Search Results (233)

The growing need to improve the management of end-of-life vehicle (ELV) waste and mitigate its environmental impact is a global concern. One promising approach to enhancing the recyclability of these vehicles is leveraging synergies between the automotive and construction industries as part of a circular economy strategy. In this context, ELV waste emerges as a valuable source of secondary raw materials, enabling the development of sustainable innovations that capitalize on its physical and mechanical properties. This paper aims to develop and evaluate construction industry composites incorporating waste from ELV carpets, with a focus on maintaining or enhancing performance compared to conventional materials. To achieve this, an experimental program was designed to assess cementitious composites, specifically subfloor mortars, incorporating automotive carpet waste (ACW). The results demonstrate that, beyond the physical and mechanical properties of the developed composites, the dynamic stiffness significantly improved across all tested waste incorporation levels. This finding highlights the potential of these composites as an alternative material for impact noise insulation in flooring systems. From an academic perspective, this research advances knowledge on the application of ACW in cement-based composites for construction. In terms of managerial contributions, two key market opportunities emerge: (1) the commercial exploitation of composites produced with ELV carpet waste and (2) the development of a network of environmental service providers to ensure a stable waste supply chain for innovative and sustainable products. Both strategies contribute to reducing landfill disposal and mitigating the environmental impact of ELV waste, reinforcing the principles of the circular economy. Full article

Carbon fiber (CF) and carbon fiber-reinforced polymers (CFRPs) are widely used in the aerospace, automotive, and energy sectors due to their high strength, stiffness, and low density. However, significant waste is generated during manufacturing and after the use of CFRPs. Traditional disposal methods like landfilling and incineration are unsustainable. CFRP machining processes, such as drilling and milling, produce fine chips and dust that are difficult to recycle due to their heterogeneity and contamination. This study investigates the oxidation behavior of CFRP drilling waste from two types of materials (tube and plate) under oxidative (non-inert) conditions. Thermogravimetric analysis (TGA) was performed from 200 °C to 800 °C to assess weight loss related to polymer degradation and carbon fiber integrity. Scanning electron microscopy (SEM) was used to analyze morphological changes and fiber damage. The optimal range for removing the polymer matrix without significant fiber degradation has been identified as 500–600 °C. At temperatures above 700 °C, notable surface and internal fiber damage occurred, along with nanostructure formation, which may pose health and environmental risks. The results show that partial fiber recovery is possible under ambient conditions, and this must be considered regarding the harmful risks to the human body if submicron particles are inhaled. This research supports sustainable CFRP recycling and fire hazard mitigation. Full article

In response to growing environmental pressures and material constraints, circular economy principles are gaining traction across manufacturing sectors. However, most existing frameworks emphasize design and supply chain considerations, with limited focus on how circularity can be operationalized within internal manufacturing systems. This paper proposes a conceptual model that embeds circular operations at the core of production strategy. Grounded in circular economy theory, operations management, and socio-technical systems thinking, the model identifies four key operational pillars: circular input management, looping process and waste valorization, product-life extension, and reverse logistics. These are supported by enabling factors—digital infrastructure, organizational culture, and leadership—and mediated by operational flexibility, which facilitates adaptive, closed-loop performance. The model aims to align internal processes with long-term sustainability outcomes, specifically resource efficiency and operational resilience. Practical implications are outlined for resource-intensive industries such as automotive, electronics, and FMCG, along with a readiness assessment framework for guiding implementation. This study offers a pathway for future empirical research and policy development by integrating circular logic into the structural and behavioral dimensions of operations. The model contributes to advancing the Sustainable Development Goals (SDGs), particularly SDG 9 and SDG 12, by positioning circularity as a regenerative operational strategy rather than a peripheral initiative. Full article

Increased concern for human health and the environment has pushed various industries to adopt new approaches towards satisfying modern regulations. Strategies to achieve these approaches include utilizing lightweight materials, repurposing waste materials, and substituting synthetic polymers with bio-based counterparts. This study investigates the effects of treated fly ash (C) and bio-based polyamide 10.10 (PA10) on the thermal, morphological, and mechanical properties of glass fiber (GF)-reinforced polyamide 6 (PA6). Our main objective was to develop a composite that would allow for the partial replacement of glass fiber in reinforced polyamide 6 composites (PA6-30G) while maintaining a favorable balance of mechanical properties. Composites processed via melt processing demonstrated enhanced mechanical properties compared to PA6-30G. Notably, significant improvements were observed in impact strength and tensile strain at break. The addition of PA10 resulted in increases of 18% in impact strength and 35% in tensile strain relative to PA6-30G. Complementary, structural and morphological analyses confirmed strong interfacial interactions within the composite matrix. These findings indicate that a PA6/PA10 hybrid composite may represent a viable alternative material for potential automotive applications. Full article

