Der im Zuge der Globalisierung immer stärker anwachsende Wettbewerb im Bereich produzierender Unternehmen führt zu einem kontinuierlichen Wettlauf um stetig kürzer werdende Produktionslaufzeiten. Aufgrund dessen ist eine kontinuierliche Spezialisierung mit produktspezifischen Fertigungssystemen der Akteure am Markt zu verzeichnen, die direkt zu einer erhöhten Nachfrage von Sondermaschinen führt (Krause 2018). Diese geforderte Spezialisierung lässt eine interne Standardisierung für die Hersteller kaum zu und führt zu einer extrem hohen Variantenvielfalt, deren Beherrschung eine der Kernaufgaben bei der Sicherstellung der Wettbewerbsfähigkeit darstellt. Insbesondere große Produktstrukturen sind aufgrund der anfallenden Datenmenge und dem resultierenden, hohen Grad an Verknüpfungen schwierig zu verwalten (Blees 2011). Eine Möglichkeit, die interne Vielfalt bei einer gleichbleibenden externen Vielfalt zu reduzieren und somit den enormen Umfang der Produktarchitektur und deren Folgekosten einzuschränken, bietet die Modularisierung (Krause 2018). Die Entwicklung von modularen Produktstrukturen eröffnet mittels entsprechender Standardisierung die Möglichkeit, durch Modul-, Plattform-, und Baukastenentwicklung den Zielkonflikt zwischen Produktkosten und -vielfalt zu lösen (Ehrlenspiel 2009). Ein solcher Baukasten wird als notwendiges Mittel zur Beherrschung der Vielfalt betrachtet [...] Ein Ansatz zur Lösung dieser Problemstellung ist in der Literatur durch die Verwendung von PLM(Product-Lifecycle-Management)-Systemen beschrieben. Ein entsprechendes PLM-System soll die im Unternehmen existierende Daten- und Softwarestruktur verbinden und als Single-Source of Truth (Riesener 2017) fungieren, um die Konsistenz der Modelle zu gewährleisten. Allerdings wird gerade bei der Verwendung von Modellen bei der Schaffung und Verwaltung der Produktarchitektur deutlich, dass ein PLM-System hierzu nicht vollumfänglich dazu in der Lage ist, als einheitlicher Datenstamm zu fungieren. Hierbei ist die Ontologie, die Verwendung „einheitlicher Vokabeln“ (Kaufmann et al. 2014) zwischen den Systemen, um z. B. eine Konsistenzprüfung bei der Konfiguration zu implementieren, eine nicht zu unterschätzende Herausforderung bei der Umsetzung auf Basis eines reinen PLM-Systems. Wie in diesem Beitrag beschrieben wird, lässt sich diese Lücke mithilfe des MBSE (Model-Based Systems Engineering) schließen. [... aus der Einleitung]

This thesis work is performed in collaboration with Syntell AB and a client company interested in assistance with charging infrastructure dimensioning. The aim of this thesis is to develop an executable, generalizable model that can aid decision making regarding charging infrastructure. Furthermore, this is done within a Model-Based Systems Engineering (MBSE) context, which enables representation of the system as a model.  As the data and model concerning the client company is classified, it is not presented in this report. Instead, to further enhance the aim of developing a generalizable model, a test case is produced for this project work. This case consists of passenger electric vehicles and chargers in a metropolitan setting, where data is gathered from public sources.  The results show that the model is executable and flexible to fit any type of electric vehicle and different specifications of chargers. Using an MBSE approach enables the project owner to customize the model development for the specific use case. Additionally, defining a system in focus establishes what the system uptime is, enabling calculations of availability. The results for this specific use case are interpreted to show how the model can be used to aid the dimensioning of charging infrastructure using the model output. To further verify the model representation of the system, the model can be run in live-mode, where vehicles and chargers can be added while the model is running to instantly examine the system dynamics.  Concluding, the method for utilizing the model to evaluate systems availability is described. The model output, as well as the thorough description of the model, can be used to increase the knowledge within MBSE for executable modeling. / Detta projekt utförs i samarbete med Syntell AB och en tredje part som är intresserad av att förbättra sitt beslutsunderlag gällande dimensionering av laddinfrastruktur. Målet med arbetet är att utveckla en exekverbar och generaliserbar modell som kan användas för att underlätta dimensionering av laddinfrastruktur. Vidare så genomförs arbetet inom ramen för MBSE, vilket möjliggör en representation av systemet med hjälp av en modell. Eftersom kunddatan är konfidentiell appliceras modellen på ett fabricerat användningsfall som underlag för denna rapport. Detta baserar sig på elektriska personbilar i stadsmiljö, där data hämtas från publika källor. Att modellen används på två olika användningsfall stärker argumenten kring generaliserbarhet. Resultatet som presenteras är främst i syfte att demonstrera tolkning av resultat samt att grundligt förklara modellen. Resultaten visar att modellen är exekverbar och flexibel för att kunna anpassas utifrån godtyckligt elektriskt fordon och olika specifikationer för laddstationer. Genom att definiera ett system i fokus kan systemets drifttid utgöra grund för att kunna beräkna tillgänglighet. Resultaten tolkas i det specifika användningsfallet för att illustrera hur modellen kan användas för att underlätta en beslutsprocess gällande dimensionering av laddinfrastruktur. För att ytterligare verifiera modellens representation av verkligheten används ett interaktivt live-mode, där fordon och laddare kan läggas till under körning för att direkt undersöka systemdynamiken. Detta är ett viktigt verktyg vid kommunikation med intressenter för att stärka förtroendet för simuleringsresultat.  Sammanfattningsvis beskrivs metoden för att använda modellen till att undersöka systemtillgänglighet. Modellens utdata, tillsammans med beskrivningen av modellen, kan användas för att utöka kunskapen inom MBSE för exekverbar modellering.

