141 research outputs found

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

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    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 review of information flow diagrammatic models for product-service systems

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    A product-service system (PSS) is a combination of products and services to create value for both customers and manufacturers. Modelling a PSS based on function orientation offers a useful way to distinguish system inputs and outputs with regards to how data are consumed and information is used, i.e. information flow. This article presents a review of diagrammatic information flow tools, which are designed to describe a system through its functions. The origin, concept and applications of these tools are investigated, followed by an analysis of information flow modelling with regards to key PSS properties. A case study of selection laser melting technology implemented as PSS will then be used to show the application of information flow modelling for PSS design. A discussion based on the usefulness of the tools in modelling the key elements of PSS and possible future research directions are also presented

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

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    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

    Toward Architecture Design for Discrete Event Logistics Systems

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    The scope and scale of contemporary discrete event logistics systems (DELS), such as parcel logistics hubs, distribution centers, and global manufacturing systems, continues to outpace the traditional industrial engineering approach to facilities and system design, particularly with regard to system architecture. System architecture is fundamental to system design in most engineering disciplines. While not part of the traditional DELS design portfolio, the ingredients are available today to support system engineering architecture design methods and tools for application to DELS design

    The Future of Modeling in Material Handling Systems

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    Today, when we talk about “modeling” in the context of material handling systems, invariably we are referring to a mathematical or computational model for analyzing some aspect of the system, such as its throughput rate, response time, cost of ownership, required storage capacity, etc. Creating these kinds of models requires considerable knowledge in at least two domains the material handling system domain, and the analysis methodology domain—and considerable skill in the “art of modeling” in order to express the former in the terms of the latter. The results can be somewhat ad hoc—e.g., two different modelers are likely to create two somewhat different simulation models of exactly the same material handling system. In the past, the situation in software development was very similar, with individual programming experts idiosyncratically driving software development. Over the past twenty years, however, computer scientists and software engineers have created a radically different approach to the process of software “modeling” called Model Driven Architecture, or MDA, that is used to create software for standard applications. The thesis of this paper is that MDA can be adapted to the kind of modeling done to support design and operational decision making in material handling systems. The paper describes MDA technologies in the context of material handling system modeling, and explains how adapting this approach to our context will transform the way we do research and the way material handling systems are analyzed and designed in practice

    A Novel Boundary Integral Formulation for Quantum Energy Eigenvalue Analysis and Its Application in a Model-Based Systems Engineering Framework for Quantum Systems Development

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    In recent decades, the development and utilization of high-end technologies have increased noticeably. This progress has become possible by finding a complete understanding of physical rules in microscopic scales, such as quantum mechanics. Quantum technologies can be applied to various fields, including optics, superconduction, computing and simulation, precision measurement, and biomedical imaging to enhance the performance of relevant devices and systems. However, the complexity which emerges in the procedure of developing such devices can prevent one from taking advantage of potential quantum technologies to effectively develop these devices. In the current research, an attempt has been made to find a solution for this problem. Based on the various benefits of using systems engineering techniques in managing the complexities of developing such systems, a model-based systems engineering methodology has been employed towards the development of quantum systems. In this research, quantum dot solar cells are chosen as a typical quantum system, and four main stages of system analysis, design, manufacturing, and verification, validation, and testing are considered and studied during the product lifecycle. By integrating systems engineering tools with domain engineering tools, it is verified that the use of appropriate models can facilitate the overall procedure of system development. Moreover, by focusing on the system design and analysis phases, a novel boundary integral formulation was developed in this research to accelerate the procedure of system development. This approach decreases the computation burden required to solve the governing equation of quantum devices and accomplishes the design procedure more effectively and accurately. Various case studies have demonstrated that the proposed technique can enhance both the accuracy and computational-efficiency in the design of new quantum devices