In response to the rising demand for sustainable engineering materials and waste valorisation strategies, this study investigates the multi-objective optimisation of eco-friendly hybrid composites reinforced with natural fibres and industrial waste. Sixteen composite specimens were fabricated using compression moulding by varying sisal fibre from 0 to 45 wt.%, banana fibre from 0 to 45 wt.%, NaOH alkali treatment from 0 to 6%, and red mud filler from 1 to 4 wt.%. Mechanical properties were evaluated following ASTM standards D256 for impact strength, D790 for flexural strength, D638 for tensile strength, D5379 for shear strength, and E18 for hardness. The Taguchi method combined with grey relational analysis was employed to identify optimal processing conditions. The best mechanical performance, with an impact strength of 6.57 J, flexural strength of 72.58 MPa, and tensile strength of 65.52 MPa, was achieved with 30 to 45 wt.% sisal fibre, 15 wt.% banana fibre, 6% NaOH, and 3 to 4 wt.% red mud. ANOVA revealed that NaOH treatment had the most significant influence on mechanical properties, with high F values and p values close to 0.05. Grey relational analysis proved more effective for multi-objective optimisation, with the highest grey grade of 0.894 observed in the specimen containing 45 wt.% sisal fibre, 6% NaOH, and 2 wt.% red mud. These findings highlight the critical role of fibre treatment and hybrid reinforcement in enhancing performance. The optimised composites demonstrate strong potential for use in automotive interior panel applications, offering a sustainable alternative with balanced strength and reduced environmental impact. Full article

In this work, the mechanical properties of composites with a polymer matrix and reinforced with carbon particles have been studied. It has been established that the obtained engineering materials have increased elastic and plastic characteristics. The thermosetting polymers used are epoxy, polyester, and vinylester resins. The carbon particles are carbon nanotubes and waste carbon from the plasma decomposition of methane in the production of green hydrogen. The carbon particles used are in an amount of 1 wt% and 2 wt% of the weight of the composite, and they are not subjected to pre-treatment (modification). The studied composites are used in shipping, automotive, and aviation technology, and the presence of carbon particles in them is a prerequisite for improving their anti-radar properties. Full article

The recovery of waste from old vehicles generates different types of waste. Most waste can be recovered with more or less success. Among the wastes that are problematic is foam. It is large in volume and light in weight, and there is currently no highly efficient technology to recover this waste and produce new products. The aim of this paper is to analyse the current situation in the processing, research, development, design and testing of test samples as a basis for the production of a machine to produce new 3D products made from waste foam. The paper begins with an analysis of the amount of plastic waste generated in the automotive industry. It describes the current state of waste management and the possibilities of its use in the production of new products. The core of the paper is the selection of suitable technology and the design and verification of experimental measurement and evaluation of test samples at different temperatures and pressures and with different endurance times. Full article

A wide experimental campaign was developed on an automotive turbocharged diesel engine, using two blends between diesel oil and waste cooking oil methyl esters (WCOME) and neat biodiesel. A conventional B7 diesel oil was considered as a reference fuel. The two blends, respectively, included 40 and 70% of WCOME, on a volumetric basis. The influence of biodiesel was analyzed by testing the engine in two part-load operating conditions, applying proper control strategies to the exhaust gas recirculation (EGR) circuit and rail pressure, to assess the interactions between the engine management and the tested fuels. The variable nozzle turbine (VNT) was controlled to obtain a constant level of intake pressure in the two experimental points. Referring to biodiesel effects at constant operating mode, higher WCOME content generally resulted in better efficiency and soot emission, while NO_X emission was negatively affected. EGR activation allowed for limited NO formation but with penalties in soot emission. Furthermore, interactions between the EGR circuit and turbocharger operations and control led to higher fuel consumption and lower efficiency. Finally, the increase in rail pressure corresponded to better soot emission and penalties in NO_X emission. Combining all these effects, the selection of EGR rate and rail pressure values higher than the standard levels resulted in better efficiency, NO_X, and soot emissions when comparing blends and neat biodiesel to conventional B7, granting advantages not only with regard to greenhouse gas emissions. Combustion parameters were also assessed, showing that combustion stability and combustion noise were not negatively affected by biodiesel use. Combustion duration was reduced when using WCOME and its blend, even if the center of combustion was slightly shifted along the expansion stroke. The main contribution of this investigation to the scientific and technical knowledge on biodiesel application to internal combustion engines is related to the development of tests on diesel–biodiesel blends with high WCOME content or neat WCOME, identifying their effects on NO_X emissions, the definition of integrated strategies of HP EGR system, fuel rail pressure, and VNT for the simultaneous reduction in NO_X and soot emissions, and the detailed assessment of the influence of biodiesel on a wide range of combustion parameters. Full article

