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Decision-making is a core engineering design activity that conveys the engineer's knowledge and translates it into courses of action. Capturing this form of knowledge can reap potential benefits for the engineering teams and enhance development efficiency. Despite its clear value, traditional decision capture often requires a significant amount of effort and still falls short of capturing the necessary context for reuse. Model-based systems engineering (MBSE) can be a promising solution to address these challenges by embedding decisions directly within system models, which can reduce the capture workload while maintaining explicit links to requirements, behaviors, and architectural elements. This article discusses a lightweight framework for integrating decision capture into MBSE workflows by representing decision alternatives as system model slices. Using a simplified industry example from aircraft architecture, we discuss the main challenges associated with decision capture and propose preliminary solutions to address these challenges.

The engineering and maintenance in operational conditions (MOC) of a digital twin system (DTS) remains today a difficult, time-consuming, costly and resource-intensive task. This paper proposes a method to support the stakeholders involved in such activity. It combines the principles and processes of model-based systems and software engineering (MBSSE), is inspired by the pattern-based systems engineering (PBSE) approach and is in line with the recent norms and standardization. An application on a real use case of the method is presented to illustrate the practical benefits of this contribution.

CubeSat missions are increasingly adopted by NewSpace actors despite their limited resources and fast-paced development cycles, often leading to high failure rates. Traditional systems engineering standards such as ISO/IEC/IEEE 15288 and ECSS-E-ST-10C are rarely applied because they are considered too complex for very small entities (VSEs). This paper introduces the CubeSat systems engineering framework (CuSEF), a lightweight yet rigorous framework tailored for CubeSat class IV/V missions. CuSEF adapts ISO 29110 as a structural foundation and incorporates selected ECSS requirements to ensure mission reliability. The framework combines a simplified lifecycle model with model-based systems engineering (MBSE) practices and leverages artificial intelligence (AI) to accelerate tasks such as requirements drafting and test case generation. Early application of CuSEF demonstrates improvements in cost, schedule, and robustness without compromising agility. Future work includes large-scale validation across diverse CubeSat teams and enhanced integration of digital continuity and AI-driven design optimization.

This paper explores the benefits of developing a method to support and enable effective collaboration between organizations involved in complex and large-scale engineering projects, particularly focused on interoperability challenges that represent a classical stake to overcome in such collaborative contexts. The paper highlights particularly issues concerning the requested use of heterogeneous engineering languages, and respect of operational practices of project stakeholders and organizational habits. The goal is to outline the foundations of a method that facilitates seamless data, information, and knowledge exchange while preserving each organization's engineering culture. To do this, the emphasis is placed on the importance of specifying, and comparing organizational habits, practices, and languages, and then finding compromises.

Circular economy (CE) is widely promoted as a sustainable alternative to the traditional linear economy. However, its industrial implementation faces persistent challenges, notably due to the lack adaptability and holistic integration of the current solutions. This paper identifies eight major barriers to CE deployment, considering the products in their changing technical, social, and financial environment. While closed-loop supply chains have emerged as a partial solution to these barriers, they often fall short in addressing systemic complexity and dynamic adaptation needs. To overcome the remaining limitations, we propose the concept of regeneration ecosystems. These ecosystems aim to support the sustainable valorisation of product across multiple use phases, while considering social, environmental, and economic impacts. This paper highlights the properties of regeneration ecosystems and argues for their potential to enable an evolutive implementation of CE at the industrial level.

In most cases, over 80% of a system's cost is already committed during the preliminary design review (PDR) of the life cycle (Claxton 1993 and NASA 2017). Overruns often occur because requirements of certain stakeholders, such as those related to maintainability, are not involved in the system design process early enough. Consequently, a collaborative effort during the design stage should involve the requirements of key stakeholders and decision-makers. In this perspective, domain ontologies and the sharing of needs should facilitate a common agreement. Systems engineers are key stakeholders to guarantee the viability of the solution system. The integration of domain ontologies within a model-based systems engineering framework will enable the interconnection of the heterogeneous data needed to integrate maintenance issues into collaborative system design. Adding maintenance requirements earlier in the design process will help limit additional costs and delays.

Large amounts of heterogeneous data are generated, used and managed all along engineering projects. The concept of digital thread (DTH) is therefore evoked to assume digital continuity, consistency, and traceability of these data. To this purpose, this paper proposes an approach to address data, tool, and processes interoperability problems in the DTH.

The optimization of the system development process has long been a significant challenge. In the context of aircraft business class seats, the products are mechatronics systems as they incorporate diverse discipline-specific components (mechanical, electrical, and electronic). Therefore, their design, manufacturing, and V&V (verification and validation) are complex. The V&V phase typically occurs later in the development process, adhering to the V-model and ISO 15288 technical processes. However, ensuring system behavior testing early in the development process is essential to prevent extensive rework and physical prototyping iterations. This paper presents an innovative approach integrating virtual testing in the development process of mechatronics systems. This methodology is built upon the traditional V-model, enhanced by a parallel testing process using the digital twin concept. The digital twin architecture is designed following the model-based systems engineering (MBSE) approach.