Search Results (90)

China’s steel decarbonization is a key sustainability challenge because cleaner production routes must be evaluated not only by their mitigation potential, but also by their implications for industrial continuity, cost affordability, resource security, and transition manageability. This study develops a national-scale soft-linked sustainability assessment framework that translates policy-conditioned macro signals into a multi-period, multi-objective optimization model of steelmaking-route transition from 2025 to 2050. Three policy environments are examined: carbon-control pressure, electricity-cost support for electrified routes, and their combined application. The model evaluates route portfolios by cumulative system cost, emissions, and transition adjustment intensity, linking mitigation with affordability and implementation feasibility. Results show that policy environments do not shift pathways uniformly; instead, they reshape the feasible trade-off frontier and alter which route combinations emerge as plausible compromise solutions. Across scenarios, scrap-based electric arc furnace steelmaking (Scrap-EAF) becomes the central medium-term route, while blast furnace–basic oxygen furnace steelmaking (BF-BOF) contracts but remains residual. Hydrogen-based direct reduced iron–electric arc furnace steelmaking (H₂-DRI-EAF) expands under favorable conditions, but does not become dominant by 2050 under the baseline national-scale parameterization. Overall, this study contributes to sustainability-oriented industrial transition analysis by showing how policy-conditioned environments reshape route feasibility, transition sequencing, affordability–mitigation trade-offs, and the practical manageability of China’s steel-sector decarbonization. Full article

Steelmaking is one of the most important industries worldwide due to many products being made with different kinds of steel or cast iron; during processing, pig iron and scrap are founded in furnaces and then transported in ladles to be cast in tundishes towards strains to produce steel billets, which are treated in a secondary manufacturing process to produce products like wires and profiles. Then, it is necessary to pay attention to every process and establish rules for safe operational practices, avoid interruptions in production, reduce risks and maintain quality. Thus, the purpose of this research is to study the hydrodynamic behavior of five stopper rods with different but basic geometrical configurations. Stopper rods are devices that are used to control the fluid flow in tundishes to allow or avoid a steel fluid drain. Stopper rods are placed to allow or avoid the liquid steel passing out towards the molds in the deepest holes in the tundishes. Management, drive and mass transport are important parameters to analyze for casting molten steel. After analyzing the hydrodynamic performance of these five stopper rods, and according to the results obtained, two more new designs were created and tested in real industrial trials, and the results are described in detail. Additionally, a study about the counting of the inclusions trapped in the rod walls is also shown to evaluate every design, with the main goal being to retain the flows passing across the stopper rod and the exit nozzle and to avoid clogging problems in order to keep constant the casting of molten steel. Hydro-dynamic analysis was carried out by solving the Navier–Stokes equation using the k-ε turbulence model using Computational Fluid Dynamics (CFD). Full article

This paper presents a comprehensive methodology for assessing supply chain transparency and resiliency using a data-driven approach. Leveraging global trade data and Harmonized System (HS) codes, the methodology maps each stage of the supply chain to enhance regulatory compliance and mitigate operational risks. Transparency is evaluated using a novel classification system that categorizes branches as fully transparent, highly transparent, moderately transparent, or non-transparent. This enables raw material traceability, Scope 3 greenhouse gas (GHG) emission estimation, and identification of high-emission nodes for targeted reductions. Resiliency is assessed through graph analytics and stress testing, incorporating metrics such as the Giant Connected Component (GCC) and probabilistic simulations to analyze vulnerabilities and develop recovery strategies. A case study on the Cr-13 Steel Drill Pipe supply chain highlights the benefits of incorporating scrap materials for sustainability, alongside challenges related to traceability due to regulatory gaps and non-transparent networks. Monte Carlo simulations identify critical nodes whose disruption significantly affects network connectivity; therefore, resiliency, and transparency. This methodology delivers actionable insights to improve supply chain resiliency, sustainability, and operational efficiency. It is scalable across industries, enabling stakeholders to optimize management strategies, align with global climate initiatives, and build resilient and transparent networks. Full article

