This paper presents an approach to system-of-systems engineering for product development with the use of ontology. A proposed method for building as well as using ontology to generate and explore system-of-systems design spaces based on identified system-of-system needs is presented. The method is largely built to cover the first levels of related work, where a process for system of systems in the context of product development is introduced. Within this work, it is shown that scenarios for a system-of-systems can be used to identify needs and subsequently the system-of-systems capabilities that fulfils them. The allocation of capabilities to possible constituent systems is used to show the available design space. The proposed method of this paper therefore addresses these initial challenges and provides a framework for approaching the system-of-systems design space creation using ontology. A case study is used to test the method on a fictitious search and rescue scenario based on available resources and information from the Swedish Maritime Administration. The case study shows that a representation of a system-of-systems scenario can be created in an ontology using the method. The ontology provides a representation of the involved entities from the fictitious scenario and their existing relationships. Defined ontology classes containing conditions are used to represent the identified needs for the system-of-systems. The invocation of a description logic reasoner is subsequently used to classify and create an inferred ontology where the available system-of-systems solutions are represented as sub-classes and individuals of the defined classes representing the needs. Finally, several classes representing different possible system-of-systems needs are used to explore the available design space and to identify the most persistent solutions of the case study.

System-of-Systems Engineering (SoSE) has become a constantly growing field within product development for complex systems. Systems are becoming more and more connected with other systems and the operational environment in general. This takes the development process to new levels of complexity where high degrees of uncertainties are expected due to ever occurring changes in the operational environment, and other external factors such as politics, economy, and technology. This creates a need of being able to understand the influence of changes early in the development process and to facilitate the systems? perseverance. The focus of the development shifts from fulfilling specific requirements, to being able to meet needs and deliver capabilities over time. Additionally, modeling and simulation for complex systems and System-of-Systems (SoS) becomes a valued alternative to the economically prohibited and almost impossible prototype testing. In consideration of this problem, the presented work introduces a method for both modeling and simulation of a SoS. The method uses ontology with description logic reasoning to derive and narrow down a SoS design space which is further analyzed using Agent Based Simulation (ABS). A Search and Rescue (SAR) scenario is used as a case study to test the method. Measures of Effectiveness (MoE), based on the time it takes to find a rescue subject and the cost of doing so, are used to evaluate the SoS performances. The presented method is envisioned to be used early in the development of complex systems and SoS to increase the overall understanding of them.

Aerospace systems are connected with the operational environment and other systems in general. The focus in aerospace product development is consequently shifting from a singular system perspective to a System-of-Systems (SoS) perspective. This increasing complexity gives rise to new levels of uncertainty that must be understood and managed to produce aerospace solutions for an ever-changing future. This paper presents an approach to using architecture frameworks, and ontologies with description logic reasoning capabilities, to break down SoS needs into required capabilities and functions. The intention of this approach is to provide a consistent way of obtaining the functions to be realized in order to meet the overarching capabilities and needs of an SoS. The breakdown with an architecture framework results in an initial design space representation of functions to be performed. The captured knowledge is then represented in an ontology with description logic reasoning capabilities, which provides a more flexible way to expand and process the initial design space representation obtained from the architecture framework. The proposed approach is ultimately tested in a search and rescue case study, partly based on the operations of the Swedish Maritime Administration. The results show that it is possible to break down SoS needs in a consistent way and that ontology with description logic reasoning can be used to process the captured knowledge to both expand and reduce an available design space representation.

This paper presents a method for generating a design space intended for aircraft design with the use of ontologies. Aircraft design, seen from a System-of-Systems (SoS) perspective, gives an idea of the complicated relationships and complexities that need to be managed and understood to develop suitable systems for an ever-changing future. Holistic SoS analyzes are used to investigate customer and stakeholder needs that then can be broken down into capabilities and subsequently functions to be performed by involved Constituent Systems (CS), sub-systems and system elements. Ontologies with description logic reasoning capabilities are then used to represent the outcome of the breakdown. An ontology development and integration process can afterwards be used to merge different ontologies together and by that map the derived functions to means that can implement them. This results in an available SoS design space that can be further processed using a description logic reasoner. The outcome of the proposed method is a reduced available design space of functions to be performed and their respective design alternatives. Search and Rescue (SAR) operations based on the Swedish Maritime Administration (SMA) are used as a case study to test the proposed method and to illustrate how it can be utilized. At the end, a design space of alternatives for a new type of search aircraft is generated with ontology and description logic reasoning.

