Purpose The layered construction inherent to additive manufacturing (AM) processes introduces unique challenges related to part geometry. This demands a better integration of knowledge during design to avoid the large number of design iterations. This paper aims to establish a framework for effectively delivering AM-related knowledge throughout the design process, particularly for designers who are not AM experts. Design/methodology/approach Two preliminary experiments were conducted to identify the types of AM knowledge that need to be transmitted and in what format, as well as the best time to integrate this knowledge into the design process. Accordingly, a six-phase knowledge transmission framework was developed to run in parallel with the design stages in a design for AM (DfAM) approach. This framework was then validated through three additional experiments. Findings The proposed framework enables a more informed design process by providing non-expert designers with relevant AM information. Its effectiveness was validated through experiments involving students with no prior AM knowledge, demonstrating improved design outcomes and reduced need for iterative rework. Originality/value This work stands out by proposing a sequence for providing information that is compatible with existing design methods. It offers a versatile approach that directly connects theoretical design methods with practical guidance, helping designers make more informed and effective decisions when designing for AM.

The reorganization required to implement the functional economy-a business model widely endorsed for promoting re-industrialization, re-shoring of businesses, better value distribution, and a local and circular economy-presents a significant challenge for companies. This service-based economy, which must be both social and sustainable, aims to enable businesses to decouple their economic growth from the sale of physical goods and, consequently, the depletion of natural resources. However, this shift often strains their financial stability. Feedback from various experiences reveals several issues, notably the difficulty of co-creating an offering that is profitable for all stakeholders. This contribution introduces a decision-making tool designed to assess different implementation scenarios of the service economy by comparing activities and risks assumed by each actor.

Additive manufacturing (AM) processes rely heavily on the geometric intricacies of parts being produced. Variations in the geometry of sequentially printed layers can introduce defects, arising from the complex interactions between geometry, process parameters, and materials. To mitigate these errors, it is critical to identify key geometric features and track their evolution in terms of both location and timing throughout the design and manufac- turing stages. This paper presents a novel method to describe shape in the context of AM, emphasizing the importance of layer-wise material deposition. Mereotopology, a framework for qualitatively describing the relationships between parts and wholes, is employed to pro- vide insights into the spatial, temporal, and spatio-temporal relationships inherent in AM processes. This formalism is particularly suited for shapes where precise dimensions may be indeterminate but where relational descriptions can still offer valuable information. The proposed theory integrates spatio-temporal evolution based on mereotopological principles and is applied to benchmark cases in AM. Additionally, a methodology for visualizing the generated descriptions is provided, along with a detailed case study. The paper concludes with a discussion on the strengths and limitations of this theory in comparison to existing approaches for describing four-dimensional objects.

Among the different stages of LCA (Life Cycle Assessment), the data reconciliation and modeling phase is identified as the most complex, time-consuming, and costly. Automation of this phase appears necessary today. Our objective is to propose a methodology for automatic data reconciliation by considering all possible reconciliation scenarios. Our approach involves analyzing automation methods from the literature. We propose data reconciliation through semantic analysis and the development of a cluster database (materials and processes) that serves as a bridge between the BoM (Bill of Material) and the environmental database. This proposal is then translated into a coded tool to automate the process. A case study was conducted involving different panels (novices and experts) to compare the choices and assumptions made in modeling an EEE (Electrical and Electronic Equipment) building component, both with and without the approach of selecting a similar material. This case study validates the proposed solution. This paper will present our research aimed at meeting the requirements of the EEE regulation in France by automating data reconciliation. This constitutes a practical and innovative solution for manufacturers while contributing to effective communication about the environmental performance of products.

Local authorities are tasked to manage mobility in their area of influence. They usually rely on mobility planning to define their long-term strategy to move towards more sustainable mobility. However, the integration of environmental issues into planning remains poorly addressed by scholars and a hindrance for local authorities. One reason highlighted by the literature is the lack of quantitative ex-ante evaluations of the plans. The proposition of the paper is a Quantitative Strategic Environmental Assessment model (QSEA) that helps define the local authorities’ strategy and validate the plan objectives.The QSEA model characterises residents’ mobility in all municipalities It assesses the cumulative distance travelled by cars and twenty environmental indicators relative to pollutant emissions and energy consumption, including indirect life cycle impacts. Moreover, the QSEA model: is based on accessible public data; reflects the density of the area; includes a description of the car fleet. The application to one representative French case (Metz Metropolis) highlights the sensitivity of distance travelled to periods of the week and density; the importance of indirect impacts due to energy supply and vehicles. This work is replicable to other metropolises while setting bases for longer term evaluations.Image, application 1Application 1

Many sustainable design approaches focus on preserving the value of the product when it reaches the end of its life and is assimilated to waste: functional recovery of the product or its modules, material recovery through recycling, or energy recovery. However, to ensure the highest levels of value preservation, another approach is to develop design strategies from end-of-life by reusing all or parts of the products into new ones.Artificial Intelligence (AI) introduces innovative solutions for circularity and waste management. Currently, design quality heavily relies on human expertise, modeling, and simulation tools. Our research explores the use of AI as an exchange tool between designers and end-of-life stakeholders to understand requirements, search for optimal solutions, and make informed decisions. As such, we aim to develop AI solutions tailored to different stages of the design process within a circular economy framework, focusing specifically on the design of products based on recovered second-life components.We aim to enhance circularity by using Generative AI for the structural and functional reuse of end-of-life products. For functional reuse, we propose a recommendation system using large language models (LLM), and for structural reuse, we propose creative design ideas using text-to-image models. Advanced technologies like Generative AI are crucial for effective product design and strengthening circular economy implementations.