The growing volume of plastic waste from end-of-life vehicles presents environmental concerns, driving efforts to integrate recycled plastics. This study investigates the possibility of using recycled plastic from automotive parts (painted and unpainted bumpers, fuel tanks) as a 10% filler in the core layer of three-layer particleboards (P) and evaluates its impact on physical properties (water absorption—WA and thickness swelling—TS), mechanical properties (internal bonding strength—IB, modulus of rupture—MOR, modulus of elasticity—MOE and screw driving torque—SDT) and volatile organic compounds—VOC emissions. The boards were produced using conventional hot-pressing technology and analyzed according to applicable standards. Based on the results, the density of the reference (P) was 0.72 g·cm⁻³, while wood–plastic composites ranged from 0.70 g·cm⁻³ to 0.72 g·cm⁻³. After 24 h, WA reached 40% for reference (P) and from 36.9% (for (P) containing unpainted bumpers) to 41.9% (for (P) containing fuel tanks). TS reached 18% for (P) and from 16.8% (for (P) containing unpainted bumpers and fuel tanks) to 18.1% (for (P) containing painted bumpers). Plastic is a hydrophobic material and it is assumed that by increasing the proportion of plastic filler in the particleboards, the WA and TS of prepared boards will decrease. From the point of view of mechanical properties, values for (P) containing plastic filler were slightly lower compared to reference (P). The lowest value of IB (0.39 MPa) were reached for (P) containing painted bumpers. Plastic surface treatment could interfere with adhesion between the plastic and adhesive, weakening the bond in the core layer. For this reason, is preferable to use unpainted fillers, which provide better adhesive properties and higher structural integrity. VOC emissions from wood components consisted primarily of monoterpenes such as α-pinene, 3-carene and limonene. Adding 10% plastic to the particleboard did not increase overall VOC emissions. On the other hand, combining wood and plastic particles resulted in a reduction in overall VOC emissions. The findings confirm that recycled automotive plastics can be effectively incorporated into particleboards, maintaining standard performance while reducing reliance on virgin wood materials, making them a viable and sustainable alternative for furniture and interior applications. Full article

Enhanced demand for the development of sustainable materials has generated significant research interest in products containing biomass-derived fibers, such as the fibers extracted from the energy crop Sida hermaphrodita (SH). Green chemicals and green methods, such as microwave treatment, have been used for the isolation of fibers from biomass waste. In this study, long extracted fibers were used as a reinforcement of the PLA matrix to give them high strength, which is required for high-performance biocomposites. To enable composite usage in automotive industry, several additives were applied to enhance their mechanical, thermal, and antimicrobial properties. Therefore, vegetable drying oil, montmorillonite nanoclay (MMT), and milled cork were used to improve their mechanical and thermal properties. Zinc oxide (ZnO) was applied to enhance the biocomposite’s antimicrobial properties, which were confirmed through significant bacterial reduction across all tested biocomposite variants, particularly in samples functionalized with ZnO, cork, and montmorillonite. Additionally, X-ray microtomography provided detailed insight into fiber dispersion and internal structural heterogeneity, which is crucial for evaluating mechanical performance and flame-retardant behavior. All characterization methods, including mechanical ones, lead to the conclusion that green and sustainable biocomposites based on PLA and Sida hermaphrodita fibers treated with antimicrobial (AM) and flame-retardant (FR) agents can be successfully applied for a wide variety of antimicrobial and flame-retardant products. Full article

This study aims to develop a process to calculate the carbon footprint of a company in the textile sector for the automotive industry, thus addressing a research gap identified in this sector. Based on a structured calculation model, the project aspires to innovate by quantifying not only the greenhouse gas emissions at different stages of the company’s operations, including those generated by the consumed electricity and gas, but also the emissions related to external and in-house transportation and solid waste management. The approach includes the design of a specific calculator, capable of integrating variables such as energy consumption, transport and types of waste, analysing them in the light of recognised conversion factors. This tool not only allows for a detailed assessment of emissions but also supports strategic decision-making, guiding the implementation of more sustainable business practices. The results indicate that, considering the use of renewable energy sources, the company’s total emissions amount to approximately 18 thousand tonnes of carbon dioxide equivalent. On the other hand, considering non-renewable energy, purchased electricity accounts for 31 thousand megawatt-hours per year, corresponding to 5 thousand tonnes of carbon dioxide equivalent, with the twisting area being the largest consumer at 89% of total usage, followed by the dipping area. In terms of mobile combustion, raw materials contribute 1373 million tonnes of carbon dioxide equivalent, while finished products generate 1869 million tonnes of carbon dioxide equivalent. Among the most impactful variables, solid waste, and stationary combustion stand out as the main contributors. These findings highlight the need for concrete measures to mitigate climate change, such as transitioning from stationary natural gas combustion to green electric power; identifying companies with more suitable waste treatment solutions, process changes that reduce disposable, and easily substitutable materials; making use of green electricity; exploring alternative transport methods or combining different modes, such as using electric vehicles for short distances; and optimizing transport routes. These initiatives reinforce the company’s commitment to sustainable development goals and the promotion of responsible environmental practices. Full article

