Search Results (366)

Disassembly is a crucial step in the remanufacturing of end-of-life (EoL) electronic products. Disassembly depth refers to the disassembly stop point determined by the disassembly sequence. For the disassembly depth optimization of EoL electronic products, a feasibility model with a fast convergence and low mean squared error (MSE) is needed to improve optimization accuracy. However, the use of a backpropagation neural network (BPNN) model or mathematical model often results in a slow convergence and high MSE due to the randomness of the initial weights and biases. In this study, an improved method for the disassembly depth optimization of smartphones based on a Particle Swarm Optimization-BPNN (PSO-BPNN) predictive model is proposed. Compared with the traditional BPNN optimization method, the proposed method in this study is that the BPNN predictive model is optimized by using PSO, which shows a superior predictive performance and reduces the MSE. The case of ‘Huawei P7’ is used to verify the feasibility of the method. The results show that the method maintains disassembly profit while reducing the disassembly time and carbon emissions by 17.1% and 7.8%, respectively. Compared with the BPNN model, the PSO-BPNN model converges 18.6%, 32.8%, and 16.6% faster in predicting the disassembly time, profit, and carbon emissions, respectively, with MSE reductions of 92.95%, 96.51%, and 92.74%, respectively. Full article

Background/Objectives: End-of-life (EoL) experiences are critically important for everyone involved, giving rise to a set of needs that extend far beyond bio-physiological aspects, to encompass the spiritual dimension as the core of human beings. Understanding the processes of spiritual awakening (SA) assists palliative care professionals in enhancing the quality of care provided to individuals with life-threatening illnesses, as well as to their families. SA is a fundamental occurrence linked to the fulfilment of our spiritual needs when facing an existential crisis, such as the proximity of death. However, its conceptual boundaries need to be clarified to provide qualified and humanized palliative care. Therefore, this study aims to identify the key attributes, antecedents, consequents, and empirical referents of SA at EoL, as well as to clarify the concept’s existing ambiguities. Methods: Walker and Avant’s eight-step concept analysis was used. A literature search was conducted in May 2025 across three databases (PubMed, CINAHL and Scopus). Results: Following the review, 21 articles were included for analysis. The concept analysis revealed four main attribute domains: (1) sensory–perceptual domain; (2) affective/cognitive domain; (3) relational domain; and (4) transcendental domain. Moreover, spiritual consciousness and the existential matrix were antecedents to this concept; revaluation of beliefs, finding spiritual serenity and inner freedom, fostering spiritual growth, and the desire to leave a legacy were its consequences. Conclusions: The concept of SA at the EoL reveals itself to be a complex and multifactorial phenomenon, with a profound impact on a person’s confrontation with finitude. Recognizing and integrating SA into palliative care allows for a more comprehensive understanding of human consciousness. To deal with SA experiences in healthcare settings, a multifaceted approach is needed. This encompasses acknowledging spirituality as a determinant of health, including spiritual care in standard practice, and offering education and training on spiritual care competence for healthcare practitioners. Further transdisciplinary research should be undertaken to explore SA phenomenological variations, guide clinical interventions, and evaluate SA impacts on spiritual well-being and spiritual growth. Full article

Background/Objectives: The skin is a protective barrier against pathogens such as herpes simplex virus type 1 (HSV-1), which causes recurrent and highly prevalent skin infections worldwide. The increasing resistance of HSV-1 to conventional treatments has driven the search for new therapeutic alternatives. In this context, the essential oil of Lippia graveolens (EOL) has demonstrated promising antiviral activity; however, its high volatility limits direct skin application. To overcome this, polymeric nanoparticles (NPs) loaded with EOL were developed to improve its availability and antiviral efficacy. Methods: Nanoformulations were prepared by nanoprecipitation, and their antiviral activity against HSV-1 was evaluated using the plaque reduction assay. The effect of the nanoformulations on skin barrier integrity was assessed using an ex vivo porcine skin model and non-invasive techniques. Results: The NP-EOL exhibited physicochemical properties favorable for skin deposition, including a particle size around 200 nm, a polydispersity index of ≤ 0.2, and negative zeta potential. Moreover, NP-EOL showed 1.85-fold higher antiviral activity against HSV-1 compared with free EOL, while also reducing cytotoxicity in Vero cells. Conclusions: Results demonstrated that the NPs promoted skin hydration without altering pH or transepidermal water loss, suggesting they do not disrupt skin homeostasis. This study supports the potential of NP-based systems as effective topical delivery vehicles for EOL, representing a promising therapeutic alternative against HSV-1 skin infections. Full article

