The concept of a Systems of Systems (SoS) most often refers to independent technical artifacts that are linked occasionally and locally to provide a valuable service. While Information Technology supports these links, the SoS framework faces a persistent gap between user-centric approach (Who are SoS’ users? What do they expect from SoS? What experience do they get from their interactions with SoS?) and the alliance of suppliers delivering or operating the constituents of the system to engineer (Who provides the capabilities, resources, technical artifacts, or services?). This gap leads to suboptimal user experiences and hinders the generation of new feasible value propositions. To address this challenge, this paper sketches a conceptual model unifying two aspects of the SoS: the first one is relating to the user, the second one to the alliance of suppliers. Our model’s primary contribution is a representation of the SoS connecting a User-Centered System (UCS), which maps the user journey and its touchpoints to the supporting constituents of the technical SoS, and a Transactional System (Transystem), which refers to the alliance of independent suppliers establishing various types of transactions between themselves. Our model, which is closely related to enterprise architecture, uses Design Thinking as UCS backgrounds and Strategy Design as Transystem pillars. The ‘glue’ of the SoS proposed is based both on user interactions and transactions between suppliers. Our holistic representation enables the integration of outside professions into SoS design projects, such as product marketing and purchasing.

In the early stages of concurrent engineering, the ability to assess design change impact is fundamentally limited by the availability of expert knowledge. Knowledge-Based Engineering (KBE) provides structured approaches for the capture, formalization, management, and diffusion of knowledge within complex organizations. KBE has increasingly turned toward ontology-based methodologies, leveraging their robust framework for shared conceptualization and reasoning capabilities. Integrated with Model-Based Systems Engineering (MBSE), such Ontology-Based Engineering (OBE) methodologies provide the necessary infrastructure for knowledge-driven workflows in a Digital Engineering (DE) context. Such integration is critical for complex engineering sectors such as the aerospace industry. However, the traditional knowledge acquisition process is expert-centric and, consequently, resource-intensive. The digital transformation of the industry has led to an explosion of data volumes, and raised concerns toward statistical approaches. This study implements a hybrid knowledge acquisition method within the OBE framework and MBSE environment. Specifically, this method combines human expertise and interpretable machine learning techniques to formalize knowledge models and instantiate them with concrete design rules. Applied in a real-world use-case involving workload estimation, this paper aims to enhance cross-domain collaboration during the conceptual design phase of new aircrafts.

Complex services are often delivered by alliances of independent partners. The user judges the result as a single service, but the alliance is governed by separate authorities and rules. Engineering this kind of system raises a problem that systems engineering has not fully addressed: alliance design and service design tend to be developed by different communities, with no shared formal representation linking them. This paper proposes a conceptual model that represents both within a single notation. The model is expressed as a SysML Block Definition Diagram organized in three interacting domains: user activity, user-centered system, and transactional system. A complementary state machine represents the lifecycle of the transactional system, with states drawn from ISO 44001:2017. The model is illustrated on the Rolls-Royce TotalCare program in commercial aerospace.

The increasing complexity of the aerospace industry has highlighted the necessity to fathom the entire product lifecycle. From initial conceptualization, engineers are meant to consider the production, maintenance, and decommissioning phases of an aircraft. By identifying how design decisions made in the conceptual phase impact the other systems involved, overall development time, costs, and quality can be significantly improved. Over the past decades, digital models have been employed in the design of complex systems, the management of data integration, and the formalization of domain knowledge. This paper examines the application of an ontology-based engineering methodology to support early concurrent engineering driven by knowledge. Copyright (c) 2025 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Early concurrent engineering necessitates a high degree of knowledge to assess the impact of design decisions. Part of Knowledge-Based Engineering (KBE), recent methodologies employing ontologies have gained more interest over the past years due to their shared conceptualizations, knowledge representations, and reasoning capabilities. Merged with Model-Based Systems Engineering (MBSE) activities, they enable knowledge-based systems to be seamlessly integrated within Industry 4.0. The incorporation of KBE within MBSE is of major importance in complex engineering sectors with an increasingly competitive market, such as the aerospace industry. This paper leverages the application of a hybrid knowledge extraction approach to support cross-domain collaboration during the conceptual design phase of a new aircraft.