Studying Systems of Systems (SoS) in relation to Measures of Effectiveness (MoE) is a difficult task. This is due to that SoSs include several system levels and operate in changing environments. There are also computational challenges related to modeling and simulation of SoSs and it is difficult to predict behaviors. Therefore, choosing model fidelity for system models and assessing their impact on MoE is of high relevance to the field. This paper illustrates an approach to modeling and simulation for SoSs that can be used to assess the impact of scenario parameters and to explore when level of fidelity on system level affects the MoE. This is made through a case study based on Search and Rescue (SAR) operations where a Design Of Experiments (DOE) of scenario parameters is performed and simulations of each scenario experiment is performed. The case study shows how Agent Based Simulations (ABS) can be used to obtain the MoE for different SAR missions and how the choice of model fidelity for one of the aircraft’s sensors has different effects for various scenarios. Additionally, a Visual Analytics (VA) approach is introduced and used to create a dashboard for visualizing the obtained simulation results in an interactive way. This allows users to make explorations on the resulting data and see how different scenarios influence the performance of each SoS. Furthermore, the results show that changes in scenario parameters impacts the MoE and that this is difficult to predict, at least using a quantitative method. The results point to the importance of exploration for both the scenario, using an interactive dashboard, but also to the importance of exploring the simulation model to study emerging phenomenon. The results of this approach have raised questions regarding if a more qualitative approach of studying SoSs could be beneficial to study MoE for SoSs and if inspiration could be transferred from a more scientific point of view of systems.

This paper presents a method for generating a geometrical representation of a concept aircraft from an ontology description. An ontology is used as an overarching knowledge base where entities, such as required functions, their design alternatives, and requirements can be represented. Description logic reasoning is then used to process the available design space and generate suitable concepts to fulfil desired functions, as well as indicate suitable approaches for a subsequent sizing procedure. As ontology representations are limited in terms of numerical calculation capabilities, the obtained concept information must be extracted for additional processing. Further investigations, such as statistical analyses, are consequently performed in order to expand the available information of the concept generated from the ontology. This expansion is performed to obtain estimates of required inputs for a continued geometrical sizing procedure. The outcome of the method is an estimation of the concept’s geometry and its characteristics. This information can from here be reintroduced into the ontology representation for further processing and to expand the original knowledge base. A case study is introduced to test the proposed method and to show how it can be used to estimate the characteristics of an already existing aircraft from basic requirements and configuration details. The results from the method and sizing are also compared with publicly available data for the reference aircraft to see how accurate the estimates were.

This work illustrates how a proposed method can be used to create optimization frameworks for early conceptual design studies and to increase overall knowledge at an early design stage. The method is intended to facilitate concept selection in challenging domains that typically involve multidisciplinary design problems with contradictory requirements. The main focus of the work presented here is on the conceptual design of helicopters; however, the method is intended to be applicable to early design studies in other domains as well. In short, statistics about existing helicopters are collected and compiled to provide a basis for various regression analyses. The purpose of this is to unravel relationships in the data and to obtain simple estimation models from statistical regressions that can be used in conjunction with existing formulas and equations to generate an initial helicopter design estimate. Models for each discipline, such as aerodynamics, are then created using the outcomes of the regression analyses and existing equations. Lastly, the method is used to define a multidisciplinary design optimization framework incorporating all the models obtained from the different disciplines. A case study based on search and rescue operations is used to test the proposed framework in order to obtain possible first suggestions for the baseline design of a new general-purpose search and rescue helicopter.