The growing volume of decommissioned wind turbine blades (WTBs) poses substantial challenges for end-of-life (EoL) material management, particularly within the composite repurposing and recycling strategies. This study investigates the repurposing of EoL WTB segments in a full-scale demonstrator for a photovoltaic (PV) floating platform. The design process is supported by a calibrated numerical model replicating the structure’s behaviour under representative operating conditions. The prototype reached Technology Readiness Level 6 (TRL 6) through laboratory-scale wave basin testing, under irregular wave conditions with heights up to 0.22 m. Structural assessment validates deformation limits and identifies critical zones using composite failure criteria. A comparison between two configurations underscores the importance of load continuity and effective load distribution. Additionally, a life cycle assessment (LCA) evaluates environmental impact of the repurposed solution. Results indicate that the demonstrator’s footprint is comparable to those of conventional PV-floating installations reported in the literature. Furthermore, overall sustainability can be significantly enhanced by reducing transport distances associated with repurposed components. The findings support the structural feasibility and environmental value of second-life applications for composite WTB segments, offering a circular and scalable pathway for their integration into aquatic infrastructures. Full article

Bioplastics are gaining attention as eco-friendly alternatives to conventional plastics, with Polybutylene Adipate Terephthalate (PBAT) emerging as a promising biodegradable substitute for polyethylene (PE) in food packaging. Commercial PBAT is often blended with other plastics or bio-based fillers to improve mechanical properties and reduce costs, though these additives can influence its environmental footprint. Therefore, this study quantifies the environmental impacts of producing PBAT resin blends reinforced with common inorganic fillers and compares end-of-life (EoL) performance against PE. While prior studies have largely assessed virgin PBAT or PBAT/Polylactic Acid (PLA) systems, systematic LCA of commercial-style PBAT blends with inorganic fillers and screening LCA level for comparisons of composting vs. landfill remain limited. The contributions of this study are to: (i) map gate-to-gate environmental hotspots for PBAT-blend conversion, (ii) provide a screening gate-to-grave comparison of PBAT composting vs. PE landfill using ReCiPe 2016 and IPCC GWP100 methods, and (iii) discuss theoretical implications for material substitution in the context of EoL strategies. The results indicated that producing 1 kg of PBAT blend generated a single score impact of 921 mPt with Human Health and Resource categories contributing similarly, and a GWP of 8.64 kg CO₂-eq, dominated by mixing and drying processes. EoL screening showed PBAT composting offered clear advantages over landfilling PE, yielding −53.9 mPt and 11.35 kg CO₂-eq savings, effectively offsetting production emissions. In contrast, landfilling PE resulted in 288.8 mPt and 2.2 kg CO₂-eq emissions. Sensitivity analysis further demonstrated that a 30% reduction in electricity use could decrease impacts by up to 10%, underscoring the importance of energy efficiency improvements and renewable energy adoption for sustainable PBAT development. Full article

