Design: Structure, Process, and Function: A Systems Methodology Perspective

Systems engineering management in the FRG

Contributors

Formalization of bond graph using higher-order-logic theorem proving

Industrie 4.0, also called Industry 4.0, represents the current trend of manufacturing industry characterized by high level of automation, industrial integration, and industrial information integration. It mainly includes enabling technologies such as the Internet of Things (IoT), cyber‐physical systems (CPS), cloud computing, industrial integration, industrial information integration, and other technologies. Systems science has been emerged and well developed since the second half of the twentieth century. From 1940s until now, systems science has been called systems science, systems engineering, systems theory, cybernetics, systems analysis, systems methodology, systems approach, and systems thinking. Since its emergence, a wealth of research has produced an astonishing array of theoretical results and empirical insights, and a large suite of methods and techniques. Systems science has been continuously, widely, and successfully applied to many subjects in natural science and social sciences. This paper aims at discussing the potential contribution of systems science to Industry 4.0. As we approach the era of Fourth Industrial Revolution, this paper points out that systems science is a necessity to deal with the overwhelming systems complexity in Industry 4.0 and the surrounding industrial ecosystem.

The Rockwell International-Collins Avionics Divisions are developing an avionics systems engineering graduate program with Iowa State University. The author discusses the proposed curriculum and the four avionics systems engineering courses that will be offered. The four courses are: Systems Engineering and Analysis, Avionics Systems Engineering, System Project Management, and Software Systems Engineering. The Systems Engineering and Analysis course introduces system engineering concepts and principles. The second course applies the system engineering techniques presented in the first course to avionics. Current avionics functions are presented and then used to discuss avionics systems. The third course discusses avionics systems engineering from the project management viewpoint. The Software Systems Engineering course examines the systems aspect of software. >

Integrating Core Systems Engineering Design Concepts into Traditional Engineering DisciplinesIn this study we describe the integration of core systems engineering design concepts intotraditional mechanical and electrical engineering curriculum at the University of Arkansas atLittle Rock (UALR) undergraduate Systems Engineering program. The program was launched in1999 in response to the industry demands for engineering graduates capable of managingcomplex engineering projects. The program has since graduated over 150 students who areworking in industry (aerospace, defense, manufacturing, design, and consulting), federal andstate government, or attending graduate school. The program curriculum has four broadcomponents: a 35 hour university core that covers basic math and science (11 hours) and generaleducation (24 hours); a 30 hour college core that enhances the math and science preparation witha course in engineering ethics; a 32 systems engineering component that introduces core systemsengineering concepts; and, a 32 hour option component that teaches the mechanical or electricalengineering disciplines. The program is accredited by ABET under general criteria, and plans areunderway to satisfy mechanical and electrical engineering program criteria. Students entering theprogram are introduced to systems engineering core concepts through courses in EngineeringEconomy, DES Modeling and Simulation, Optimization Methods, Decision and Risk Analysis,and Systems Engineering Design and Analysis. Among them, Engineering Economy coversengineering project evaluation and economic decision making. Optimization Methods in SystemsEngineering covers linear and nonlinear methods of engineering design optimization. DESModeling and Simulation covers theory and practice of discrete event simulation modeling.Decision and Risk Analysis covers uncertainty modeling and analytical techniques for rationaldecision making. Systems Engineering Design and Analysis covers the systems engineering life-cycle process, including identification of system requirements, engineering design andarchitecture, system modeling, testing and integration, and system operation and support. The128-hr program culminates in a two-semester Systems Engineering Capstone Design thatemphasizes the multi-disciplinary nature of the program. The students perform functional designin the first semester followed by detailed physical design and testing in the second semester. TheUALR program graduates skilled systems engineers who combine holistic thinking with deepproduct knowledge, strong technical background, effective communication skills, and goodinterpersonal skills.

There are many ways in which we can describe systems engineering. It can be described according to structure, function, and purpose. It may be described in terms of efforts needed at the level of systems management, systems methodology, and systems engineering methods and tools. We can speak of systems engineering organizations in terms of their organizational management facets, in terms of their business processes or product lines, or in terms of their products or service. We can speak of systems engineering in terms of the knowledge principles, knowledge practices, and knowledge perspectives necessary for present and future success in systems engineering. This paper takes a multifaceted view of systems engineering. It attempts to describe systems engineering in terms of this relatively large number of trilogies. The process view of systems engineering is expanded on in some detail. Within this, a large number of necessary roles for systems engineering are described. We present a brief discussion of systems engineering from the perspective of each of these necessary roles as it applies to the systems engineering of computer based systems, including some 21st century projections.

