Search Results (38)

Product innovation for remanufacturing, beginning at the development stage, has become an important strategic decision in third-party remanufacturing. This study investigates decision-making on product innovation for remanufacturing under two third-party remanufacturing modes and examines how original equipment manufacturers (OEMs) and remanufacturers respond. Results show that outsourcing remanufacturing consistently offers a wider profitability range for the OEM and increases the likelihood of the remanufacturer adopting a full remanufacturing strategy. Furthermore, a higher innovation level enhances OEM profits, particularly when the remanufacturing industry is mature or when the innovation investment efficiency is high. Otherwise, incremental innovation is more beneficial. Innovation also lowers entry barriers for remanufacturers. Finally, the authorization remanufacturing is initially more environmentally friendly, whereas the outsourcing mode becomes superior as the innovation level increases. Full article

This paper tackles the challenge of disassembly sequence planning (DSP) in energy-efficient remanufacturing by introducing an innovative hybrid optimization framework. The proposed model integrates a Dynamic Time-Varying CRITIC–Entropy (DTVCE) decision-making framework with an Improved Honey Badger Algorithm (IHBA) to optimize disassembly sequences under key operational criteria, including idle rate, line smoothness, and energy consumption. The DTVCE framework constructs a dynamic composite score by normalizing evaluation criteria across time slices and incorporating temporal discounting to capture the evolving importance of each factor. Meanwhile, by establishing a symmetric disassembly constraint matrix to restrict the disassembly sequence and integrating exploration and exploitation mechanisms to enhance the IHBA, the solution process is empowered to efficiently generate feasible disassembly sequences and fulfill task allocation across workstations while satisfying takt time constraints. Experimental validation demonstrates that the proposed framework significantly outperforms traditional disassembly optimization approaches in both energy efficiency and line balance performance. In a case study involving an automotive drive axle, the method achieved a near-optimal configuration using only eight workstations, leading to a marked reduction in both energy consumption and idle times. Sensitivity analysis further verifies the model’s robustness, showing stable convergence and consistent performance under varying takt times and energy parameters. Overall, this study contributes to the advancement of green remanufacturing by offering a scalable, data-driven, and adaptive solution to disassembly optimization—paving the way toward sustainable and energy-aware production environments. Full article

Tertiary buildings, characterized by temporary uses and frequent renovations of internal spaces, present some criticalities in terms of the consumption of materials that quickly become waste, despite their high residual value, not exploited for further use. The goal of rethinking the life cycle of building products, and related construction systems, enabling multiple cycles of use and extending the life span of the products, presupposes new Organizational Models and changes throughout the whole building process. This paper presents two Pilot Projects (developed within Re-NetTA research), which experiment with innovative Organizational Models and disassembly construction solutions in the tertiary building sector with the goal of extending the life cycle of materials and products through reusing and remanufacturing. The Pilot Projects involve two key operators: a manufacturer and a Third Sector organization. The paper highlights the fundamental key role of digital technologies by analyzing the following: (i) the development of virtual models to understand the technical feasibility for disassembly and to foresee reuse and remanufacturing scenarios; and (ii) the use of digital twin, augmented reality, and web-based platforms as a support tools, to put the products on a virtual market to reach customers before the activities of remanufacturing. Finally, the enabling conditions for improving circularity are discussed in terms of design process, environmental and economic sustainability assessment, and operator networking. Full article

This review article examines the role of additive manufacturing (AM) in increasing energy efficiency and sustainability within the evolving framework of Industry 5.0 and 6.0. This review highlights the unique ability of additive manufacturing to deliver mass-customized products while minimizing material waste and reducing energy consumption. The integration of smart technologies such as AI and IoT is explored to optimize AM processes and support decentralized, on-demand manufacturing. Thisarticle discusses different AM techniques and materials from an environmental and life-cycle perspective, identifying key benefits and constraints. This review also examines the potential of AM to support circular economy practices through local repair, remanufacturing, and material recycling. The net energy efficiency of AM depends on the type of process, part complexity, and production scale, but the energy savings per component can be significant if implemented strategically.AM significantly improves energy efficiency in certain manufacturing contexts, often reducing energy consumption by 25–50% compared to traditional subtractive methods. The results emphasize the importance of innovation in both hardware and software to overcome current energy and sustainability challenges. This review highlights AM as a key tool in achieving a human-centric, intelligent, and ecological manufacturing paradigm. Full article