Injection-molding purges are heterogeneous, bulky residues whose uncertain composition and irregular geometry hinder direct reinsertion, making cold shredding costly and maintenance-intensive. This work develops a low-infrastructure solar-assisted pre-processing route using a PMMA Fresnel lens to induce controlled sub-onset softening and enable clean shear cutting without destructive thermal histories. The sub-onset softening is here defined into a viscoelastically active range (at or above T_g for the amorphous phase) while remaining below the melting onset (T_m, onset) and below the onset of thermal degradation (T_d, onset). The station was engineered via QFD and risk-oriented design tools, while a weighted Pugh matrix selected shear cutting over saw-based alternatives. A screening factorial DOE showed that lens height, angle, and their interaction significantly govern focal-spot diameter and receiver temperature, yielding linear relations for conservative set-point selection. Receiver benchmarking further indicated that copper reaches substantially higher temperatures than graphite under identical exposure conditions, supporting copper as the simplest, rapid-heating receiver. Under DOE-calibrated operation, tear-free shear cutting was achieved across representative purge families (PP–ABS, PC–ABS–PP, PA66, PA66-filler, and POM) without forced convection. From a recycling and waste-management perspective, the approach converts bulky purge scrap into mill-compatible feedstock with reduced mechanical resistance, lowering tool wear and fines generation, accelerating downsizing, and limiting stockpiling that elevates combustible-inventory fire risk. Overall, the proposed DOE-calibrated, operator-friendly framework improves recycling feasibility by enabling safer handling, more stable preprocessing throughput, and reduced reliance on disposal or long-term storage for heterogeneous industrial purges. Full article

Crumb rubber (CR), a recycled elastomeric polymer derived from scrap tyres, has been used as a partial replacement for fine aggregates in concrete to manage non-biodegradable waste tyre piling, which fills landfills and harms the environment. Polymer-modified rubber improves the concrete’s flexibility, toughness, and impact resistance, but reduces its strength and modulus of elasticity. Multi-walled carbon nanotubes (MWCNTs) are being used to mitigate these issues. The purpose of this study is to investigate the impact of CR% (1% to 5%) as a partial replacement for sand by volume and MWCNTs (at a percentage of 0.05% to 0.08%) as additives by weight of cement as input parameters for determining the mechanical strength (compressive, tensile, and flexural) and deformation properties (modulus of elasticity and Poisson’s ratio) of MWCNT- and polymer-modified CR concrete using response surface methodology (RSM). The results show that 0.05% MWCNT and 1% CR content led to increases in compressive strength, flexural strength, and tensile strength by 14.12%, 11%, and 13.68%, respectively. In addition, models to predict those properties have been developed using RSM with a 95% reliability level. It has been observed that the notable development in the mechanical characteristics of CR concrete with the accumulation of MWCNTs and the models constructed using RSM were deemed satisfactory, with a variation of 0.05% to 0.065% of MWCNTs along with 2% CR. Full article

The extensive integration of lithium-ion batteries (LIBs) into modern technologies—including portable electronics, electric vehicles (EVs), and battery energy storage systems (BESSs)—has created a critical dependency on the supply of raw materials. The ongoing shift toward clean mobility is expected to further intensify this demand. This trend coincides with a projected increase in battery waste: over the next decade, millions of tons of EV and BESS batteries will reach their end-of-life (EOL), alongside the generation of considerable manufacturing scrap. Recycling is essential for recovering critical materials and reducing dependency on primary mining, thereby benefiting the circular economy and environmental sustainability. However, EOL-LIBs are more prone to thermal runaway due to defects and aging-induced degradation, which can lead to fire and explosion incidents, as well as associated environmental and health hazards. Such incidents have been increasingly reported in recent years during transportation, storage, handling, and illegal disposal, resulting in potential loss of life, property damage, and ecological degradation. To ensure the safe design and operation of the battery recycling industry, this work provides an updated overview of the health, safety and environment (HSE) hazards posed by EOL-LIBs and the safety measures required to mitigate these hazards. First, this work outlines the structures, components, and aging mechanisms of LIBs. Second, it summarizes the state-of-the-art recycling pathways and relevant process risks, such as deactivation, dismantling, and mechanical and thermal pretreatments. Third, it reviews recent safety incidents initiated by thermal runaway of EOL-LIBs and recycling intermediates like black mass, with an emphasis on storage and handling. Fourth, recommendations for future work regarding the safe storage and processing of EOL batteries are provided. Finally, conclusions and perspectives on future research directions are presented. Continued research and development in this field are essential to improve recycling methods, optimize processes, and ensure the safe and sustainable management and legislation of EOL lithium-ion batteries. Full article

Fertilization management is crucial mainly during the walnut training phase in order to obtain good plant formation, which is essential for guaranteeing future optimal yield. The aim of the present experiment was to evaluate the effect of different organic amendments on plant nutritional status and soil fertility in young bearing walnut trees. The experiment was conducted in 2023 and 2024 on walnut trees of the cultivar Chandler grafted on Juglans regia, planted in 2021. Since 2023, plants were yearly treated as follows: 1. non-fertilized control; 2. mineral fertilization; 3. application of municipal solid waste compost; and 4. application of compost from agri-food chain scraps. Soil amendments were supplied at the same rate as mineral fertilizer (120 kg N ha⁻¹) in spring on the tree row on a 1.5 m wide strip, while mineral fertilizer was split in two applications (50% in spring and 50% in summer). Plant growth, measured with trunk diameter and pruning wood weight, was enhanced by mineral fertilization, followed by compost, in comparison to the control. Soil mineral N was too high in relation to plant needs, with a consequent increase in the risk of nitrate leaching. Organic amendments increased soil nutrient availability, microbial activity, and carbon concentration, which, in the long term, could provide a positive environmental effect related to its sequestration into the soil. Full article

