safe operations of complex, hazard‐sensitive systems. The SOPs are particularity important for dealing with non‐normal operations in which the human operator must intervene and/or provide instructions to the automation. Under these rare circumstances, the appropriate human operator actions are defined by SOPs. The SOPs must be completed within an Allowable Operational Time Window (AOTW) to avert a hazardous outcome. In many cases, the AOTW is not fixed, but exhibits variance due to complex non‐linear, plant dynamics. The Time on Procedure (ToP) is also subject to variability due to human factors such as experience, proficiency, fatigue, and the efficacy of the SOPs and the supporting automation user‐interface. For this reason, it is critical to evaluate the dynamic performance of the SOP in the context of the operations and determine the likelihood of the ToP exceeding the AOTW.This paper describes how to model SOPs and perform SOP analysis using LML/SysML Action/Activity Diagrams that can be found in most Model‐based System Engineering (MBSE) tools. The method enables the SOP designer to assess the performance of the SOP by accounting for human factors and operation dynamics. The ability to test the procedures in a MBSE tool can inform the system design and verify the procedure design early in the development life‐cycle. The implications and limitations of this approach are discussed.

MBSE Enabled Trade‐Off Analyses

AbstractThis paper examines the potential to use Model‐Based Systems Engineering (MBSE) tools to perform trade‐off analysis of alternative systems decisions in the system life cycle from the concept stage to the retirement stage. Specially, we searched for integrated models that automate the simultaneous evaluation of the performance, effectiveness, stakeholder value, and cost of multiple alternative system designs. We used the Web of Science to perform a literature search to identify published papers that describe the use of MBSE tools to support automated analysis of alternatives and trade‐off analyses. We found very few papers that claimed to use MBSE to provide analysis of design alternatives or tradespace exploration. Based on the literature search insights, we identify and describe the required and desired capabilities to perform automated trade‐off analyses of performance, effectiveness, stakeholder value, and cost for multiple system design alternatives using integrated models.