The increasing complexity of the aerospace industry has highlighted the need to anticipate issues from the entire lifecycle of aircrafts. Identified too late, issues originating from the manufacturing or the maintenance phases can have considerable consequences on the overall development costs, time and quality of aircraft development. Concurrent Engineering (CE) is an approach that aims to improve the design process of a system by considering all lifecycle phases from the initial conceptualization. However, this way of working demands a high degree of collaboration and extensive knowledge sharing among the involved stakeholders. The digitization of the industry has provided new opportunities addressing such challenges. Approaches based on Model-Based Systems Engineering (MBSE), Knowledge-Based Engineering (KBE) and Artificial Intelligence (AI) are providing compelling ways to foster cross-domain collaboration while incorporating knowledge supporting design decisions. This paper leverages an ontology-based digital thread framework as a bridge between aircraft and manufacturing engineering activities. With enriched insights and global perspectives, this framework aims to enable early cross-domain trade-offs analysis to support knowledge-driven concurrent and collaborative engineering during the conceptual design phase.

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.

The traditional sequential aircraft design process is reaching its limits in an increasingly complex environment. Therefore, it has become an industrial necessity to implement radical change in working methods. This paper focuses on the conceptual design phase, where concurrent engineering offers the greatest potential to improve the costs, quality, and development time of a new aircraft. It pays particular attention to the knowledge management and modeling activities used to provide global perspectives that are inherently lacking in early phases. A digital thread framework is presented linking model-based systems engineering artifacts from product and manufacturing systems, coupled with knowledge capture methods. This framework aims to enable early trade-off analysis to support concurrent engineering during the conceptual design phase. Copyright (c) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

To deal with environmental, economic and social problems linked to high consumption and intense manufacturing, Europe, ecological associations propose scenarios for the implementation of the circular economy, without saying how to implement them. Several circular strategies (CS) (reuse, remanufacturing, recycling...) enable to regenerate a product and its components throughout its life cycle. Currently, these CS are not implemented in a systemic way, but in a punctual and individual way. The objective is to deepen the knowledge of the global implementation of several CS. To achieve this, the paper proposes to characterise each CS according to the requirements of the entering and leaving products. This technical characterisation allows us to analyse their complementarities and interactions. This characterisation will be illustrated by the example of remanufacturing and resynthesis. Then, an analysis of our proposal is carried out to show the contributions in order to have a holistic approach of the regeneration.

L’industrie 4.0 pose de nouvelles problématiques de recherche qui doivent être abordées également en enseignement. Dans ce contexte, il est nécessaire de sensibiliser les étudiants à ces problématiques via des plateformes intégrant les derniers concepts abordés en recherche et aux dernières technologies aussi proches que possible de la réalité industrielle voire en avance de phase. Les problématiques traitées via cette plateforme portent sur le développement durable, plus particulièrement de régénération et l’utilisation des technologies de l’industrie 4.0. L’objectif de ce papier est de présenter d’une part une plateforme nommée ProGreSS 4.0 en cours de réalisation et d’autre part de montrer le transfert des travaux de recherche en enseignement. Cette plateforme est basée à l’AIP de Lorraine et elle est réalisée conjointement entre les ingénieurs du CRAN et de l’AIPL.

