António Baptista

Abstract
The footwear industry, a sub-sector of textile industrial sector, faces increased pressures towards higher levels of sustainability and circularity along all the value chain. Along the last decades, shoe products have become more complex products, integrating a greater number of components, materials diversity and often long supply-chains related to cost reduction and production or sourcing delocalization strategies. Full value-chain digitalization, as a cornerstone of Industry 4.0 paradigm, plays a key role for leveraging more sustainable and circular products, namely by traceability operationalization and forthcoming instruments such as Digital Product Passport. This research studied, via a state-of-art framing of the challenges followed by qualitative approach, how Industry 4.0 technologies can support the development of new services that contribute to sustainable and circular practices in footwear companies. An interview-based survey was conducted to 6 footwear companies, to map the adoption level of Industry 4.0 technologies and cross-linking to circular services business models.

Abstract
The world faces unprecedented challenges related to the so-called Triple Planetary Crisis (climate changes, massive pollution, biodiversity losses). The Linear Economy model of development represents a very relevant cause for these crises effects, since it is anchored on the paradox of ever-growing natural resources extraction within a finite planet space and limited policy barriers for ecosystems degradation. Circular Economy emerges as a promising alternative development model, but it still urges for effective implementation. This work presents a novel De-Production model that combines, by design or redesign, the articulation of R-Strategies and D-Strategies across the product and production life cycles in order to unblock circular business models. It is proposed a systemic approach considering product circularity by means of activating R-Strategies, improving both production operations and de-production operations via value retention mindset. The model is tested via discrete simulation in a remanufacturing case study of a bicycle wheel assembly. © 2025 Elsevier B.V., All rights reserved.

Abstract
Water scarcity is currently a concerning problem and is likely to worsen in the future. To address this issue, it is essential that water used in human activities is treated before being reused or returned to nature. Wastewater is processed in wastewater treatment plants (WWTPs), which are complex structures that consume a considerable amount of resources and need to operate optimally. Many authors have proposed computational methodologies to optimize WWTPs, and each work has different approaches and characteristics, but most have in common the lack of concern with maximizing sustainability, in its broadest definition. Furthermore, even when sustainability is considered, it is typically addressed in an indirect or superficial manner, rather than being treated as a central objective. This paper provides a critical literature review of computational methodologies that, in some way, focus on improving the sustainability of WWTPs. Considering the target of the paper, this review aims to answer the following main questions: (1) What are the general objectives of the proposed works? (2) In which locations/phases of the treatment process are the proposed techniques applied? (3) What are the main methodologies and performance metrics used in the proposed techniques? The review identifies a strong focus on optimizing aeration in biological reactors, limited holistic and real-time optimization across WWTP stages, and sparse integration of sustainability metrics, especially for environmental and social impacts. Future research should prioritize the development of real-time, multi-objective optimization frameworks that encompass all WWTP stages and fully integrate economic, environmental, and social sustainability dimensions.

Abstract
To address the increasing complexity of product characteristics, demand fluctuations, and higher costs of raw materials, along with pressures for fast-er integration of decarbonized energy resources, manufacturing companies require flexible production systems. These systems should minimize waste, achieve faster cycle times, and deliver high-quality products to stay competitive. In this regard, Product Design-for-Excellence (DfX) principles have gained significant importance in recent years. DfX enables all management levels to perform quick and comprehensive design inputs and performance evaluations, leveraging product lifecycle management platforms. LeanDfX, a dedicated Lean approach for product development performance assessment, has been previously proposed. This work builds upon LeanDfX by presenting a multi-dimensional approach to support design and performance assessment of production systems throughout its lifecycle. This approach coherently integrates different production knowledge areas and strategic foundations (e.g., Lean Manufacturing, Strategic Aspects, Sustainability, and Circular Economy) for the effectiveness and efficiency evaluation of production systems. The research hypothesis revolves around the translational strategy of extending and transforming the LeanDfX methodology for application in production system design within factory operations. This new architecture is presented in the context of the European project RENEE, devoted to designing and deploying remanufacturing processes for a more sustainable, circular, and competitive industry.

Abstract
As the need for enhanced material performance continues to escalate in several sectors, addressing complex parameters such as economic feasibility, ease of manufacturing, and production volume, rises the need for multidomain decision-making tools. In order to explore and streamline this process, this study employed the novel Material Design-for-eXcellence methodology to investigate polymer material selection in aeronautical and power transformer components, using additive manufacturing. The study assessed the X's selected (mechanical, thermal, physical, cost, dielectric, and environmental) by assigning weights to these factors, and identifying the optimal materials for each application. In the aeronautical context, PEI+GF30 was chosen as the best solution, attaining an overall effectiveness of 79 %, primarily due to its exceptional mechanical characteristics. The use of a thermoplastic can lead to lighter components while ensuring the same technical performance, enabling longer flight duration. Conversely, in the energy sector for power transformers, PSU obtained a 78 % score, largely attributable to its outstanding dielectric properties. The application of additive methods on transformers' insulating parts leads to optimized channels for the mineral oil, enhancing its thermal and dielectric performance. The obtained results underscored the importance of tailored material selection approaches, adjusted to specific application requirements. The importance of comprehending and adapting to diverse contexts for effective material design and implementation is also highlighted.