During the early design stages of airframe components, many possible design architectures and production methods need to be traded to find the best configuration. Evaluating different production methods can be challenging as different production methods put different requirements on the product to be designed. This paper presents a new methodology that enables the inclusion of manufacturing and assembly in the design process. By extending the architectural design space model with components of the production system, the design choices regarding production are made explicit. Through the modeling of product and production requirements and assigning them a verification method, a dynamic MDAO workflow is formulated. Within a dynamic workflow, the design variables, analysis tools, and constraints change depending on the current design vector. The methodology has been applied to the design and manufacturing of a wing rib in which two manufacturing options were traded: metal machining and composite stamp forming. The dynamic MDAO workflow successfully found the Pareto front for both manufacturing methods. The main benefit is that only one workflow needed to be formulated and executed, whereas previously a separate MDAO workflow needed to be created for each combination of product design and production method. Overall, the newly presented methodology enables the optimization and trade-off between different production methods while ensuring the design complies with the production-specific requirements.@en

Including production considerations in the early design stages of aircraft structures is challenging. Production information is mostly known by experts and rarely formally documented such that it can be effectively used during the design process. Producibility is mostly considered after completing the design, resulting in increased cost and development time due to the late discovery of production issues. This paper presents a new model, called the Manufacturing Information Model (MIM), which supports the automatic inclusion of production considerations into the design process. The MIM provides a single source of truth and a generic structure to capture and organize production-related information in a product system. Furthermore, it provides compatibility analyses to automatically warn for or exclude infeasible designs. Analysis tools use the information stored within the MIM to calculate the mass, costs, and production rate of the product. To show the functionalities of the MIM, it has been applied to the conceptual design of a wing box at a Tier 1 company. This use case shows how the MIM supports trade-off decisions, as it allows for the identification of trends and the ranking of different manufacturing concepts. Overall, the MIM provides a structured and formal approach to include production information in the conceptual design, improving the decision-making process.@en

This paper discusses the approach for architecture design space optimization of aeronautical systems investigated in the DEFAINE project. In system architecture optimization problems, hierarchical relations between design variables may exist. This means that the quantity and type of some variables are dependent on the value of other variables. To address this challenge, a nested optimization strategy is proposed, where an outer loop deals with the independent design variables and an inner loop with the dependent ones. As the characteristics of the dependent variables may become known only during workflow execution, a dynamic workflow formulation approach is developed to introduce these variables into the MDAO workflow, automatically, during execution. The proposed methodology is implemented using a suite of technologies provided by partners of the DEFAINE consortium to enable formulation and execution of collaborative MDAO problems. This implementation is then applied to the design and optimization of the structural layout of a UAV aileron. The goal is to minimize the aileron mass, subjected to failure criteria constraints. In this use case, hierarchical relations between variables are present. The aileron skin is discretised into material zones, each one defined by a (dependent) design variable. The number of zones, hence the number of design variables, is not known a priori as it depends on the number and position of ribs and spars(both independent variables). A preliminary implementation of the proposed approach proved effective in dealing with the hierarchical mixed-integer design space. Trade off studies comparing different aileron architectures could be efficiently set up and executed. Some limitations in the implemented workflow management technology, however prevent performing a full nested architecture optimization. Therefore, to demonstrate the effectiveness of the proposed nested approach, a parallel study was conducted on the same aileron, using a less generic and manual implementation of the nested MDAO workflow. This second study successfully minimized the mass and cost of the aileron structure, thereby proving the merit of the proposed nested approach to address system architecture optimization. @en