Safety validation of Autonomous Vehicles (AV) requires simulation. Automotive manufacturers need to generate scenarios used during this simulation-based validation process. Several approaches have been proposed to master scenario generation. However, none have proposed a method to measure the potential hazardousness of the scenarios with regard to the performance limitations of AV. In other words, there is no method offering a metric to guide the search for potentially critical scenarios within the infinite space of scenarios. However, designers have knowledge of the functional limitations of AV components depending on the situations encountered. The more sensitive the AV is to a situation, the more safety experts consider it to be critical. In this paper, we present a new method to help estimate the sensitivity of AV to logical situations and events before their use for the generation of concrete scenarios submitted to simulators. We propose a characterization of the inputs used for sensitivity analysis (definition of the context of the automation function, generation of functional and logical situations with their associated events). We then propose an approach to set up a distribution function that will make it possible to select situations and events according to their importance in terms of sensitivity. We illustrate this approach by implementing it on the Traffic Jam Chauffeur (TJC) function. Finally, we compare the obtained sensitivity rank with expert judgment to demonstrate its relevance. This approach has been shown to be a promising method to guide the search for potentially hazardous scenarios that are relevant to the simulation-based safety validation process for AV.

Circular economy enables to restore product value at the end of life i.e. when no longer used or damaged. Thus, the product life cycle is extended and this economy permits to reduce waste increase and resources rarefaction. There are several revaluation options (reuse, remanufacturing, recycling, …). So, decision makers need to assess these options to determine which is the best decision. Thus, we will present a study about an End-Of-Life (EoL) decision making which aims to facilitate the industrialization of circular economy. For this, it is essential to consider all variables and parameters impacting the decision of the product trajectory. A first part of the work proposes to identify the variables and parameters impacting the decision making. A second part proposes an assessment approach based on a modeling by Generalized Colored Stochastic Petri Net (GCSPN) and on a Monte-Carlo simulation. The approach developed is tested on an industrial example from the literature to analyze the efficiency and effectiveness of the model. This first application showed the feasibility of the approach, and also the limits of the GCSPN modelling.

Requirements engineering is a critical activity in developing complex cyber-physical systems. Requirements are usually expressed using natural language, which may be ambiguous, inconsistent, or incomplete. These issues in requirements qualities may introduce errors in system design that lead to high project cost overruns. Hence it is essential to verify the qualities of requirements early. Since formal methods have demonstrated their ability to verify system designs and are increasingly adopted to support requirements engineering for software systems, a question arises about adapting formal methods to account for specific properties of cyber-physical systems. Even if there are many literature reviews concerning requirements engineering, there is a lack of a global view on the reviews that specifically address the issues related to validation and verification (V&V) of requirements. This paper aims to provide an overview of literature reviews related to requirements V&V and mainly investigates the use of formal approaches and models for preventing, detecting, or correcting errors occurring in requirements and identifies the main challenges of adopting formal methods on requirements engineering for cyber-physical systems. Copyright (C) 2022 The Authors.

Regeneration is the process restoring value to a product at the end of life, i.e. no longer used or damaged. We present a study on the evaluation of the regeneration level which aims to facilitate the regeneration industrialization. For this, it is essential to consider the health state of the product to be regenerated and to propose an evaluation method. A first part of the work proposes to identify the variables that allow to quantify the health state. A second part proposes an assessment approach based on a modeling by generalized colored stochastic Petri Net (GCSPN) and on a Monte Carlo simulation. The approach developed is tested on an industrial example from the literature to analyze the efficiency and effectiveness of the model.

In a working situation on an automated assembly machine, technical drifts during operation can lead to machine dysfunctions.These dysfunctions may cause the operator supervising the machine to adapt and respond to reduce the effect of these technical drifts on the rest of the working situation.To respond to these dysfunctions the operator may expose him or herself to hazards and thus be in a hazardous situation.(Lamy & Perrin, 2020) showed the feasibility of identifying this kind of potentially hazardous situation by observing the working situation.Here, we propose a method called Working Situation Health Monitoring (WSHM).The goal of this method is to identify these potentially hazardous situations by analyzing the potential drift of working situations and monitor the advent of potentially hazardous situations using equipment and production data.It consists of three steps: firstly, we model the working situation studied to characterize the nominal working situation; secondly, we analyze cause-and-effect relationships between potential process drifts, potential operator responses and potentially hazardous situations; and thirdly, we construct a health indicator of the working situation based on knowledge of potentially hazardous situations identified in the second step and by equipment data.This paper also presents the application of the method to a case study (an educational automated assembly machine).