Background/Objectives: Historically, humankind has consistently regarded death as an uncomfortable topic. Although death and dying are unescapable, they are frequently overlooked in formal education, as discussing or acknowledging them is believed to provoke emotional or psychological discomfort. To the best of our knowledge, little is known about the influence of the fear of death on the lives of university students. To fill this gap, this study aimed to examine the relationship between the concept of a good death, fear of death and self-compassion among university students in Portugal. Methods: This cross-sectional study was conducted in Portugal between November 2024 and January 2025 with 310 university students using an e-survey. Personal questionnaire and the Portuguese versions of the Good Death Concept Scale, the Collett-Lester Fear of Death Scale, and the Self-Compassion Scale were used. JAMOVI statistical software (version 2.7.6.) was used for descriptive analysis, independent sample t-tests, one-way ANOVA with post hoc analysis, and Pearson correlation analysis. To identify the factors associated with fear of death, a multiple linear regression analysis was conducted. This study adhered to the STROBE checklist for reporting. Results: A total of 310 students were included. The average age was 25 ± 8.52 years, and 75.2% were female. The total mean score for fear of death was 99.22 ± 21.97, indicating relatively low fear levels. However, health sciences students presented higher fear of death rates compared with non-health counterparts. Age and gender differences were also found, with female and younger students reporting significantly higher levels of fear of death (p < 0.01). The Pearson correlation matrix indicated that fear of death is positively correlated with the concept of a good death, while negatively correlated with self-compassion (p < 0.01). Key factors influencing fear of death include age, gender, closure and control domains, and the overidentification subscale (adjusted R-Squared valued [R2] = 0.352). Conclusions: The results suggest that students are often poorly prepared to deal with death-related issues (revealing fear) and with negative thoughts and feelings about mortality. In this vein, it is necessary to implement curricular educational interventions focusing on death education as well as actively involving students in compassionate community initiatives, increasing their awareness and self-confidence about EoL care. Full article

As the demand for more efficient energy storage solutions grows, emerging battery chemistries are being developed to complement or potentially replace conventional lithium-ion technologies. This review explores the circular economy potential of sodium (Na), magnesium (Mg), zinc (Zn), and aluminum (Al) battery systems as alternative post-lithium configurations. Through a comparative literature analysis, it identifies key barriers related to material complexity, recovery efficiency, and regulatory gaps, while highlighting opportunities for design improvements and policy alignment to enhance sustainability across battery life cycles. However, end-of-life (EoL) material recovery remains constrained by complex chemistries, low technology readiness levels, and fragmented regulatory frameworks. Embedding materials/battery design principles, transparent life cycle assessment (LCA) data (e.g., publishing LCAs in open repositories using a standard functional unit), and harmonized policy early could close material loops and transform the rising post-lithium battery stream into a circular-economy resource rather than a waste burden. Full article

Design for remanufacturing (DfRem) is a green design mode that ensures good remanufacturability at the end-of-life (EOL) of the product. However, the diversity of service environments and operating modes makes it difficult to generate accurate DfRem solutions for the smooth implementation of remanufacturing. Moreover, the historical remanufacturing process contains a great deal of information conducive to DfRem. It will greatly enhance the efficiency and accuracy of remanufacturing design by feeding effective remanufacturing information back into the product design process. Unfortunately, there is a lack of direct correlation between them, which prevents remanufacturing information from effectively guiding DfRem. To improve the accuracy of DfRem solutions and the utilization rate of remanufacturing information, an intelligent design method for product remanufacturing based on remanufacturing information reuse is proposed. Firstly, rough set theory (RST) is used to identify key remanufacturability demand, and the quality function development (QFD) is used to establish a relationship between remanufacturability demand and engineering characteristics, which can accurately obtain the design objectives. Then, the correlation between remanufacturability demand, remanufacturing information, and DfRem parameters is analyzed, and the ontology technology is applied to construct the DfRem knowledge by ingratiating remanufacturing information. In addition, case-based reasoning (CBR) is applied to search for design cases from DfRem knowledge that best match the design objectives, and gray relational analysis (GRA) is used to calculate the similarity between design knowledge. Finally, the feasibility of the method is verified by taking an ordinary lathe as an example. This method has been implemented as a DfRem interface application using Visual Studio 2022 and Microsoft SQL Server 2022, and the research results indicate that this design method can accurately generate a reasonable DfRem scheme. Full article

