Strategies and Best Practices for Model-based Systems Engineering Adoption in Embedded Systems Industry

[Context] Model-based Systems Engineering (MBSE) advocates the integrated use of models throughout all development phases of a system development life-cycle. It is also often suggested as a solution to cope with the challenges of engineering complex systems. However, MBSE adoption is no trivial task and companies, especially large ones, struggle to achieve it in a timely and effective way. [Goal] We aim to discover what are the best practices and strategies to implement MBSE in companies that develop embedded software systems. [Method] Using an inductive-deductive research approach, we conducted 14 semi-structured interviews with experts from 10 companies. Further, we analyzed the data and drew some conclusions which were validated by an on-line questionnaire in a triangulation fashion. [Results] Our findings are summarized in an empirically validated list of 18 best practices for MBSE adoption and through a prioritized list of the 5 most important best practices. [Conclusions] Raising engineers’ awareness regarding MBSE advantages and acquiring experience through small projects are considered the most important practices to increase the success of MBSE adoption.BMBF, 01IS15058, Verbundprojekt SPEDiT: Software Platform Embedded Systems - Dissemination und Transfe

A Quantitative SWOT-TOWS Analysis for the Adoption of Model-Based Software Engineering

Enterprises’ trend to low-code development revives model-based software engineering (MBSE) since several low-code platforms are based on the principles of model-based design, automatic code generation, and visual programming. Changes in an enterprise’s software development process, however, always require strategic planning. To find an appropriate strategy, we present an analytical tool for identifying and evaluating strengths, weaknesses, opportunities and threats factors for the adoption of MBSE. This tool provides a SWOT-TOWS analysis supplemented by a quantitative evaluation of strategies based on a multiple-criteria decision technique drawing on the knowledge of industry experts. Our analytical tool is general so it can be used in the industrial context for making other strategic decisions.Fil: Escalona, María José. Universidad de Sevilla; EspañaFil: de Koch, Nora Parcus. Universidad de Sevilla; EspañaFil: Rossi, Gustavo Héctor. Universidad Nacional de La Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Should I stay or should I go? : On forces that drive and prevent MBSE adoption in the embedded systems industry

[Context] Model-based Systems Engineering (MBSE) comprises a set of models and techniques that is often suggested as solution to cope with the challenges of engineering complex systems. Although many practitioners agree with the arguments on the potential benefits of the techniques, companies struggle with the adoption of MBSE. [Goal] In this paper, we investigate the forces that prevent or impede the adoption of MBSE in companies that develop embedded software systems. We contrast the hindering forces with issues and challenges that drive these companies towards introducing MBSE. [Method] Our results are based on 20 interviews with experts from 10 companies. Through exploratory research, we analyze the results by means of thematic coding. [Results] Forces that prevent MBSE adoption mainly relate to immature tooling, uncertainty about the return-on-investment, and fears on migrating existing data and processes. On the other hand, MBSE adoption also has strong drivers and participants have high expectations mainly with respect to managing complexity, adhering to new regulations, and reducing costs. [Conclusions] We conclude that bad experiences and frustration about MBSE adoption originate from false or too high expectations. Nevertheless, companies should not underestimate the necessary efforts for convincing employees and addressing their anxiety

Model Based Mission Assurance: NASA's Assurance Future

Model Based Systems Engineering (MBSE) is seeing increased application in planning and design of NASAs missions. This suggests the question: what will be the corresponding practice of Model Based Mission Assurance (MBMA)? Contemporaneously, NASAs Office of Safety and Mission Assurance (OSMA) is evaluating a new objectives based approach to standards to ensure that the Safety and Mission Assurance disciplines and programs are addressing the challenges of NASAs changing missions, acquisition and engineering practices, and technology. MBSE is a prominent example of a changing engineering practice. We use NASAs objectives-based strategy for Reliability and Maintainability as a means to examine how MBSE will affect assurance. We surveyed MBSE literature to look specifically for these affects, and find a variety of them discussed (some are anticipated, some are reported from applications to date). Predominantly these apply to the early stages of design, although there are also extrapolations of how MBSE practices will have benefits for testing phases. As the effort to develop MBMA continues, it will need to clearly and unambiguously establish the roles of uncertainty and risk in the system model. This will enable a variety of uncertainty-based analyses to be performed much more rapidly than ever before and has the promise to increase the integration of CRM (Continuous Risk Management) and PRA (Probabilistic Risk Analyses) even more fully into the project development life cycle. Various views and viewpoints will be required for assurance disciplines, and an over-arching viewpoint will then be able to more completely characterize the state of the project/program as well as (possibly) enabling the safety case approach for overall risk awareness and communication