With the sharp increase in the number of products and the development of the remanufacturing industry, disassembly lines have become the mainstream recycling method. In view of the insufficient research on the layout of multi-form disassembly lines and human factors, we previously proposed a linear-U-shaped hybrid layout considering the constraints of employee posture and a Duel-DQN algorithm assisted by Large Language Model (LLM). However, there is still room for improvement in the utilization efficiency of workstations. Based on this previous work, this study proposes an innovative layout of U-shaped and circular disassembly lines and retains the constraints of employee posture. The LLM is instruction-fine-tuned using the Quantized Low-Rank Adaptation (QLoRA) technique to improve the accuracy of disassembly sequence generation, and the Dueling Deep Q-Network(Duel-DQN) algorithm is reconstructed to maximize profits under posture constraints. Experiments show that in the more complex layout of U-shaped and circular disassembly lines, the iterative efficiency of this method can still be increased by about 26% compared with the traditional Duel-DQN, and the profit is close to the optimal solution of the traditional CPLEX solver, verifying the feasibility of this algorithm in complex scenarios. This study further optimizes the layout problem of multi-form disassembly lines and provides an innovative solution that takes into account both human factors and computational efficiency, which has important theoretical and practical significance. Full article

The remanufacturing of end-of-life products is an effective approach to alleviating resource shortages, environmental pollution, and global warming. As the initial step in the remanufacturing process, the quality and efficiency of disassembly have a decisive impact on the entire workflow. However, the complexity of product structures poses numerous challenges to practical disassembly operations. These challenges include not only conventional precedence constraints among disassembly tasks but also sequential dependencies, where interference between tasks due to their execution order can prolong operation times and complicate the formulation of disassembly plans. Additionally, the inherent uncertainties in the disassembly process further affect the practical applicability of disassembly plans. Therefore, developing reliable disassembly plans must fully consider both sequential dependencies and uncertainties. To this end, this paper employs a chance-constrained programming model to characterise uncertain information and constructs a multi-objective sequence-dependent disassembly line balancing (MO-SDDLB) problem model under uncertain environments. The model aims to minimise the hazard index, workstation time variance, and energy consumption, achieving a multi-dimensional optimisation of the disassembly process. To efficiently solve this problem, this paper designs an innovative multi-objective adaptive large neighbourhood search (MO-ALNS) algorithm. The algorithm integrates three destruction and repair operators, combined with simulated annealing, roulette wheel selection, and local search strategies, significantly enhancing solution efficiency and quality. Practical disassembly experiments on a lithium-ion battery validate the effectiveness of the proposed model and algorithm. Moreover, the proposed MO-ALNS demonstrated a superior performance compared to other state-of-the-art methods. On average, against the best competitor results, MO-ALNS improved the number of Pareto solutions (NPS) by approximately 21%, reduced the inverted generational distance (IGD) by about 21%, and increased the hypervolume (HV) by nearly 8%. Furthermore, MO-ALNS exhibited a superior stability, providing a practical and feasible solution for disassembly optimisation. Full article

On 14 June 2023, the European Parliament adopted Regulation (EU) 2023/1230 on machinery, which entered into force on 19 July 2023 (with some exceptions as per art. 54, according to a corrigendum issued to address a clerical error as regards the application dates in the original version) and shall apply from 20 January 2027, replacing the Machinery Directive 2006/42/EC. The main innovations/differences introduced by the Machinery Regulation (MR) compared to the Machinery Directive (MD) are critically analysed here, with a focus on sustainability issues. Some of these issues are covered by several international standards (such as BS 8887, ISO 10987 or DIN 91472), which also define the criteria and requirements for the remanufacturing process, although some technical gaps remain. Using the example of agricultural machinery, this paper proposes a methodology for determining the areas of acceptability for remanufactured products: these are expressed in terms of structural performance (e.g., the number of cycles ahead to failure expressed as the mutual of damage $1-D=0.625$) and the functional and safety requirements of the original machine. In this way, the issue of “substantial modification of machinery” is explored in terms of the safety obligations that the remanufactured machinery must fulfil. The paper is therefore a contribution to circular design by providing general criteria for the extension of the service life of machinery while at the same time considering safety issues. Full article