With the growing adoption of circular economy principles in manufacturing, efficient disassembly and reassembly of end-of-life (EOL) products has become a key challenge in smart factories. This paper addresses the Disassembly and Assembly Line Balancing Problem (DALBP), which involves scheduling robotic tasks across workstations while minimizing total operation time and accounting for directional switching time between disassembly and assembly phases. To solve this problem, we propose an improved reinforcement learning algorithm, IQ($\lambda$), which extends the classical Q($\lambda$) method by incorporating eligibility trace decay, a dynamic Action Table mechanism to handle non-conflicting parallel tasks, and switching-aware reward shaping to penalize inefficient task transitions. Compared with standard Q($\lambda$), these modifications enhance the algorithm’s global search capability, accelerate convergence, and improve solution quality in complex DALBP scenarios. While the current implementation does not deploy live IoT infrastructure, the architecture is modular and designed to support future extensions involving edge-cloud coordination, trust-aware optimization, and privacy-preserving learning in Industrial Internet of Things (IIoT) environments. Four real-world disassembly-assembly cases (flashlight, copier, battery, and hammer drill) are used to evaluate the algorithm’s effectiveness. Experimental results show that IQ($\lambda$) consistently outperforms traditional Q-learning, Q($\lambda$), and Sarsa in terms of solution quality, convergence speed, and robustness. Furthermore, ablation studies and sensitivity analysis confirm the importance of the algorithm’s core design components. This work provides a scalable and extensible framework for intelligent scheduling in cyber-physical manufacturing systems and lays a foundation for future integration with secure, IoT-connected environments. Full article

The problem of end-of-life (EoL) fibre-reinforced polymer (FRP) wind turbine blades (WTBs) poses a growing challenge due to the absence of an integrated circular value chain currently available on the market. A key barrier is the information gap between the EoL condition of WTB components and their second-life application requirements. This study addresses this question by focusing on the spar cap, which is an internal structural component with high repurposing potential. A framework has been developed to determine the as-received mechanical properties of spar caps from different EoL WTB models, targeting repurpose in the construction sector. The experimental programme encompasses fibre architecture assessment, calcination processes and mechanical tests in both longitudinal and transverse directions of three different WTB models. Results suggest that the spar caps appear to retain their strength and stiffness, with no evidence of degradation from previous service life. However, notable variation in properties is observed. To account for this, a prediction tool is proposed to estimate the as-received mechanical properties based on practically accessible parameters, thereby supporting decision-making. The results of this study contribute to enabling the repurposing of EoL spar cap beams from the wind energy sector for applications in the construction sector. Full article

In the pursuit of a circular economy, the substitution of conventional polymers with compostable materials such as polylactic acid (PLA) has emerged as a primary strategy. However, the environmental performance of these materials is highly dependent on the post-consumer system. Based on a systemic analysis methodology, this paper investigates this performance paradox. Using a compostable coffee capsule made from PLA as a case study, the research compares its designed, ideal end-of-life (EoL) pathway (industrial composting) with its probable real-world fate within existing waste management infrastructures (landfilling and recycling stream contamination). The analysis of these scenarios reveals a significant gap between the product’s intended function and its actual environmental impact, showing that in realistic contexts, intended benefits are often unrealized and negative outcomes may occur. This study yields results that can inform more robust and systemic sustainable design strategies, highlighting the need to align product design with real-world infrastructural capabilities. Full article

The growing concern about climate change and increased carbon emissions has promoted the electric vehicle market. Lithium-Ion Batteries (LIBs) are now the prevailing technology in electromobility, and large amounts will soon reach their end-of-life (EoL). Most counties have not designed sustainable reverse logistics networks to collect, remanufacture and recycle EoL electric vehicle batteries (EVBs). This study is focused on estimating the future EoL LIBs generation through dynamic material flow analysis using a three parameter Weibull distribution function under two scenarios for battery lifetime and then designing a reverse logistics network for the region of Attica (Greece), based on a generalizable modeling framework, to handle the discarded batteries up to 2040. The methodology considers three different battery handling strategies such as recycling, remanufacturing, and disposal. According to the estimated LIB waste generation in Attica, the designed network would annually manage between 5300 and 9600 tons of EoL EVBs by 2040. The optimal location for the collection and recycling centers considers fixed costs, processing costs, transportation costs, carbon emission tax and the number of EoL EVBs. The economic feasibility of the network is also examined through projected revenues from the sale of remanufactured batteries and recovered materials. The resulting discounted payback period ranges from 6.7 to 8.6 years, indicating strong financial viability. This research underscores the importance of circular economy principles and the management of EoL LIBs, which is a prerequisite for the sustainable promotion of the electric vehicle industry. Full article