The cement industry contributes approximately 7% of global anthropogenic CO₂ emissions, primarily through energy-intensive clinker production. This study evaluates the thermal behavior and gas emissions of seven waste materials (sawdust, pecan nutshell, wind blade waste, industrial hose waste, tire-derived fuel, plastic waste, and automotive shredder residue) as alternative fuels for cement manufacturing, motivated by the limited information available regarding their performance and environmental impact, with bituminous coal used as a reference. Thermogravimetric analysis and differential scanning calorimetry (TGA-DSC) were used to quantify mass loss and energy changes, while TGA coupled with mass spectrometry (TGA-MS) was used to identify volatile compounds released during thermal degradation. Both TGA-DSC and TGA-MS were conducted under oxidative conditions. The analysis revealed that these waste materials can generate up to 70% of coal’s energy, with combustion primarily occurring between 200 °C and 600 °C. The thermal profiles demonstrated that these materials can effectively replace fossil fuels without releasing harmful toxic gases like HCl, dioxins, or furans. Combustion predominantly emitted CO₂ and H₂O, with only trace volatile organic compounds such as C₃H₃ and COOH. The findings highlight the potential of alternative fuels to provide substantial energy for cement production while addressing waste management challenges and reducing the industry’s environmental impact through innovative resource valorization. Full article

The automotive industry constantly seeks intelligent technologies to increase competitiveness, reduce costs, and minimize waste, in line with the advancements of Industry 4.0. This study aims to implement and analyze a predictive model based on machine learning within the automotive industry, validating its capability to reduce the impact of unplanned downtime. The implementation process involved identifying the central problem and its root causes using quality tools, prioritizing equipment through the Analytic Hierarchy Process (AHP), and selecting critical failure modes based on the Risk Priority Number (RPN) derived from the Process Failure Mode and Effects Analysis (PFMEA). Predictive algorithms were implemented to select the best-performing model based on error metrics. Data were collected, transformed, and cleaned for model preparation and training. Among the five machine learning models trained, Random Forest demonstrated the highest accuracy. This model was subsequently validated with real data, achieving an average accuracy of 80% in predicting failure cycles. The results indicate that the predictive model can effectively contribute to reducing the financial impact caused by unplanned downtime, enabling the anticipation of preventive actions based on the model’s predictions. This study highlights the importance of multidisciplinary approaches in Production Engineering, emphasizing the integration of machine learning techniques as a promising approach for efficient maintenance and production management in the automotive industry, reinforcing the feasibility and effectiveness of predictive models in contributing to sustainability. Full article

The integration of machine learning (ML) has begun to reshape the development of advanced polymeric materials used in technical textiles. Polymeric materials, with their versatile properties, are central to the performance of technical textiles across industries such as healthcare, aerospace, automotive, and construction. By utilizing ML and AI, researchers are now able to design and optimize polymers for specific applications more efficiently, predict their behavior under extreme conditions, and develop smart, responsive textiles that enhance functionality. This review highlights the transformative potential of ML in polymer-based textiles, enabling advancements in waste sorting (with classification accuracy of up to 100% for pure fibers), material design (predicting stiffness properties within 10% error), defect prediction (enabling proactive interventions in fabric production), and smart wearable systems (achieving response times as low as 192 ms for physiological monitoring). The integration of AI technologies drives sustainable innovation and enhances the functionality of textile products. Through case studies and examples, this review provides guidance for future research in the development of polymer-based technical textiles using AI and ML technologies. Full article

This study presents an automated computer vision system for assessing the cleanliness of plastic mirror caps used in the automotive industry after a washing process. These components are highly visible and require optimal surface conditions prior to painting, making the detection of residual contaminants critical for quality assurance. The system acquires high-resolution monochrome images under various lighting configurations, including natural light and infrared (IR) at 850 nm and 940 nm, with different angles of incidence. Four blob detection algorithms—adaptive thresholding, Laplacian of Gaussian (LoG), Difference of Gaussians (DoG), and Determinant of Hessian (DoH)—were implemented and evaluated based on their ability to detect surface impurities. Performance was assessed by comparing the total detected blob area before and after the cleaning process, providing a proxy for both sensitivity and false positive rate. Among the tested methods, adaptive thresholding under 30° natural light produced the best results, with a statistically significant z-score of +2.05 in the pre-wash phase and reduced false detections in post-wash conditions. The LoG and DoG methods were more prone to spurious detections, while DoH demonstrated intermediate performance but struggled with reflective surfaces. The proposed approach offers a cost-effective and scalable solution for real-time quality control in industrial environments, with the potential to improve process reliability and reduce waste due to surface defects. Full article