Designing and developing complex engineering systems is a collaborative effort. In Model-Based Systems Engineering (MBSE), this collaboration is supported through the use of formal, computer-interpretable models, allowing stakeholders to address concerns using well-defined modeling languages. However, because concerns cannot be separated completely, implicit relationships and dependencies among the various models describing a system are unavoidable. Given that models are typically co-evolved and only weakly integrated, inconsistencies in the agglomeration of the information and knowledge encoded in the various models are frequently observed. The challenge is to identify such inconsistencies in an automated fashion. In this research, a probabilistic (Bayesian) approach to abductive reasoning about the existence of specific types of inconsistencies and, in the process, semantic overlaps (relationships and dependencies) in sets of heterogeneous models is presented. A prior belief about the manifestation of a particular type of inconsistency is updated with evidence, which is collected by extracting specific features from the models by means of pattern matching. Inference results are then utilized to improve future predictions by means of automated learning. The effectiveness and efficiency of the approach is evaluated through a theoretical complexity analysis of the underlying algorithms, and through application to a case study. Insights gained from the experiments conducted, as well as the results from a comparison to the state-of-the-art have demonstrated that the proposed method is a significant improvement over the status quo of inconsistency identification in MBSE.

The Ph.D. project has evolved from focusing on the technical problem of the integration and interoperability of an assemblage of complex systems and SoS within a flight training system to development of a workflow process using frameworks to aid the decision making process for the selection of optimal flight training blending mixes. The focus of the research involved developing a methodology to satisfy research project proposal requirements agreed upon with the industrial sponsor. This thesis investigates the complexity of a modern flight training systems and the need for understanding that it is supported by a complex Family of Systems (FoS) including Virtual Reality Training Environments such as flight simulators, to live training aircraft with various configurations of avionic controls. One of the key technical problems today is how best to develop and assemble a family of flight training system into an integrated Live/Synthetic mix for aircrew training to optimise organisation and training objectives. With the increased use of emulation/synthetic data on aircraft for live training, the synthetic boundary is becoming increasingly blurred. Systematic consideration of the most appropriate blend is needed. The methodology used in the research is model driven and the architecture produced is described at a level of abstraction to enable communication to all stakeholders for the means of understanding the structure involved in the system design process. Relational Oriented Systems Engineering and Technology Trade-Off Analysis (ROSETTA) frameworks are described using Model Based Systems Engineering (MBSE) techniques for supporting capability based trade-off decisions for selection of optimal flight training FoS mixes dependent on capability. The research proposes a methodology and associated methods including a high-level systematic closed loop information management structure for blended device/tool aircrew training and a modelling and analysis approach for the FoS aviation training problem to enhance the existing training programmes to provide a more efficient and agile training environment. The mathematical formalisms used provide a method of quantifying subjective opinions and judgements for trade studies to be accomplished on the suitability of technology for each student pilot in relation to training and organisational objectives. The methodology presented is by no means a final solution, but a path for further research to enable a greater understanding of the suitability of training tools/technology used to train individual pilots at various stages throughout the training pipeline lifecycle(s).