Evidence on the environmental and socio-economic harms linked to plastic pollution has prompted major governance responses, including the 2019 Basel Convention amendments on plastic waste and the start of negotiations on a global plastics treaty in 2022. In parallel, many jurisdictions have introduced minimum recycled-content requirements to curb virgin-material demand and strengthen circularity in plastics. Yet trade statistics show that plastic scrap is only a small fraction of cross-border flows of secondary (recyclable) materials. Policy debates are also increasingly focused on non-plastic alternatives for packaging and other uses, but these substitutes can carry substantial upstream and downstream burdens that may match or exceed plastics depending on production pathways and end-of-life management. This article contrasts global trade patterns for secondary plastics, textiles, paper, and ferrous metals, and highlights how governance frameworks have centered disproportionately on plastics. We argue that the momentum from plastic-waste controls and recycled-content mandates should be used to build more systemic policies that also cover other material streams; otherwise, interventions may simply displace impacts to substitute materials and weaken circular-economy objectives. Full article

The purpose of this paper is to examine the application and development of CAD/CAM technologies in the modern metal cutting industry, with a focus on their role in increasing production accuracy, efficiency, and sustainability. The study presents an industrial case of laser cutting of AISI 304 stainless-steel sheets, in which two approaches are compared under identical material and technological parameters: conventional manual nesting and automatic nesting based on algorithms implemented in a CAD/CAM environment. The methodology evaluates both layouts using clear technical and economic indicators, including number of parts per sheet, material utilization, cutting time, weight of scrap, and cost per sheet. For the analyzed batch, automatic nesting increases the number of parts per sheet from 44 to 76 (≈73%), reduces the unused sheet area from 61% to 39%, and shortens the cutting time from 12 to 9 min (≈25%), which leads to a reduction in material waste by about 36% and cost savings of approximately 314 EUR per sheet. As a result, the process becomes more efficient and reliable, supporting sustainable and digital manufacturing goals. The findings confirm the importance of algorithmic optimization in CAD/CAM systems for enhancing industrial competitiveness, enabling effective resource management, and facilitating the transition towards Industry 5.0. Full article

Biodegradable waste is commonly treated as a problem to be managed, but it can be a valuable resource when considered within a circular bioeconomy perspective. This article develops a practical and systems-based frame work for integrating biodegradable waste, ranging from municipal food scraps to wastewater biosolids, into valuable resources. It explores real-world strategies for transforming waste into value-added products, including composting, anaerobic digestion, biochemical conversion, and the creation of bio-based materials. The review also highlights key drivers and barriers, including technical, regulatory, and social factors, which shape the feasibility and impact of circular solutions. A visual model illustrates the full cycle, from identifying waste streams to reintegrating recovered resources. The paper also highlights case studies from Toronto, Milan and Brazil as examples of successful implementation. Overall, this paper emphasizes a pragmatic yet regenerative shift toward organic resource recovery aligned with sustainability and decarbonization goals. Full article

Data-driven quality control (QC) systems for the hot forming of steel parts increasingly rely on deep learning models deployed at the network edge, making multivariate sensor time series a critical asset for both local decisions and management information system (MIS) reporting. However, these models are vulnerable to adversarial perturbations and realistic signal disturbances, which can induce misclassification and distort key performance indicators (KPIs) such as first-pass yield (FPY), scrap-related losses, and latency service-level objectives (SLOs). To address this risk, this study introduces a Digital-Twin-Conditioned Diffusion Purification (DTCDP) framework that constrains latent diffusion-based denoising using process states from a lightweight digital twin of the hot-forming line. At each reverse-denoising step, the twin provides physics residuals that are converted into a scalar penalty, and the diffusion latent is updated with a guidance term. This directly bends the sampling trajectory toward reconstructions that adhere to process constraints while removing adversarial perturbations. DTCDP operates as an edge-side preprocessing module that purifies sensor sequences before they are consumed by existing long short-term memory (LSTM)-based QC models, while exposing purification metadata and physics-guidance diagnostics to the plant MIS. In a four-week production dataset comprising more than 40,000 bars, with white-box ℓ∞ attacks crafted on multivariate sensor time series using Fast Gradient Sign Method and Projected Gradient Descent at perturbation budgets of 1–3% of the physical range, combined with additional realistic disturbances, DTCDP improves the robust classification performance of an LSTM-based QC model from 61.0% to 81.5% robust accuracy, while keeping clean accuracy (≈93%) and FPY on clean data (≈97%) essentially unchanged. These results indicate that physics-aware, digital-twin-guided diffusion purification can enhance the adversarial robustness of edge QC in hot forming without compromising operational KPIs. Full article