    Knowledge Representation in Engineering 4.0

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    This dissertation was developed in the context of the BMBF and EU/ECSEL funded projects GENIAL! and Arrowhead Tools. In these projects the chair examines methods of specifications and cooperations in the automotive value chain from OEM-Tier1-Tier2. Goal of the projects is to improve communication and collaborative planning, especially in early development stages. Besides SysML, the use of agreed vocabularies and on- tologies for modeling requirements, overall context, variants, and many other items, is targeted. This thesis proposes a web database, where data from the collaborative requirements elicitation is combined with an ontology-based approach that uses reasoning capabilities. For this purpose, state-of-the-art ontologies have been investigated and integrated that entail domains like hardware/software, roadmapping, IoT, context, innovation and oth- ers. New ontologies have been designed like a HW / SW allocation ontology and a domain-specific "eFuse ontology" as well as some prototypes. The result is a modular ontology suite and the GENIAL! Basic Ontology that allows us to model automotive and microelectronic functions, components, properties and dependencies based on the ISO26262 standard among these elements. Furthermore, context knowledge that influences design decisions such as future trends in legislation, society, environment, etc. is included. These knowledge bases are integrated in a novel tool that allows for collabo- rative innovation planning and requirements communication along the automotive value chain. To start off the work of the project, an architecture and prototype tool was developed. Designing ontologies and knowing how to use them proved to be a non-trivial task, requiring a lot of context and background knowledge. Some of this background knowledge has been selected for presentation and was utilized either in designing models or for later immersion. Examples are basic foundations like design guidelines for ontologies, ontology categories and a continuum of expressiveness of languages and advanced content like multi-level theory, foundational ontologies and reasoning. Finally, at the end, we demonstrate the overall framework, and show the ontology with reasoning, database and APPEL/SysMD (AGILA ProPErty and Dependency Descrip- tion Language / System MarkDown) and constraints of the hardware / software knowledge base. There, by example, we explore and solve roadmap constraints that are coupled with a car model through a constraint solver.Diese Dissertation wurde im Kontext des von BMBF und EU / ECSEL gefördertem Projektes GENIAL! und Arrowhead Tools entwickelt. In diesen Projekten untersucht der Lehrstuhl Methoden zur Spezifikationen und Kooperation in der Automotive Wertschöp- fungskette, von OEM zu Tier1 und Tier2. Ziel der Arbeit ist es die Kommunikation und gemeinsame Planung, speziell in den frühen Entwicklungsphasen zu verbessern. Neben SysML ist die Benutzung von vereinbarten Vokabularen und Ontologien in der Modellierung von Requirements, des Gesamtkontextes, Varianten und vielen anderen Elementen angezielt. Ontologien sind dabei eine Möglichkeit, um das Vermeiden von Missverständnissen und Fehlplanungen zu unterstützen. Dieser Ansatz schlägt eine Web- datenbank vor, wobei Ontologien das Teilen von Wissen und das logische Schlussfolgern von implizitem Wissen und Regeln unterstützen. Diese Arbeit beschreibt Ontologien für die Domäne des Engineering 4.0, oder spezifischer, für die Domäne, die für das deutsche Projekt GENIAL! benötigt wurde. Dies betrifft Domänen, wie Hardware und Software, Roadmapping, Kontext, Innovation, IoT und andere. Neue Ontologien wurden entworfen, wie beispielsweise die Hardware-Software Allokations-Ontologie und eine domänen-spezifische "eFuse Ontologie". Das Ergebnis war eine modulare Ontologie-Bibliothek mit der GENIAL! Basic Ontology, die es erlaubt, automotive und mikroelektronische Komponenten, Funktionen, Eigenschaften und deren Abhängigkeiten basierend auf dem ISO26262 Standard zu entwerfen. Des weiteren ist Kontextwissen, welches Entwurfsentscheidungen beinflusst, inkludiert. Diese Wissensbasen sind in einem neuartigen Tool integriert, dass es ermöglicht, Roadmapwissen und Anforderungen durch die Automobil- Wertschöpfungskette hinweg auszutauschen. On tologien zu entwerfen und zu wissen, wie man diese benutzt, war dabei keine triviale Aufgabe und benötigte viel Hintergrund- und Kontextwissen. Ausgewählte Grundlagen hierfür sind Richtlinien, wie man Ontologien entwirft, Ontologiekategorien, sowie das Spektrum an Sprachen und Formen von Wissensrepresentationen. Des weiteren sind fort- geschrittene Methoden erläutert, z.B wie man mit Ontologien Schlußfolgerungen trifft. Am Schluss wird das Overall Framework demonstriert, und die Ontologie mit Reason- ing, Datenbank und APPEL/SysMD (AGILA ProPErty and Dependency Description Language / System MarkDown) und Constraints der Hardware / Software Wissensbasis gezeigt. Dabei werden exemplarisch Roadmap Constraints mit dem Automodell verbunden und durch den Constraint Solver gelöst und exploriert

    MARTE for CPS and CPSoS: Present and Future, Methodology and Tools

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    International audienceCyber-Physical Systems (CPS) combine discrete computing elements together with physical devices in uncertain environment conditions. There have been many models to capture different aspects of CPS. However, to deal with the increasing complexity of these ubiquitous systems, which invade all the part of our lives, we need an integrated framework able to capture all the different views of such complex systems in a consistent way. We also need to combine tools to analyze their expected properties and guarantee safety issues. Far from handing out a full-fledge solution, we merely explore a possible path that could bring part of the solution. We advocate for relying on uml models as a unifying framework to build a single-source modeling environment with design, exploration and analysis tools. We comment on some useful extensions of UML, including MARTE and SysML, and show how they can together capture different views of CPS. We also report on some recent results obtained and discuss possible evolutions in a near future

    Design and development of a sustainability toolkit for simulation modeling and analysis

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    A simulation-based sustainability toolkit is developed in this research, in order to efficiently provide the capability of modeling and evaluating the sustainability related performance measures in systems of interest. As sustainability related issues, such as energy consumption, emissions, and waste generation are becoming a more integrated part of operational and long-term planning decisions, simulation modeling is needed to analyze the system performance not only from the traditional system performance measures such as productivity and efficiency, but also taking into account the environmental impacts within the studied system in order to aid in decision-making. This research introduces the concept and general methodology to develop such a sustainability toolkit for simulation and provides a prototype implementation of the toolkit using commercially available discrete event simulation software. In particular, toolkit modules have been developed for modeling and evaluating the sustainability aspects of transportation and logistics systems, industrial and manufacturing processes, and warehouse material handling systems. Furthermore, general sustainability toolkit modules are constructed to model other systems of interest. The toolkit contains a flexible framework which enables the simulation modeling and analysis of the sustainability related performance measures as easily as traditional system performance measures. The toolkit will enable the users to efficiently simulate complex systems taking into account system sustainability in an integrated decision-making process

    Test-Driven, Model-Based Systems Engineering.

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