The definition of the recycling and recyclability rates used today relies too heavily on the mass of the recycled materials, to the disadvantage of less dense materials such as polymers. In order to help with this issue, two indices have been created to, respectively, evaluate the retrievability of materials in their end-of-life stage and their reintegrability in new equipment once they have been recycled. These two indices comprise four indicators each, which are themselves divided into 23 sub-indicators. The six formal mathematical principles of the construction of these entities are presented, along with the formulas used for their calculation. Then, a case study is presented: the data of an equipment from a French EEE and sports and leisure distributor have been collected, and all sub-indicators, indicators and indices have been calculated for this equipment, hence assessing the retrievability and reintegrability of its constitutive materials. In conclusion, the precise nature of the indicators and sub-indicators has allowed us to give eco-design recommendations on different aspects of the design process, such as the choice of materials, the mechanical connections and modularity of the product, and its insertion into the waste treatment chain.

The Circular Economy (EC) model and the various R strategies have accelerated the recovery of electrical components from End of Life (EoL) products with the aim of minimizing the amount of waste and the use of new raw materials. Due to the higher degree of product complexity and the uncertainty and variability of the components to be disassembled, automation in this context is a challenging task. For robotic dismantling cell, computer vision solutions are mandatory to detect parts ranging from screws and small electrical components to the entire product. These vision systems provide data such as object location, classification, and tool suggestions, which are essential for implementing robots for disassembly tasks. This paper proposes a computer vision framework to form a screw detection and classification model with the least number of images for training the model. The location and the screw type are known, thus this model aims to check the presence of the screw in the specified location and then classify it to confirm the type of tool to be utilized for the removal process in the received EoL product to ease the integration of robots into disassembly. For both detection and classification, the YOLOv8 algorithm was used. As the model is product based, the dataset is also created for individual products by taking 10 pictures of each type of screw present in that particular product. A case study with an automotive electric motor and a power inverter was carried out to study the performance of the proposed methodology. The electric motor had Hex and Torx type screws and the power inverter had slotted hex type screws. The average precision of the two models was promising given the dataset is small providing the possibility of implementing a detection check system to support disassembly automation without the need for a huge dataset.

Local authorities have a strategic role in mitigating the environmental impacts of the transport sector. However, they struggle to integrate environmental issues into their decision-making processes, especially planning. In the European context of the Sustainable Urban Mobility Plan approach and Strategic Environmental Assessments (SEAs), this paper scrutinises three French localities to determine the current best practices and limitations for designing mobility plans and integrating environmental issues. Several limitations are identified: (1) limited expertise in defining and characterising actions and objectives, which complexifies plans' design, understanding, and monitoring; (2) a lack of a framework to conduct long-term quantitative environmental assessments and to use the results to influence decision effectively; and (3) monitoring processes are barely described in the documents, and the planning horizon where objectives are defined is not in sync with the indicators’ mandatory evaluation period. This French case study thus reveals that European planning practices must be further analysed and improved to deal with the rising environmental concerns, e.g. through an operational framework to design mobility plans with effective integration of environmental issues.

Power Electronics Converters (PEC) play a crucial role in the operation of many modern electrical systems and devices. Despite their widespread use, the lack of an efficient and cost-effective disassembly process can limit their repairability, refurbishability, remanufacturability and, ultimately, recyclability, thus hindering the circularity of products. In order to improve their circularity, it is important to assess their ease of disassembly. Therefore, this paper investigates the applicability of the “ease of Disassembly Metric” (eDiM), which is referenced in the material efficiency standards, Benelux repairability assessment method, and Repair Scoring System (RSS), to analyze the ease of disassembly of energy-related products. After identifying the limitations of the eDiM method, we refined and adapted it to make it more suitable for Printed Circuit Board (PCB)-based PEC, and thus propose a PCB-based disassemblability assessment method allowing the implementation of quantifiable requirements supporting their circularity. This standardized approach, at the PCB level, can improve the circularity of such products by facilitating design enhancements. With this approach, policymakers and designers can contribute more effectively to the transition to a circular economy in PCB electronics, particularly in the field of power electronics.