The demand for submersible pumps for lifting the liquids from under the surface is growing day by day. The growing market of submersible pumps creates difficulties for managing their end of life. Recycling, the process of converting scraps material into new virgin material and fine products while the expenditures are used for carrying the scrap material from different sources to destinations, is the main focus area of this research. The aim of this study is to investigate and create strategies for minimizing the transportation cost in the reverse logistics of electrical appliances (submersible pumps) in order to increase profitability and economically sustainability. Data was gathered through interviews with two distinct individuals that are extremely knowledgeable and proficient in their fields. A case study of reverse logistics of submersible pumps is used to optimize the transit cost in a supply chain. To find an appropriate solution, the simplex linear programming approach was used. Microsoft Excel Solver was utilized to conduct data analysis. The findings revealed that optimizing the transportation cost not only reduces the operational cost, but also increases the profit margins. The study concludes that by integrating reverse logistics strategically, both environmental and financial benefits can be achieved by industries. Full article

Gravity beneficiation is a key operation in mineral processing and waste recycling, enabling the production of concentrates with required quality. Among gravity separators, pulsating jigs remain widely applied due to their robustness and adaptability. This study evaluates the KOMAG laboratory jig for upgrading diverse feedstocks: hard coal with variable ash content, gravel aggregates with organic impurities, post-mining waste, and battery scrap. Tests were performed on a two-chamber jig with an air-pulsation system and advanced control. The results confirmed the feasibility of obtaining coal concentrates with 8%–10% ash at 59%–71% yield, complete removal of organic contaminants from aggregates with minimal losses, and recovery of combustible fractions from post-mining waste with favourable separation parameters (d₅₀ = 1.569 g/cm³, imperfection = 0.191). Beneficiation of shredded battery scrap achieved 74%–88% plastic removal and over 99% metallic recovery. Industrial implementations of KOMAG pulsating jigs validated these findings, showing high efficiency in coal, aggregate, and waste processing. This study demonstrates the versatility of pulsating jigging and its relevance in sustainable resource management, confirming that laboratory results can be effectively scaled to industrial practice. Full article

The electric arc furnace (EAF) is a key technology in the steel production industry, particularly for recycling scrap iron. It plays a crucial role in the shift to low-carbon metallurgy, responding to the growing demand for more sustainable production methods. Alongside its environmental and energy benefits, the EAF process generates significant amounts of solid by-products, including dust (EAFD) and slag (EAFS). These wastes are not only rich in base metals but also contain critical elements, which have attracted increasing scientific and industrial interest. Depending on the waste type, key metals such as zinc (from EAFD) and chromium, vanadium, and titanium (from EAFS) are targeted for recovery. This review examines the chemical and phase compositions of these wastes, various leaching techniques (often combined with pretreatment stages), and methods for final metal recovery, either in their pure form or as compounds. Key challenges in hydrometallurgical routes include chloride contamination, the dissolution of refractory zinc ferrite, and impurity management. Despite current limited industrial adoption, hydrometallurgical approaches show significant promise as efficient and environmentally friendly solutions for resource recycling, offering high-purity metal recovery. Full article

Optimizing manufacturing processes to reduce scrap and enhance process stability presents significant challenges, particularly when multiple conflicting objectives must be addressed concurrently. As the number of objectives increases, the complexity of the optimization task escalates. This difficulty is further intensified in online optimization scenarios, where optimal parameter settings must be delivered in real time within active production environments. In this work, we propose a reinforcement learning-based framework for the multi-objective optimization of manufacturing parameters, demonstrated through a case study on pinion gear manufacturing. The framework utilizes the Multi-Objective Maximum a Posteriori Optimization (MO-MPO) algorithm to train a reinforcement learning agent. A high-fidelity simulation of the pinion manufacturing process is constructed in Simufact, serving both data generation and validation purposes. The agent’s performance is assessed using a hold-out test set along with additional simulations of the physical process. To ensure the generalizability of the approach, further validation is performed using open-source manufacturing datasets and synthetically generated data. The results demonstrate the feasibility of the proposed method for real-time industrial deployment. Moreover, Pareto-optimality is verified via half-space analysis, emphasizing the framework’s effectiveness in managing trade-offs among competing objectives. Full article