During the aircraft conceptual design phase, many different design options need to be explored and compared in a short time frame. To speed up this process, efforts have been made in the past decades to digitalize parts of the design process, with a focus on the automation of the repetitive and non-creative tasks inherent to the iterative design process. Whilst many of the newly developed methodologies focus on specific parts of the design process, a holistic model-based design framework, incorporating the latest design technology developments, is lacking. To fill this gap, this paper presents the latest version of the Design and Engineering Engine (DEE) framework, originally proposed in the early 2000s and progressively matured through the experience of several international research collaborations. The DEE enables the setup and execution of Multidisciplinary Design Analysis and Optimization (MDAO) problems for aircraft (sub)systems, leveraging the automated, rule-based modeling capabilities offered by Knowledge-Based Engineering (KBE) and recent developments in the automatic formulation and integration of MDAO workflows. While the traditional MDAO process focuses on a given product architecture, the DEE allows also architectural design studies and makes use of Model-Based Systems Engineering (MBSE) principles to address the whole design process, from requirements modeling up to the automatic verification of the requirements. In practice, the DEE provides a single conceptual framework or template from which specific design framework instances can be formulated and executed, according to the user's needs. This paper describes the DEE architecture and its implementation concepts. Furthermore, it demonstrates the application of the DEE template to four different scenarios, ranging from a simple requirement verification study, up to the simultaneous synthesis and optimization of an aircraft system and its production process, including multiple system architecture options.@en

According to a study performed by the Project Management Institute, around 47% of unsuccessful projects do not meet their goals and objectives due to poor requirements management. Taking requirements into account during the aircraft design process and ensuring requirement compliance during all design phases is important to obtain good and feasible aircraft designs. However, a typical aircraft design process is very complex and many requirements need to be taken into account. This paper proposes a new framework that implements requirements in the design process by establishing a direct link between Model-Based Systems Engineering and Multidisciplinary Design Analysis and Optimization (MDAO). Model-based requirements are directly implemented in the optimization problem and based on the requirement verification methods the MDAO workflows are formulated. When requirements or verification methods change, the workflow is automatically updated accordingly. This way, requirement compliance can either be automatically enforced or checked based on the optimization or analysis results. Automatically generated requirement reports provide information on the requirement compliance results. The framework has been implemented in a software prototype, which was applied to the design of a wing box, showing the functionalities of the framework. With the framework, the traceability from requirements to product design is improved, as all stakeholders can see how the design process was formulated and how requirement compliance has been achieved. Furthermore, optimized designs can be obtained that satisfy all the stakeholders' needs.@en

Collaboration is a key enabler for the development of modern aircraft and its systems and components. Because of the highly complex and integrated nature of many aircraft systems, effective collaboration requires well-organized, multi-disciplinary, multi-engineer, and multi-organization development processes. These processes require data-driven and computer-supported tools and methodologies. Collaboration may seem as simple as working together, thereby adopting standards and tools, and freely sharing data, information, and knowledge. However, in the development of complex systems such as aircraft, collaboration is not that straightforward. For example, aircraft engineers across disciplines and organizations commonly face challenges such as firewalls, data and tool heterogeneity, and intellectual property protection. In this paper, we review the collaboration challenges, describe how the EU-funded research project AGILE 4.0 addresses these challenges, and detail the application of, and experiences with, AGILE 4.0’s collaboration-enabling technologies. @en

Most MDO problems currently do not include manufacturing as an optimization domain. Within the H2020 project AGILE 4.0 the intent is to bring manufacturing into the MDO domain using MBSE techniques developed within the project. To demonstrate how manufacturing can be brought into the MDO domain application cases are set up that resemble MDO problems from industry. In this paper, the MDO techniques will be used for the design of a Flap for a regional jet. The manufacturing aspect is represented by including the manufacturing cost of the flap in a Design Of Experiments (DOE). In this DOE different flap kinematic mechanisms and different flap sizes and paths are explored. The DOE is set up using the MDO toolset developed within AGILE 4.0. It allows for an automatic definition of the DOE workflow. The DOE results show that the choice of flap configuration has a significant effect on the Flap manufacturing cost, the flap wright and the landing performance of the aircraft. Next steps will be to investigate more flap configurations, improved the manufacturing cost model used and to set up a true flap optimization.

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