The Aircraft Data Hierarchy (ADH) represents a transformative Model-based Systems Analysis & Engineering (MBSA&E) data storage format for standardized aerospace data exchange, specifically designed to address critical challenges in the aerospace industry's digital transformation of its multidisciplinary design processes. This technical document outlines the development, structure, and prototype Python implementation of an open-source ADH as a solution that integrates systems analysis with systems engineering using a recursive Model-Based Systems-of-Systems Architecture (MSoSA) structure aligned with established standards. The ADH facilitates efficient exchange of critical information—geometry definitions, disciplinary tool inputs/outputs, and engineering requirements—through a centralized, validated data structure implemented using Pydantic v2, with support for serialization in JSON, YAML, and XML formats. The initial ADH architecture was designed by Boeing with support from NASA, GE Aerospace, Collins Aerospace, and the University of Michigan to gather a wide and varied set of requirements. This paper details the ADH's high-level architecture, including an example integration with NASA’s MBSA&E framework, its hierarchical organization of aerospace data, and its adaptability to accommodate diverse aircraft configurations. The use of a centralized authoritative data source like the ADH reduces data duplication, enhances cross-disciplinary and cross-organizational collaboration, improves traceability, and supports digital thread continuity. This ultimately enables more efficient and innovative aircraft design processes. The ADH is poised to become a fundamental component of future aircraft design systems. However, continued investment and industry involvement through AIAA and other avenues are needed to realize the full transformative potential of the ADH.

Moving systems engineering's center of gravity from text documents to digital models, model‐based system engineering (MBSE) facilitates collaboration, reduces errors, and improves system understanding, but systems engineers often face challenges when they start working with MBSE, as they need to consider and model textual requirements as a basis for the system architecture. Synchronizing requirements with the system model can address critical questions, such as which requirements are assigned and covered in the system model, what effort is required to meet these requirements, how to manage changes to requirements, and how to effectively trace them in the system. Object Process Methodology (OPM, ISO 19450) is an MBSE language and methodology for modeling systems, which encapsulates function, structure, and behavior within a single model. The research goal is to expand the MBSE methodology by modeling requirements that are linked to system model artifacts. The objective is minimizing misunderstandings between stakeholders’ text‐based requirements and the engineered model while improving the ability to track changes in requirements and artifacts. An OPM‐based model, OPM‐R, which unifies system requirements and architecture, was developed and evaluated through (1) interviews with seven experts who compared the current text‐based approach and the proposed one based on the requirements of three test system models and (2) a researcher diary. Findings indicate that OPM‐R is preferred over the text‐based approach, as it reduces misunderstandings and gaps in requirements, enhancing the ability to trace coverage of system artifacts and track changes in requirements.

Systems engineering is a transdisciplinary scientific and applied direction that combines the principles of a systems approach, methods, tools and standards that provide an integrated methodology and relevant technologies for the design and development of complex systems, their comprehensive analysis and verification, efficient and safe use. The modern approach to systems engineering is characterized by an accentuated modeling of systems throughout their life cycle with the ultimate goal of creating their digital twins. It is called model-based systems engineering (MBSE). Consistent integration of MBSE with software engineering leads to the formation of the MBSSE (Model-Based Systems and Software Engineering) direction. This textbook is devoted to this area, the main objective of which is to study the conceptual and scientific-methodological foundations of MBSE and MBSSE, models and methods of life cycle management of systems and software, basic standards of systems engineering, study and mastery of the UML and SysML systems modeling languages and the corresponding modeling tools, study of requirements engineering methods and development of a description of the system architecture, familiarization with the concept of digital twins and their role in MBSE, study of the MBSSE reference model and its relationship with the process standards of systems engineering, study of the methodological aspects of the system and software integration process. The final chapter of the textbook is devoted to the study of the mathematical foundations of systems engineering. The main aspects of the mathematical theory of systems by A. Wayne Wymore, which became an important stimulus for the development of the model-oriented approach in systems engineering, and modern research, including the apparatus of finite automata by David Harel, the formalism of modeling of discrete systems DEVS, research into category theory as a formal mathematical basis for model-based system design are considered. The authors recommend this course as a basic course for training IT professionals.

This article explores the potentials of systems analysis and design of information system for sustainable natural resource management. Soft and hard system analyses were performed to better understand the information needs and design of an information system for improving decision making for achieving sustainable natural resource management. In order to analyze the complex and soft systems situations for developing an effective information system, which meets related actors’ changing needs, a conceptual model inspired by soft systems methodology (SSM) was developed. This model is based on information derived from twelve farmers who were purposely selected to represent diverse conditions and 23 agricultural extension experts across the Alborz Watershed in Mazandaran Province, located in northern Iran. Since a conceptual model resulting from SSM is not in itself sufficient as the basis for the implementation of information systems, a hard system methodology was used to structure the data handling by using unified modeling language. This research has shown the promising potentiality of using soft system analysis methodology as a preliminary step to the actual design of an information system in the natural resource management situation in the watershed system level when combined with hard system analysis methods.