INTEGRATING DEVOPS INTO NAVY COMBAT SYSTEMS DEVELOPMENT

This thesis seeks to answer three questions concerning the Navy's adoption of DevOps and its practices. Those questions are: What is DevOps in a naval context? What stands in the way of that adoption? What are some ways that the Navy can overcome those obstacles? By drawing upon both an extensive review of literature on the topic, as well as interviews with subject-matter experts, this work provides a comprehensive understanding of the breadth and complexity of the change needed in order for the Navy to adopt a culture of DevOps as well as its attendant practices. Pursuant to the same end, this thesis proposes process architectures for continuous integration, continuous testing, and continuous certification, as well as the reorganization of the Navy's combat systems development hierarchy necessary for the transition to DevOps.Lieutenant, United States NavyApproved for public release. distribution is unlimite

Industrial Adoption of Model-Based Systems Engineering: Challenges and Strategies

As design teams are becoming more globally integrated, one of the biggest challenges is to efficiently communicate across the team. The increasing complexity and multi-disciplinary nature of the products are also making it difficult to keep track of all the information generated during the design process by these global team members. System engineers have identified Model-based Systems Engineering (MBSE) as a possible solution where the emphasis is placed on the application of visual modeling methods and best practices to systems engineering (SE) activities right from the beginning of the conceptual design phases through to the end of the product lifecycle. Despite several advantages, there are multiple challenges restricting the adoption of MBSE by industry. We mainly consider the following two challenges: a) Industry perceives MBSE just as a diagramming tool and does not see too much value in MBSE; b) Industrial adopters are skeptical if the products developed using MBSE approach will be accepted by the regulatory bodies. To provide counter evidence to the former challenge, we developed a generic framework for translation from an MBSE tool (Systems Modeling Language, SysML) to an analysis tool (Agent-Based Modeling, ABM). The translation is demonstrated using a simplified air traffic management problem and provides an example of a potential quite significant value: the ability to use MBSE representations directly in an analysis setting. For the latter challenge, we are developing a reference model that uses SysML to represent a generic infusion pump and SE process for planning, developing, and obtaining regulatory approval of a medical device. This reference model demonstrates how regulatory requirements can be captured effectively through model-based representations. We will present another case study at the end where we will apply the knowledge gained from both case studies to a UAV design problem

Operation Principles of the Industrial Facility Infrastructures Using Building Information Modeling (BIM) Technology in Conjunction with Model-Based System Engineering (MBSE)

The current industrial facility market necessitates the digitization of both production and infrastructure to ensure compatibility. This digitization is presently accomplished using Building Information Modeling and digital twin technologies, as well as their integrated usage, which enhances convergence and adds further value to facility assets. However, these technologies primarily focus on the physical components of industrial facilities, neglecting processes, requirements, and functions. To address these gaps, the inclusion of the Model-Based System Engineering approach, a proven benchmark in systems engineering, is essential. This inclusion is the main objective of this research. This article outlines methods and principles for integrating Model-Based System Engineering into the informational modeling of existing industrial facilities to address current market gaps. It offers practical steps for such integration and compares it to other methods, positioning Model-Based System Engineering as a pivotal tool for enhancing the value of industrial facility digital assets. The main findings include the proposal of BIM and MBSE integration, which aims to create a competitive advantage for industrial facilities by improving customer service and operational efficiency, requiring collaboration from various stakeholders

A Framework for Reliability and Safety Analysis of Complex Space Missions

Long duration and complex mission scenarios are characteristics of NASA's human exploration of Mars, and will provide unprecedented challenges. Systems reliability and safety will become increasingly demanding and management of uncertainty will be increasingly important. NASA's current pioneering strategy recognizes and relies upon assurance of crew and asset safety. In this regard, flexibility to develop and innovate in the emergence of new design environments and methodologies, encompassing modeling of complex systems, is essential to meet the challenges

Model-Based Systems Engineering Approach to Distributed and Hybrid Simulation Systems