To improve the detachability performance and remanufacturing capability of existing agricultural micro-tillers, a modular design concept is introduced into the product design and development process, with Axiomatic Design (AD) and the Design Structure Matrix (DSM) serving as the methodological guidance and theoretical framework. In the design process, “Z-mapping” is used to reconstruct the demand/function/structure of the agricultural micro-tiller, decompose the total functions step by step, and establish a design matrix to transform the initial user requirements into specific functional indicators and design parameters. Geometric correlation is used as the design evaluation index to assign values to the matrix to establish a DSM for the correlations between agricultural micro-tiller design parameters. Using system clustering to optimize the distribution of matrix values, a total of five functional modules were identified to achieve a modular design scheme and design a prototype for agricultural micro-tillers. This design solution has significantly better disassembly performance than existing products, effectively enhancing the remanufacturing capability of existing equipment, proving the effectiveness of the Kano-AD-DSM-based design strategy, and providing a new theoretical reference for the innovative design of other small agricultural equipment. Full article

The evolving landscape of industrial manufacturing is increasingly embracing automation within smart factories. However, the critical role of human operators, particularly in manual assembly and disassembly tasks, remains undiminished. This paper explores the complexities arising from mass customization and remanufacturing, which significantly enhance the intricacy of these manual tasks. Human involvement is essential in these tasks due to their complexity, necessitating a structured learning process to enhance efficiency and mitigate the learning–forgetting cycle. This study focuses on the utilization of virtual reality (VR) as an innovative training tool to address these challenges. By conducting a systematic literature review (SLR) on the impact of VR on training operators for assembly and disassembly tasks, this paper evaluates the current level of VR application, the used technologies, the operator performance, and the VR benefits and limitations. The analysis reveals a limited but promising application of VR in training, highlighting its potential to improve learning outcomes, productivity, and safety while reducing costs. However, the research also identifies gaps in the practical application of VR for training purposes suggesting a future research agenda to explore its full potential. Full article

The use of a circular economy (CE) in a supply chain is conducive to remanufacturing. It can not only make the supply chain innovative but can also further ease resource consumption and lower pollution, thereby reducing carbon emissions. However, most current research remains focused on the concept of integrating circular economy supply chains (CESCs); few studies have carried out practical research in industry, and research addressing issues regarding the rubber recycling industry is even rarer. Therefore, this study refined the existing framework by screening out key factors that a CESC applies to remanufacturing products. This study conducted an expert questionnaire survey using the FDM to select key factors. Since the 30 respondents selected for this study are all experts in related fields, the reliability and stability of the method and results can be ensured. Meanwhile, this study adopted the fuzzy DEMATEL method to rank the importance of the five selected aspects and nineteen criteria and clarified cause-and-effect relationships between the criteria. The results show that important aspects, including “the circular business model” and “enhancing the resource value in the supply chain”, are both classified as cause groups; there are four main criteria that need to be highlighted, namely, “optimizing the production process”, “effectively tracking and recycling products”, “redesigning remanufactured rubber products”, and “improving resource efficiency”. Therefore, when related industries build CESCs to manufacture remanufactured products, these criteria need to be considered first. This study combined a CESC with remanufactured products, constructed a new framework to expand the related literature, and further analyzed the rubber industry and the underlying rubber recycling industry. Accordingly, related industries can refer to the new framework and key factors to develop production strategies for remanufactured products when implementing a CESC. Full article

