System design is an inherently expensive and time consuming process. Engineers are constantly tasked to investigate new solutions for various programs. Model-based systems engineering (MBSE) is an up and coming successful method used to reduce the time spent during the design process. By utilizing simulations, model-based systems engineering can verify high-level system requirements quickly and at low cost early in the design process. The Horizon Simulation Framework, or HSF, provides the capability of simulating a system and verifying the system performance. This paper outlines an improvement to the Horizon Simulation Framework by providing information to the user regarding schedule failures due to subsystem failures and constraint violations. Using the C# language, constraint violation rates and subsystem failure rates are organized by magnitude and written to .csv files. Also, proper subsystem failure and constraint violation checking orders were stored for HSF to use as new evaluation sequences. The functionalities of the systemEval framework were verified by five test cases. The output information can be used for the user to improve their system and possibly reduce the total run-time of the Horizon Simulation Framework.

Yes / The process of generating FMEA following document-centric approach is tedious and susceptible to human error. This paper presents preliminary methodology for robotic manufacturing process modelling in MBSE environment with a scope of automating multiple steps of the modelling process using ontology. This is followed by the reasoning towards automatic generation of process FMEA from the MBSE model. The proposed methodology allows to establish robust and self-synchronising links between process-relevant information, reduce the likelihood of human error, and scale down time expenses.

Technische Änderungen sind im Produktentstehungsprozess allgegenwärtig und beanspruchen einen hohen Anteil an vorhandenen Forschungs- und Entwicklungskosten. Gleichzeitig wird ca. ein Drittel aller technischen Änderungen aufgrund der hohen Systemkomplexität als kritisch eingestuft. Für den Umgang mit hoher Systemkomplexität werden Ansätze des Model-Based Systems Engineering (MBSE) als vielversprechend gesehen. MBSE stellt einen formalisierten Ansatz zur Erstellung und Analyse von domänenübergreifenden Systemmodellen dar, die u.a. in den Bereichen Anforderungsmanagement, Verifikation und Validierung sowie Analyse und Synthese unterstützen können. Die Entwicklung von technischen Systemen erfolgt in Generationen. Mit Hilfe des Beschreibungsmodells der Systemgenerationsentwicklung - SGE nach ALBERS können u.a. technische und ökonomische Risiken von technischen Änderungen auf Basis der Herkunft von Referenzsystemelementen sowie der Übernahme- und Neuentwicklungsanteilen eingeschätzt werden. Es existieren zudem viele weitere Ansätze im technischen Änderungsmanagement, die sich auf einzelne Aspekte der Ausbreitungs- und Auswirkungsanalyse fokussieren. Die modellbasierte Methodik AECIA - Advanced Engineering Change Impact Approach bietet eine ganzheitliche Unterstützung im technischen Änderungsmanagement. Erste Veröffentlichungen untersuchen insbesondere Aktivitäten zur Prüfung der Validität sowie die Modellierung und Analyse der Ausbreitung von technischen Änderungen. Ziel dieser Veröffentlichung ist es die AECIA-Methodik um ein Vorgehen zur Bewertung von technischen Änderungen zu erweitern und dieses am Beispiel einer Sondermaschine anzuwenden und zu evaluieren.