Mechatronic design is an enigma. On the one hand, mechatronic products promise enhanced functionality, and better performance at reduced cost. On the other hand, optimizing mechatronic design concepts is a major challenge to overcome during the design process. In the past, less attention has been paid to the life phases of a mechatronic product, and it was assumed that modifications in electronics and software will ensure that the product performs to expectation throughout its life time. However it has been realized that introducing design changes in mechatronics is not easy, since it is difficult to assess the consequences of a design decision, both during the design process of a new product, and during a design modification. It is also realized that there is a strong need to consider the product's life phases during the early phases of product development. Furthermore, it is rather difficult to perform a design optimization since it requires introducing changes across different domains, which is not well supported by the methods and tools available today. This thesis investigates the topic of mechatronic design and attacks some of the major challenges that have been identified regarding the design of mechatronic products. The goal is to provide support to the designers to facilitate better understanding of the consequences of their design choices as early as possible. The work also aims to provide support for assessing alternative design concepts, and for optimizing a design concept based on requirements, constraints and designer preferences at the time of design. The thesis highlights three main challenges related to mechatronic product development: the need for a common language during conceptual design; the inadequate information transfer between engineering domains; and the difficulty in assessing the properties of competing mechatronic concepts. A model-based integration approach is presented, and these key challenges are considered in relation to an integrated modeling and design infrastructure. The approach is illustrated through the design of two mechatronic systems- a two degrees-of-freedom robot, and a hospital bed propulsion system. Initial results provide evidence of good potential for information transfer across mechatronic domains. Although SysML was used for the case studies, some important questions were raised about its suitability as a common language for mechatronics. Suggestions for future work are: to utilize the developed infrastructure and incorporate a capability to model and assess consequences of competing design concepts; provide support for optimizing these concepts; and evaluate the usefulness of the developed infrastructure in a real-world design setting. These efforts should provide ample information to the designer for making adequate decisions during the design process. / QC 20110629

La complexité des systèmes conçus actuellement devient de plus en plus importante. En effet,afin de rester compétitives, les entreprises concevant des systèmes cherchent à leur rajouter de plus en plusde fonctionnalités. Cette compétitivité introduit aussi une demande de réactivité lors de la conception desystèmes, pour que le système puisse évoluer lors de sa conception et suivre les demandes du marché.Un des éléments identifiés comme empêchant ou diminuant cette capacité à concevoir de manière flexibledes systèmes complexes concerne les spécifications des systèmes, et en particulier l’utilisation de la languenaturelle pour spécifier les systèmes. Tout d’abord, la langue naturelle est intrinsèquement ambiguë et celarisque donc de créer des non-conformités si client et fournisseur d’un système ne sont pas d’accord sur lesens de sa spécification. De plus, la langue naturelle est difficile à traiter automatiquement, par exemple, onpeut difficilement déterminer avec un programme informatique que deux exigences en langue naturelle secontredisent. Cependant, la langue naturelle reste indispensable dans les spécifications que nous étudions,car elle reste un moyen de communication pratique et très répandu.Nous cherchons à compléter ces exigences en langue naturelle avec des éléments permettant à la fois de lesrendre moins ambiguës et de faciliter les traitements automatiques. Ces éléments peuvent faire partie demodèles (d’architecture par exemple) et permettent de définir le lexique et la syntaxe utilisés dans lesexigences. Nous avons testé les principes proposés sur des spécifications industrielles réelles et développéun prototype logiciel permettant de réaliser des tests sur une spécification dotée de ces éléments de syntaxeet de lexique. / Systems are becoming more and more complex, because to stay competitive, companies whichdesign systems search to add more and more functionalities to them. Additionally, this competition impliesthat the design of systems needs to be reactive, so that the system is able to evolve during its conception andfollow the needs of the market.This capacity to design flexibly complex systems is hindered or even prevented by various variouselements, with one of them being the system specifications. In particular, the use of natural language tospecify systems have several drawbacks. First, natural language is inherently ambiguous and this can leadsto non-conformity if customer and supplier of a system disagree on the meaning of its specification.Additionally, natural language is hard to process automatically : for example, it is hard to determine, usingonly a computer program, that two natural language requirements contradict each other. However, naturallanguage is currently unavoidable in the specifications we studied, because it remains very practical, and itis the most common way to communicate.We aim to complete these natural language requirements with elements which allow to make them lessambiguous and facilitate automatic processing. These elements can be parts of models (architectural modelsfor example) and allow to define the vocabulary and the syntax of the requirements. We experimented theproposed principles on real industrial specifications and we developped a software prototype allowing totest a specification enhanced with these vocabulary and syntax elements.