In FY 2004, JPL launched an initiative to improve the way it practices systems engineering. The Lab's senior management formed the systems engineering advancement (SEA) project in order to significantly advance the practice and organizational capabilities of systems engineering at JPL on flight projects and ground support tasks. The scope of the SEA project includes the systems engineering work performed in all three dimensions of a program, project, or task: 1) the full life-cycle, i.e., concept through end of operations; 2) the full depth, i.e., program, project, system, subsystem, element (SE Levels 1 to 5); 3) the full technical scope, e.g., the flight, ground and launch systems, avionics, power, propulsion, telecommunications, thermal, etc. The initial focus of their efforts defined the following basic systems engineering functions at JPL: systems architecture, requirements management, interface definition, technical resource management, system design and analysis, system verification and validation, risk management, technical peer reviews, design process management and systems engineering task management. They also developed a list of highly valued personal behaviors of systems engineers, and are working to inculcate those behaviors into members of their systems engineering community. The SEA project is developing products, services, and training to support managers and practitioners throughout the entire system life-cycle. As these are developed, each one needs to be systematically deployed. Hence, the SEA project developed a deployment process that includes four aspects: infrastructure and operations, communication and outreach, education and training, and consulting support. In addition, the SEA project has taken a proactive approach to organizational change management and customer relationship management - both concepts and approaches not usually invoked in an engineering environment. This paper describes JPL's approach to advancing the practice of systems engineering at the Lab. It describes the general approach used and how they addressed the three key aspects of change: people, process and technology. It highlights a list of highly valued personal behaviors of systems engineers, discusses the various products, services and training that were developed, describes the deployment approach used, and concludes with several lessons learned.

PurposeThis paper aims to examine the differences in epistemological underpinnings of conventional information systems analysis and design (ISAD) approaches (such as structured system and analysis design methodologies) and a recently developed situated ISAD approach.Design/methodology/approachThis empirical investigation involved constructing a simulated field situation to allow a conventionally trained IS analyst to analyse the same case as had been previously analysed by applying the situated ISAD methodology.FindingsWhile the conventional approach focuses on articulated knowledge and observes the system under study with a detached stance, the situated approach includes tacit knowledge and recognises the importance of the environment. The situated analyst is immersed in the system, attempting to take the subject position of an actor in the system, while also maintaining some analytical distance.Research limitations/implicationsThe research method and framework presented is a novel way to compare the epistemological underpinnings of other systems analysis and design methodologies. Validity issues are explicitly addressed in the paper; although it is based on a single case, the fact that it is a real‐world problem gives it high external validity.Practical implicationsThe investigation is based on an actual system design case and shows that, in analysis and design, the different epistemological underpinnings affect what is identified as a problem and hence the type of solution proposed.Originality/valueThere has been little previous work comparing epistemological commitments of alternative ISAD methodologies as they are played out in actual application. This paper makes a significant contribution to the theoretical foundations of IS.

Mechatronic systems become ever more complex because of their increasing number of interconnected safety critical components and sophistication. MBSE (Model‐based Systems Engineering) and MBSA (Model‐Based Safety Assessment) are the most commonly adopted approaches to deal with the design and safety analysis of mechatronic systems. Unfortunately, both approaches are normally adopted separately, especially in the earlier phases of system design, thus leading to a lack of communication between system engineers and the safety team. This work aims to fill that gap at a high level, that is, through process interaction. This paper proposes an enhanced V‐model for the design of safety‐critical mechatronic systems. It relates a system development process with specific safety assessment methods. Specifically, the proposed workflow details exchange flows between the RFLP (Requirements, Functional, Logical, Physical) method, the FHA (Functional Hazard Analysis), the FMEA (Failure Mode and Effects Analysis), the MBSA and simulation, and the FTA (Fault Tree Analysis). These analyses are complemented with multiphysics modeling and simulation to observe system behavior in functional and failure scenarios, with the aim of requirements verification. The design workflow has been applied to a winged Unmanned Aerial Vehicle to apply the parallel process and the necessary interaction of MBSE and MBSA approaches. The information flows between the individual activities proved effective for designing a safe system before the verification phase. The main benefit of the proposed workflow is providing both the design and safety team with some interaction points, thus avoiding a lack of safety‐critical analysis in the early phases of system design.

PurposeModel-based systems engineering (MBSE) is an important approach for the transforming process from “document-centered” to “model centered” systems engineering mode in equipment development, which can effectively shorten the equipment development cycle and improve product design quality. This paper aims to understand if MBSE enables to support manufacturing and equipment development.Design/methodology/approachThe paper opted a bibliometric analysis of MBSE in domain of advanced manufacturing from different perspectives such as publication volume, research team, sources and keyword co-occurrence.FindingsFirstly, the application of MBSE in advanced manufacturing can be roughly divided into three stages. And MBSE has been widely implemented globally and has gradually formed several noteworthy teams. Secondly, this article has identified some high-quality sources, with a large number of publications and citations, the most influential publications focus on the practice or guidance of digital twins and intelligent manufacturing. Thirdly, research can be divided into six categories, including systems engineering, digitalization, intelligent manufacturing, product design, model and architecture and MBSE applications.Research limitations/implicationsBecause of the chosen research approach, the visualized network tends to lose certain information such as a few keywords may be inaccurately categorized.Practical implicationsThis paper comprehensively study the research status of MBSE in advanced manufacturing and forecasts future research trends, emphasizing the combination of intelligent manufacturing and digitization.Originality/valueThis paper fulfills an identified need to understand the current application status and future development trends of MBSE.