Dans la mesure où un système est un ensemble d'éléments en interaction, la difficulté pour un ingénieur système est de guider l’architecture d'un modèle « total » du système en tant qu'ensemble de modèles « locaux » d’ingénieries interdisciplinaires en interaction. Les travaux présentés dans ce mémoire s’intéressent plus précisément à la nature heuristique, spécifiante et exécutable de cette relation « totale » de couplage afin de construire un modèle virtuel du système à faire. La perspective holonique retenue permet de considérer cette relation de couplage de façon descriptive du TOUT et prescriptive de chacune des PARTIES aussi bien en regard de la situation-système à percevoir que des constitutifs-système à architecturer. Ainsi, nous avons revisité cette relation en tant que processus itératif, récursif et collaboratif de co-spécification-système visant à supporter la requête de connaissances auprès de chacune des ingénieries spécialistes délivrant en retour les modèles constitutifs satisfaisant des exigences systèmes. Notre environnement de co-modélisation-système se compose alors d’un ensemble d’environnements élémentaires de modélisation de constituants-système, avec pour objectif de préserver les outils, méthodes et processus de travail de chacune des parties prenantes. La modélisation au niveau système s’appuie sur le langage de modélisation « SysML » pour architecturer l’ensemble des connaissances. La vérification et la validation système s’effectue par co-exécution de modèles autour d’un bus de co-simulation, y compris in-situ avec la plate-forme d’expérimentation CISPI du projet SAFETECH du CRAN constituant notre cas d’application / Insofar as a system is a set of interacting elements, the difficulty for a system engineer is to guide the whole model architecture of a system as a set of interdisciplinary engineering part models interacting. The works presented in this thesis are specifically interested in the heuristic, specifying and executable nature of this whole relationship coupling to design a virtual model of the system-of-interest. The holonic perspectives allows us to consider this coupling relationship as descriptive of a WHOLE (H) and prescriptive of each parts as well in regards to system situation to perceive, as system-elements to architect. In this sense, we revisit this relation as an iterative, recursive and collaborative process of system co-specification to the quest of knowledge with each specialist engineering delivering constitutive models satisfying basic requirements. Our system co-modelling environment is itself composed of a set of system-components modelling environment, with the stated objective to preserve tools, methods and works of each stakeholders in order to facilitate the expression of their skills. The modelling at a system level is based on the system modelling language (SysML) to architecture the set of knowledge. Verification and validation are performed by co-execution of models around a co-simulation bus, including CISPI platform of SAFETECH project of CRAN constituting our case study

This dissertation develops a new model transformation approach that supports engineering model integration, which is essential to support contemporary interdisciplinary system design processes. We extend traditional model transformation, which has been primarily used for software engineering, to enable model-based systems engineering (MBSE) so that the model transformation can handle more general engineering models. We identify two issues that arise when applying the traditional model transformation to general engineering modeling domains. The first is instance data integration: the traditional model transformation theory does not deal with instance data, which is essential for executing engineering models in engineering tools. The second is syntactical inconsistency: various engineering tools represent engineering models in a proprietary syntax. However, the traditional model transformation cannot handle this syntactic diversity. In order to address these two issues, we propose a new multi-layer syntactical model transformation approach. For the instance integration issue, this approach generates model transformation rules for instance data from the result of a model transformation that is developed for user model integration, which is the normal purpose of traditional model transformation. For the syntactical inconsistency issue, we introduce the concept of the complete meta-model for defining how to represent a model syntactically as well as semantically. Our approach addresses the syntactical inconsistency issue by generating necessary complete meta-models using a special type of model transformation.

This dissertation supports human decision-making with a Model-Based Systems Engineering methodology enabling engineering analysis, and in particular Operations Research analysis of discrete-event logistics systems, to be more widely used in a cost-effective and correct manner. A methodology is a collection of related processes, methods, and tools, and the process of interest is posing a question about a system model and then identifying and building answering analysis models. Methods and tools are the novelty of this dissertation, which when applied to the process will enable the dissertation's goal. One method which directly enables the goal is adding automation to analysis model-building. Another method is abstraction, to make explicit a frequently-used bridge to analysis and also expose analysis model-building repetition to justify automation. A third method is formalization, to capture knowledge for reuse and also enable automation without human interpreters. The methodology, which is itself a contribution, also includes two supporting tool contributions. A tool to support the abstraction method is a definition of a token-flow network, an abstract concept which generalizes many aspects of discrete-event logistics systems and underlies many analyses of them. Another tool to support the formalization method is a definition of a well-formed question, the result of an initial study of semantics, categories, and patterns in questions about models which induce engineering analysis. This is more general than queries about models in any specific modeling language, and also more general than queries answerable by navigating through a model and retrieving recorded information. A final contribution follows from investigating tools for the automation method. Analysis model-building is a model-to-model transformation, and languages and tools for model-to-model transformation already exist in Model-Driven Architecture of software. The contribution considers if and how these tools can be re-purposed by contrasting software object-oriented code generation and engineering analysis model-building. It is argued that both use cases share a common transformation paradigm but executed at different relative levels of abstraction, and the argument is supported by showing how several Operations Research analyses can be defined in an object-oriented way across multiple layered instance-of abstraction levels. Enabling Operations Research analysis of discrete-event logistics systems to be more widely used in a cost-effective and correct manner requires considering fundamental questions about what knowledge is required to answer a question about a system, how to formally capture that knowledge, and what that capture enables. Developments here are promising, but provide only limited answers and leave much room for future work.