This dissertation develops systems engineering and machine learning models for aviation maintenance support. With the constant increase in demand for air travel, aviation organizations compete to maintain airworthy aircraft to ensure the safety of passengers. Given the importance of aircraft safety, the aviation sector constantly needs technologies to enhance the maintenance experience, ensure system safety, and limit aircraft downtime. Based on the current literature, the aviation maintenance sector still relies on outdated technologies to maintain aircraft maintenance documentation, including paper-based technical orders. Aviation maintenance documentation contains a mixture of structured and unstructured technical text, mainly inputted by operators, making them prone to error, misunderstanding communication, and inconsistency. This dissertation intends to develop decision support models based on systems engineering and artificial intelligence models that can automate the maintenance documentation system, extract useful information from maintenance work orders, and predict the aircraft's top degrader signals based on textual data. The first chapter of this dissertation introduces the significant setbacks of the aviation industry and provides a working ground for the following chapters. The dissertation's second chapter develops a system engineering framework using model-based systems engineering (MBSE) methodology to model the aviation maintenance process using the systems engineering language (SysML). The outcome of this framework is the design of an automated maintenance system model that can be used to automate maintenance documentation, making it less prone to error. The third chapter of the dissertation uses textual data in maintenance work orders to develop a hybrid approach that uses natural language processing (NLP) and transformer models to predict the readiness of a legacy aircraft. The model was tested using a real-life case study of the EA-6B military aircraft. The fourth chapter of this dissertation develops an ensemble transformer model based on three different transformer models. The ensemble model leverages the benefits of three different transformer architectures and is used to classify events based on an aviation log-based dataset. This dissertation's final and fifth chapter summarizes key findings, proposes future work directions, and provides the dissertation's limitations.

Increased trends towards servitization within previously exclusively manufacturing industries makes a larger part of maintenance become the responsibility of the manufacturer. This increased responsibility makes it more important for suppliers to know how different parameters contribute to cost, to be able to price their contracts correctly. Systems Engineering (SE) and Integrated Logistics Support (ILS) are two current methodologies on how to manage large systems. These methodologies are mainly used within defence industries and large capital-intensive infrastructure projects but are today also utilised in civilian industries. With the new methodology of Model Based Systems Engineering (MBSE) and the new demands of servitization it becomes more important to know how different parameters affect the final cost of a project during the very early phases of development. Within ILS the parameters Administrative Delay Time (ADT) and Logistics Delay Time (LDT) have previously not received attention proportional to their contribution to overall availability in projects. This thesis is based in literature, interviews of industry professionals, and the study of a real case of an electrical charging infrastructure project currently in development. From these sources multiple paths to resolve the issues with support from ILS, MBSE, SE, and other management literature are explored. Several attributes of the case, and characteristics of MBSE and ILS leads to the conclusion that coupling the methodologies with Lean methods would lead to better insight into where critical points in the explored system are and give ways of resolving issues with ADT and LDT that exist. The combination of MBSE and Lean methods could successfully identify possible critical points in the error handling of the electrical charging infrastructure system early in the process of implementation. Conclusionary the combination of MBSE, ILS, and Lean is a possibly powerful way to identify and improve the availability and consequently the cost of a project in the early stages. / Tjänstefiering är en trend som gör att en allt större del av underhåll inom tidigare endast tillverkande industrier blir tillverkarens ansvar. När detta ansvar ökar blir det viktigare för tillverkaren and veta vilka parametrar som är kostnadsdrivande. Detta för att kunna prissätta sina tjänster korrekt. Systemteknik (SE) och Integrerat Logistikstöd (ILS) är två metodologier som används till att hantera underhåll av stora system. Dessa nyttjas främst inom försvarsindustrin och inom kapitalintensiva infrastrukturprojekt, men används även i privat industri. Med hjälp av en utveckling inom SE, Modellbaserad Systemteknik (MBSE), och med de krav som tjänstefiering innebär så blir vikten av att ha korrekt angivna parametrar tidigt i projektet mer tydlig. Inom ILS är särskilt parametrarna administrativ väntetid (ADT) och logistisk väntetid (LDT) särskilt eftersatta med hänsyn till hur mycket de påverkar tillgängligheten och kostnaderna för systemet. Detta examensarbete baseras på tillgänglig litteratur inom nämnda områden, intervjuer med industrirepresentanter, och dokumentation och intervjuer i ett riktigt fall. Det riktiga fallet är ett pågående projekt för uppbyggnad och underhåll av laddningsinfrastruktur för eldrivna fordon. Från dessa källor utforskades och analyserades flera vägar för hur man skulle kunna förbättra hanteringen av ADT och LDT med grund i litteraturen kring ILS, MBSE, och SE med annan litteratur inom mangament som stöd. Fallets egenskaper, och egenskaper hos ILS och MBSE leder till slutsatsen att en kombination av MBSE och Lean skulle leda till att man lättare kan utforska kritiska delar av ett underhållssystem, och åtgärda existerande problem med ADT och LDT. En kombination av dessa principer kunde identifiera kritiska punkter i felhanteringssystemet hos laddarna i infrastrukturprojektet trots att projektet befann sig tidigt i implementationen. Slutligen kan konstateras att MBSE, ILS och Lean är en möjlig kraftfull kombination för att förbättra tillgängligheten tidigt i ett projekts livscykel.