AbstractWhile innovation in waste treatment processes continue to advance, plastics are still often put aside in comparison to other materials. It is especially the case for WEEE-plastics: as they are included in complex equipment, their recovery is disregarded, in aid of critical metals and rare earths. The recycling of plastics is hindered by the low re-integration rate of these materials, due to concerns around their quality and their availability. Ecodesign of EEE thus seems to be a robust solution. This paper details two approaches to assess product design, by respectively evaluating the product recyclability and the implementation of predefined ecodesign guidelines. Based on these methods, the construction of a quality standard for recycled plastics in France is presented. The definition of the quality includes mechanical properties, but chemical, logistics, and regulatory aspects are also at stake. Eventually, ecodesign indexes and indicators are selected, and a method for their formal construction is proposed. The goal of this study is to provide ways to assess the overall quality and usability of recycled plastics, along with design for circularity methods to integrate them in new manufactured products.

AbstractResearch on additive manufacturing has highlighted methods and guidelines to optimise the design process and improving finished product quality. There is still room for improvement in making AM as reliable as more traditional processes when considering industrial use. In terms of manufacturing, managing print parameters properly can improve reproducibility and repeatability of a part, in addition to its fidelity to the basic geometric model. However, a topological optimised geometry requires more than good parameterisation. Efforts are therefore being made to formalise knowledge so that it is explicit and accessible to designers. This paper proposes an approach based on the spatio-temporal evolution of a geometry during printing to quantify data at the meso scale. Previous studies have been conducted on the description of features in time, space and space-time, and on the influence of their arrangement within a part. Building on this work, a parameterised test specimen was designed to measure the quantitative impact of these arrangements on the final product. The method is then presented and illustrated through a case study to help the designer with quantitative predictive values of geometric parameters.

AbstractThe current regulatory framework for Electrical and Electronic Equipment (EEE) is changing and now requires manufacturers to disclose the environmental performance of their products. This means that manufacturers must perform a life cycle analysis (LCA) on their entire range of products. An LCA is a recognized and standardized methodology for assessing the environmental impact of activities. However, communicating this information to consumers is challenging because it can be complicated.Despite this challenge, there is currently no common standard for communicating environmental information to consumers. The objective of this study is to explore the best practices for conveying environmental information. To achive this, a review of current environmental labeling approaches and recommendations available in the literature is conducted. Additionally, consumer requirements are collected and analyzed through a questionnaire that employs both quantitative and qualitative methods. The information collected is then used to develop the best practices for implementing environmental labeling for EEE.

Designing more circular products is essential to reaching Sustainable Development Goal 12, Responsible Consumption and Production, which is anticipated to be achieved by 2030. To achieve progress toward a circular economy in power electronics, discarded products, modules, or components must be recovered. This requires the implementation of End-of-Life (EoL) strategies. In order to maximize the high-value circularity efficiency of a power electronic product, EoL choices and constraints should be taken into account early on in the design phase. Since disassembly is a known bottleneck in EoL practices, design to enable disassembly is essential. Modularity enhances the product's reconfigurability and disassemblability, its reuse in other product families, as well as the product's maintenance, and serviceability. So, it is anticipated that this multiple life cycle thinking enabled by modularity would contribute to the transition towards more circular power electronic designs. Therefore, in this paper, we aim to consider modular designs of power electronic converters (PECs) and categorize them. As a result of a corresponding discussion about the existing PECs, we point out the general potentials to enhance circularity by modularity applied to PECs.

AbstractWithin the on-going ecological transition, mobility systems are considered as sociotechnical systems that raise several challenges for local authorities due to the different levels of decision, a complex stakeholder network and the numerous objectives to be dealt with. Designers are therefore seeking to develop new frameworks to support local authorities moving towards more sustainable mobility systems. Based on the French context, this study relies on an analysis of the regulation and an interview-based survey that depict the mobility design from the local authorities’ perspective. First, it investigates the objectives defined in the law and the difficulties met by local authorities. Then, it highlights the main political, organisational, and knowledge barriers for sustainable mobility. Finally, it proposes a set of recommendations to create a framework to better define and prioritise the objectives, ensure efficient planning and monitoring, clarify the interactions between actors, and enhance mobility plans.

Consequential Life Cycle Assessment (CLCA) can be particularly relevant for studying the changes proposed by new policies since they may result in important displacements of environmental, social and economic impacts. For example, the financial aids for encouraging the use of new technologies may increase the demand for some materials of which production is constrained and the marginal suppliers may be more impacting than the average ones. The goal of this project was to propose a method for calculating the potential environmental burdens and benefits from new policies in the construction sector. Consequential Life Cycle Inventory must include all processes that are actually affected by the studied changes, considering the market effects. The economic models can be helpful on this matter. The proposed method couples a Stock-Flow Consistent (SFC) to the CLCA methodology to obtain the flows and stocks that are affected by the new policy. The model goes further in order to obtain the second-order effects, i.e., the monetary redistribution effects resulting from an economic perturbation. The main result is a novel method that couples an SFC model to CLCA. It is tested in a case study where the evolution of carbon tax in France (economic shock) leads to an increase in thermal retrofitting works in the French existing built stock. These results may help the construction sector to anticipate important rebound effects that are not usually included in the current studies used for decision and policy-making.