Contemporary systems engineering problems are becoming increasingly complex as they are handled by geographically distributed design teams, constrained by the objectives of multiple stakeholders, and inundated by large quantities of design information. According to the principles of model-based systems engineering (MBSE), engineers can effectively manage increasing complexity by replacing document-centric design methods with computerized, model-based approaches. In this thesis, modeling constructs from SysML and Modelica are integrated to improve support for MBSE. The Object Management Group has recently developed the Systems Modeling Language (OMG SysML ) to provide a comprehensive set constructs for modeling many common aspects of systems engineering problems (e.g. system requirements, structures, functions). Complementing these SysML constructs, the Modelica language has emerged as a standard for modeling the continuous dynamics (CD) of systems in terms of hybrid discrete- event and differential algebraic equation systems. The integration of SysML and Modelica is explored from three different perspectives: the definition of CD models in SysML; the use of graph transformations to automate the transformation of SysML CD models into Modelica models; and the integration of CD models and other SysML models (e.g. structural, requirements) through the depiction of simulation experiments and engineering analyses. Throughout the thesis, example models of a car suspension and a hydraulically-powered excavator are used for demonstration. The core result of this work is the provision of modeling abilities that do not exist independently in SysML or Modelica. These abilities allow systems engineers to prescribe necessary system analyses and relate them to stakeholder concerns and other system aspects. Moreover, this work provides a basis for model integration which can be generalized and re-specialized for integrating other modeling formalisms into SysML.

Design synthesis is a fundamental engineering task that involves the creation of structure from a desired functional specification; it involves both creating a system topology as well as sizing the system's components. Although the use of computer tools is common throughout the design process, design synthesis is often a task left to the designer. At the synthesis stage of the design process, designers have an extensive choice of design alternatives that need to be considered and evaluated. Designers can benefit from computational synthesis methods in the creative phase of the design process. Recent increases in computational power allow automated synthesis methods for rapidly generating a large number of design solutions. Combining an automated synthesis method with an evaluation framework allows for a more thorough exploration of the design space as well as for a reduction of the time and cost needed to design a system. To facilitate computational synthesis, knowledge about feasible system configurations must be captured. Since it is difficult to capture such synthesis knowledge about any possible system, a design domain must be chosen. In this thesis, the design domain is hydraulic systems. In this thesis, Model-Driven Software Development concepts are leveraged to create a framework to automate the synthesis of hydraulic systems will be presented and demonstrated. This includes the presentation of a domain specific language to describe the function and structure of hydraulic systems as well as a framework for synthesizing hydraulic systems using graph grammars to generate system topologies. Also, a method using graph grammars for generating analysis models from the described structural system representations is presented. This approach fits in the context of Model-Based Systems Engineering where a variety of formal models are used to represent knowledge about a system. It uses the Systems Modeling Language developed by The Object Management Group (OMG SysML™) as a unifying language for model definition.