Innovative technological solutions have become increasingly critical in addressing the transportation sector’s environmental impact. Passenger vehicles present an opportunity to introduce novel drivetrain solutions that can quickly penetrate the electric vehicle market due to their shorter development time and lifetime compared to commercial vehicles. As environmental policy pressure increases and customers demand more sustainable products, shifting from a linear business approach to a circular economy model is in prospect. The new generation of economically competitive machines must be designed with a restorative intention, considering future reuse, refurbishment, remanufacture, and recycling possibilities. This review investigates the market penetration possibilities of permanent magnet-assisted synchronous reluctance machines for mini and small-segment electric vehicles, considering the urban environment and sustainability aspects of the circular economy model. When making changes to the materials used in an electric machine, it is crucial to evaluate their potential impact on efficiency while keeping the environmental impact of those materials in mind. The indirect ecological effect of the vehicle’s use phase may outweigh the reduction in manufacturing and recycling at its end-of-life. Therefore, thoroughly analysing the materials used in the design process is necessary to ensure maximum efficiency while minimising the environmental impact. Full article

The manufacturing industry often faces challenges related to customer satisfaction, system degradation, product sustainability, inventory, and operation management. If not addressed, these challenges can be substantially harmful and costly for the sustainability of manufacturing plants. Paradigms, e.g., Industry 4.0 and smart manufacturing, provide effective and innovative solutions, aiming at managing manufacturing operations, and controlling the quality of completed goods offered to the customers. Aiming at that end, this paper endeavors to mitigate the described challenges in a multi-stage degrading manufacturing/remanufacturing system through the implementation of an intelligent machine learning-based decision-making mechanism. To carry out decision-making, reinforcement learning is coupled with lean green manufacturing. The scope of this implementation is the creation of a smart lean and sustainable production environment that has a minimal environmental impact. Considering the latter, this effort is made to reduce material consumption and extend the lifecycle of manufactured products using pull production, predictive maintenance, and circular economy strategies. To validate this, a well-defined experimental analysis meticulously investigates the behavior and performance of the proposed mechanism. Results obtained by this analysis support the presented reinforcement learning/ad hoc control mechanism’s capability and competence achieving both high system sustainability and enhanced material reuse. Full article

Younger and highly skilled generations are one of the major driving forces of a successful transformation to a circular economy (CE); therefore, this paper intends to assess the prevalent behaviour, attitudes, and knowledge of the CE by university students. The study focuses specifically on Portuguese students. Some new conclusions were added to the existent literature. Our conclusions show that, although students engage in several types of CE behaviour and have positive attitudes, these mostly include actions such as reducing food waste, recycling practices, or purchasing energy-efficient products. Circular consumption habits like remanufactured products, second-hand purchases, the sharing economy, and product-as-a-service systems (PSSs) still need further implementation. However, we determine that the level of knowledge of the CE goes beyond the conventional recycling premise. Moreover, we have included an innovative part, based on a probit model, by studying how knowledge of the CE affects students’ behaviour and attitudes and conclude that it positively influences them. Other variables such as age, gender, and level of education are also found to influence actions and attitudes. As a result, this study can significantly improve the overview of the current situation and provide a starting point for measuring the effectiveness of future policies to be defined. Full article

The building sector is a major contributor to global resource consumption and waste generation. The circular economy (CE) concept offers a promising alternative to the traditional linear economy by promoting the reuse, remanufacture, repair, and recycling of materials and products. However, the adoption of CE in the building sector faces several barriers. This paper presents a systematic literature review utilising the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach, focusing on the barriers and enablers influencing the adoption of the CE concept in the building sector. Drawing from an analysis of numerous papers published between 2008 and 2023, we identified a high number of barriers and enablers that delay the integration of CE. The barriers were categorised into six categories: awareness, technical, economic and market, implementation, support/promotion, and social. The paper also discusses the interdependence of the identified barriers, using a co-occurrence matrix. The study findings indicate lack of CE regulations, fragment supply chain, and high upfront investment cost as major barriers to the implementation of CE in the building sector. Based on the study results, stringent governance and legislation, financial incentives, and the development of technology and innovation for circular building tools are critical factors for the successful implementation of CE principles. The results of this study provide a comprehensive overview of the feasibility to CE adoption in the building sector, which could also help to develop strategies to accelerate the transition to an integrated CE. Full article