Although the exponential increase in photovoltaic installations does contribute to mitigating climate change, it has posed the problem of photovoltaic (PV) residue. As PV panels contain strategic metals, their recovery has become a priority. This paper therefore employs a mesoporous carbon impregnated with P507 extractant as adsorbent to selectively recover gallium and indium from solutions simulating the leachate of end-of-life CIGS (Copper Indium Gallium Selenide) cells in a fixed-bed. The previous batch results obtained in our lab show that both metals can be selectively separated by simply adjusting the initial pH, with large adsorption capacities (44.97 mg/g for gallium and 34.24 mg/g for indium). The obtained breakthrough curves were fitted to the Thomas, Yan, Yoon, and HSDM (Homogeneous Surface Diffusion Model) models using a simulation program developed in Python 3.12 obtaining good results in all cases (R² > 0.9). The estimated parameters were used to predict the experimental breakthrough curve for a different experiment that had not been used for parameter estimation, being the best predictive results the obtained with the HSDM. This is logical, given that unlike the other three models, it is mechanistic. Full article

The recycling and remanufacturing of end-of-life (EoL) electric vehicle (EV) batteries are urgent challenges for a circular economy. Disassembly is crucial for handling EoL EV batteries due to their inherent uncertainties and instability. The human–robot collaborative disassembly of EV batteries as a semi-automated approach has been investigated and implemented to increase flexibility and productivity. Unscrewing is one of the primary operations in EV battery disassembly. This paper presents a new method for the robotic unfastening and collecting of screws, increasing disassembly efficiency and freeing human operators from dangerous, tedious, and repetitive work. The design inspiration for this method originated from how human operators unfasten and grasp screws when disassembling objects with an electric tool, along with the fusion of multimodal perception, such as vision and touch. A robotic disassembly system for screws is introduced, which involves a collaborative robot, an electric spindle, a screw collection device, a 3D camera, a six-axis force/torque sensor, and other components. The process of robotic unfastening and collecting screws is proposed by using position and force control. Experiments were carried out to validate the proposed method. The results demonstrate that the screws in EV batteries can be automatically identified, located, unfastened, and removed, indicating potential for the proposed method in the disassembly of EoL EV batteries. Full article

The rapid growth of electric vehicles (EVs) in the Jakarta Greater Area is expected to significantly increase the volume of end-of-life (EoL) batteries, necessitating an efficient and sustainable waste management system. This study designs a reverse logistics network that includes Collection Centers (CCs), a combined Remanufacturing and Recycling Center (RMC), and a Waste Disposal Center (WDC). Dealer clusters are identified using K-means clustering to determine the optimal CC locations. A deterministic mixed-integer linear programming (MILP) model is developed to minimize total costs. It comprises acquisition, transportation, processing, facility, and carbon tax components. The model yields a minimum total cost of IDR 1,236,435,000,187, with processing costs contributing the largest share (56.68%), followed by transportation (29.30%). The selected facilities include five CCs (CCA-1, CCE-2, CCK-3, CCM-4, and CCR-5), one RMC (RMC-1), and one WDC (WDC-1). Based on battery health, the batteries are classified into three categories: L1 (>80% health, suitable for remanufacturing), L2 (60–80%, suitable for recycling), and L3 (<60%, directed to disposal). L1 and L2 batteries are directed to RMC-1, while L3 batteries and solid waste are routed to WDC-1, totaling 1.029 tons. The results emphasize the need for improving processing efficiency and strategic facility placement to enhance the sustainability and cost-effectiveness of EoL battery management in urban EV ecosystems. Full article