<div>The internal and external interactions between the complex structural and behavioral characteristics of the system of interest and the surrounding environment result in unpredictable emergent behaviors. These emergent behaviors are not well understood, especially when modeled using the traditional top-down systems engineering approach. The intrinsic nature of current complex systems has called for an elegant solution that provides an integrated framework in Model-Based Systems Engineering. A considerable gap exists to integrate system engineering activities and engineering analysis, which results in high risk and cost. This thesis presents a framework that incorporates indefinite and definite modeling aspects that are developed to determine the complexity that arises during the development phases of the system. This framework provides a workflow for modeling complex systems using Systems Modeling Language (SysML) that captures the system’s requirements, behavior, structure, and analytical aspects at both problem definition and solution levels. This research introduces a new level/dimension to the framework to support engineering analysis integrated with the system architecture model using FMI standards. A workflow is provided that provides the enabling methodological capabilities. It starts with a statement of need and ends with system requirement verification. Detailed traceability is established that glues system engineering and engineering analysis together. Besides, a method is proposed for predicting the system’s complexity by calculating the complexity index that can be used to assess the complexity of the existing system and guide the design and development of a new system. To test and demonstrate this framework, a case study consisting of a complex district cooling system is implemented. The case study shows the framework’s capabilities in enabling the successful modeling of a complex district cooling system. The system architecture model was developed using SysML and the engineering analysis model using Modelica. The proposed framework supports system requirements verification activity. The analysis results show that the district chiller model developed using Modelica produces chilled water below 6.6 degrees Celsius, which satisfies the system requirement for the district chiller system captured in the SysML tool. Similarly, many such requirement verification capabilities using dynamic simulation integration with the high-level model provides the ability to perform continuous analysis and simulation during the system development process. The systems architecture complexity index is measured for the district cooling case study from the black-box and white box-perspective. The measured complexity index showed that the system architecture’s behavioral aspect increases exponentially compared to the structural aspect. The systems architecture’s complexity index at black-box and white-box was 4.998 and 67.3927, respectively.</div>

Im Zuge der Globalisierung sehen sich produzierende Unternehmen mit einem kontinuierlich anwachsenden Wettbewerbsdruck konfrontiert. Aufgrund dessen sehen sich viele Marktakteure zu einer intensivierten Spezialisierung gezwungen, um auf kunden-individuelle Anforderungen eingehen zu können. Einen möglichen Lösungsansatz zur Bewältigung dieser Herausforderung bietet der Ansatz der Modularisierung. Hier wird allerdings nicht konkret ein Baukasten definiert, vielmehr werden verschiedene Alternativen generiert. Die Entscheidung, welcher Baukasten schlussendlich implementiert wird, fällt meist aufgrund einiger weniger Einflussfaktoren sowie maßgeblich durch Expertenentscheidungen. An dieser Stelle setzt der vorliegende Beitrag an. Um ein quantifizierbares und ganzheitliches Kriterium zur Unter-stützung der Auswahl modularer Baukastensysteme zu bieten, wird eine multifaktorielle Simulation eingesetzt. Einer der maßgeblichen Aspekte derer ist die beidseitige Inbezugnahme von sowohl Kunden- als auch Unternehmensperspektive. Dies wird v.a. durch die Verwendung eines dynamischen Produktkonfigurationssystems ermöglicht. Um die zugrundeliegenden, teils komplexen Produktarchitekturen datentechnisch konsistent und pflegbar zu halten, wird zusätzlich der Einsatz einer modellbasierten Datenstruktur aufgezeigt. Die Verwendung des Model-Based Systems-Engineering (MBSE) Ansatzes hilf dabei, die vielschichtigen Zusammenhänge des Modulbaukastens in einer konsistenten und maschinenlesbaren Form auszudrücken. Somit kann das Konfigurationssystem produktunabhängig auf die Ontologie der zugrundeliegenden Datenstruktur zugreifen. Für die Baukastensimulation wird dieses Konfigurationssystem rekursiv für mehrere Kundenanfragen und alternative Baukästen eingesetzt, um anschließend mittels eines geometrisch-mathematischen Algorithmus ein multi-dimensionales Entscheidungskriterium hinsichtlich der Baukasten-performance zu generieren.