The Concurrent Design Platform 4 (CDP4®) is a collaborative Model-Based Systems Engineering (MBSE) software tool conceived for architecting complex systems. Nevertheless, there are limitations concerning the manageable number of system options. The upcoming Siemens tool for generative engineering, Simcenter™ Studio, is attempting to overcome this limitation by enabling automatic synthesis and evaluation of architecture variants. The motivation for the Generative Concurrent Design (GCD) project as a collaboration between RHEA, Siemens and OHB is to develop a combined prototype of these two tools. This thesis presents a modelling of Copernicus Next Generation (CNG) space component, using generative capabilities in a typical Phase-0 study. It represents the third step of the bottom-up GCD validation process, intended to investigate how architecting differs among “Sub-system”, “Systems” and “Systems of Systems (SoS)”. Therefore, this work provides an architecting strategy which is generalizable for other SoS use-cases and contributes to assess whether extensions to ECSS-E-TM-10-25 are necessary to successfully support GCD. / Concurrent Design Platform 4 (CDP4®) är ett samarbetsverktyg för modellbaserad systemteknik (MBSE) som utformats för att bygga komplexa system. Dock finns det begränsningar vad gäller det antalet hanterbara systemalternativ. Det kommande Siemens-verktyget för generativ teknik, Simcenter™ Studio, försöker övervinna denna begränsning genom att möjliggöra automatisk syntes och utvärdering av arkitekturvarianter. Motivationen för Generative Concurrent Design (GCD) -projektet som ett samarbete mellan RHEA, Siemens och OHB är att utveckla en kombinerad prototyp av verktygen CDP4® och Simcenter™. Detta examensarbete presenterar en modellering av rymdkomponenten Copernicus Next Generation (CNG) med användning av generativa funktioner i en typisk fas-0-studie. Den representerar det tredje steget i GCD-valideringsprocessen nedifrån och upp, avsedd att undersöka hur arkitekturen skiljer sig åt mellan "Sub-system", "Systems" och "Systems of Systems (SoS)". Detta arbete ger därför en arkitektonisk strategi som är generaliserbar för andra SoS-användningsfall och bidrar till att bedöma om förlängningar till ECSS-E-TM-10-25 är nödvändiga för att framgångsrikt stödja GCD.

Energy and environmental impacts are two factors that will influence urban region composition in the near future. One emerging issue is the effect on water usage resulting from changes in regional or urban transportation trends. With many regions experiencing stresses on water availability, transportation planners and users need to combine information on transportation-related water consumption for any region and assess potential impacts on local water resources from the expansion of alternative transportation modes. This thesis will focus on use-phase water consumption factors for multiple vehicle modes, energy and fuel pathways, roads, and vehicle infrastructure for a given transportation network. While there are studies examining life cycle impacts for energy generation and vehicle usage, few repeatable models exist for assessing overall water consumption across several transportation modes within urban regions. As such, the question is: is it possible to develop a traceable decision support model that combines and assesses water consumption from transportation modes and related mobility infrastructure for a given mobility network? Based on this, an object-oriented system model of transportation elements was developed using the Systems Modeling Language (SysML) and Model-Based Systems Engineering principles to compare water consumption across vehicle modes for assessing the resiliency of existing infrastructure and water resources. To demonstrate the intent of this model, daily network usage water consumption will be analyzed for current and alternative network scenarios projected by policies regarding the expansion of alternative energy. The model is expected to show variations in water consumption due to fluctuations in energy pathways, market shares, and driving conditions, from which the model should help determine the feasibility of expanding alterative vehicles and fuels in these networks. While spatially explicit data is limited compared to the national averages that are used as model inputs, the analytical framework within this model closely follows that of existing assessments and the reusable nature of SysML model elements allows for the future expansion of additional transportation modes and infrastructure as well as other environmental analyses.