INCOSE defines Model-Based Systems Engineering (MBSE) as the formalized application of modeling to support system requirements, design, analysis, verification, and validation activities beginning in the conceptual design phase and continuing throughout development and later life cycle phases. One very important development is the utilization of MBSE to develop distributed and hybrid (discrete-continuous) simulation modeling systems. MBSE can help to describe the systems to be modeled and help make the right decisions and partitions to tame complexity. The ability to embrace conceptual modeling and interoperability techniques during systems specification and design presents a great advantage in distributed and hybrid simulation systems development efforts. Our research is aimed at the definition of a methodological framework that uses MBSE languages, methods and tools for the development of these simulation systems. A model-based composition approach is defined at the initial steps to identify distributed systems interoperability requirements and hybrid simulation systems characteristics. Guidelines are developed to adopt simulation interoperability standards and conceptual modeling techniques using MBSE methods and tools. Domain specific system complexity and behavior can be captured with model-based approaches during the system architecture and functional design requirements definition. MBSE can allow simulation engineers to formally model different aspects of a problem ranging from architectures to corresponding behavioral analysis, to functional decompositions and user requirements (Jobe, 2008)

A Building Information Modeling (BIM)-centric Digital Ecosystem for Smart Airport Life Cycle Management

An increasing number of new airport infrastructure construction and improvement projects are being delivered in today\u27s modern world. However, value creation is a recurring issue due to inefficiencies in managing capital expenditures (CapEx) and operating expenses (OpEx), while trying to optimize project constraints of scope, time, cost, quality, and resources. In this new era of smart infrastructure, digitalization transforms the way projects are planned and delivered. Building Information Modeling (BIM) is a key digital process technique that has become an imperative for today\u27s Architecture, Engineering, Construction and Operations (AECO) sector. This research suggests a BIM-centric digital ecosystem by detailing technical and strategic aspects of Airport BIM implementation and digital technology integration from a life cycle perspective. This research provides a novel approach for consistent and continuous use of digital information between business and functional levels of an airport by developing a digital platform solution that will enable seamless flow of information across functions. Accordingly, this study targets to achieve three objectives: 1- To provide a scalable know-how of BIM-enabled digital transformation; 2- To guide airport owners and major stakeholders towards converging information siloes for airport life cycle data management by an Airport BIM Framework; 3- To develop a BIM-based digital platform architecture towards realization of an airport digital twin for airport infrastructure life cycle management. Airport infrastructures can be considered as a System of Systems (SoS). As such, Model Based Systems Engineering (MBSE) with Systems Modeling Language (SysML) is selected as the key methodology towards designing a digital ecosystem. Applying MBSE principles leads to forming an integrating framework for managing the digital ecosystem. Furthermore, this research adopts convergent parallel mixed methods to collect and analyze multiple forms of data. Data collection tools include extensive literature and industry review; an online questionnaire; semi-structured interviews with airport owner parties; focus group discussions; first-hand observations; and document reviews. Data analysis stage includes multiple explanatory case study analyses, thematic analysis, project mapping, percent coverage analysis for coded themes to achieve Objective 1; thematic analysis, cluster analysis, framework analysis, and non-parametric statistical analysis for Objective 2; and qualitative content analysis, non-parametric statistical analysis to accomplish Objective 3. This research presents a novel roadmap toward facilitation of smart airports with alignment and integration of disruptive technologies with business and operational aspects of airports. Multiple comprehensive case study analyses on international large-hub airports and triangulation of organization-level and project-level results systematically generate scalable technical and strategic guidelines for BIM implementation. The proposed platform architecture will incentivize major stakeholders for value-creation, data sharing, and control throughout a project life cycle. Introducing scalability and minimizing complexity for end-users through a digital platform approach will lead to a more connected environment. Consequently, a digital ecosystem enables sophisticated interaction between people, places, and assets. Model-driven approach provides an effective strategy for enhanced decision-making that helps optimization of project resources and allows fast adaptation to emerging business and operational demands. Accordingly, airport sustainability measures -economic vitality, operational efficiency, natural resources, and social responsibility- will improve due to higher levels of efficiency in CapEx and OpEx. Changes in business models for large capital investments and introducing sustainability to supply chains are among the anticipated broader impacts of this study