Search Results (422)

The socks, hosiery, bodywear (SHB) industry is a critical segment of the textile sector, characterized by high-volume production and rapid delivery requirements, making efficiency and resource optimization essential. A corporate sustainability system is needed to minimize environmental impact, ensure long-term competitiveness, and align operations with global sustainability standards. Thus, this research aims to propose an integrated Corporate Sustainability System (CSS) framework that synergizes Lean Manufacturing (LM), Digital Transformation (DT), and sustainability transition through a methodological triangulation of (1) a narrative review, (2) in-depth expert interviews, and (3) a comprehensive Turkish case study. The proposed framework integrates foundational lean principles such as 5S, TPM, and Value Stream Mapping with Industry 4.0 technologies, including RFID traceability, real-time ERP integration and machine vision systems. Empirical demonstration through the case study reveals that establishing foundational lean maturity is a critical foundation for successful digital adoption. Furthermore, the study demonstrates that transitioning from manual tracking to integrated digital platforms resolves data silos and enhances the transparency of customer revisions and warehouse accuracy. The framework also incorporates human-centric Lean 5.0 improvements, proving that ergonomic interventions such as rail-mounted cable systems are vital for operational sustainability. Ultimately, the CSS provides a scalable model that aligns SHB production with global mandates like the EU Green Deal and CBAM, positioning the sector for long-term competitive advantage in an increasingly eco-conscious global market. Full article

The fashion industry’s business is becoming increasingly complicated and active. This industry is expected to be highly competitive, particularly in the retail sector. Therefore, this research aims to examine the impact of supply chain information sharing and quality management on firm performance, with supply chain agility as a mediating variable, in the Asian fashion industry. A total of 169 participants from the fashion sector in a developing country were surveyed. The proposed hypotheses were examined using a quantitative approach, employing Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS to assess and validate the measurement model. The results indicate that supply chain information sharing and quality management have a significant impact on a firm’s performance. Similarly, the sharing of supply chain information and quality management has a significant impact on firm performance by mediating supply chain agility. The study offers actionable insights for managers in volatile fashion supply chains. Firms can enhance performance by sharing real-time demand and inventory information, strengthening key quality practices, and adopting flexible, data-driven production processes. Integrating information sharing, quality management, and agility enables faster responses to shifting consumer trends, thereby improving overall competitiveness in fast-fashion environments. This study offers valuable guidance for supply chain professionals seeking to enhance practices within their networks. The results underscore the strategic importance of information sharing and quality management in promoting agility, an essential capability for achieving a competitive advantage. Additionally, the insights generated are relevant to practitioners, policymakers, and industry leaders aiming to strengthen supply chain responsiveness and resilience. Full article

Advances in Industry 4.0 manufacturing have accelerated the adoption of machine learning (ML) for automated classification. Polyester (PES), a widely used synthetic fiber, competes with natural fibers like cotton and other synthetics, highlighting the need for continuous research and improvement. In the textile sector, distinguishing recycled polyester (rPES) from virgin polyester (vPES) remains challenging due to overlapping chemical signatures and material variability. A combination of Fourier transform infrared (FTIR) spectroscopy and ML has not been explored for this purpose. In this study, we evaluated ML models to discriminate three PES fiber types (45 vPES, 65 rPES, and 55 mixed PES) using 165 FTIR spectra across four spectral regions, R1, R2, R3, and R4, as well as their combined representation. Six ML approaches were tested on data reduced with fast independent component analysis (FastICA) (1–30 components) using an 80/20 train–test dataset split. The Decision Tree classifier achieved the highest Accuracy in four of the five spectral evaluations, with classification accuracies ranging from 66.67% to 77.78% for region R4, which also had a balanced classification profile with an area-under-the-curve (AUC) value of 0.81. Notably, despite the moderate overall Accuracy, the model achieved 100% discrimination of rPES when distinguishing it from both mixed and vPES. Mixed fibers remained the most difficult to classify, highlighting the need for improved feature representation. Full article

The textile industry of Pakistan plays a vital role in the national economy; however, it faces increasing pressure to adopt sustainable and circular practices. The circular economy (CE) approach minimizes waste and enhances resource efficiency. However, prior studies have focused on technical and legislative elements of CE adoption, while eco-capability remains understudied in developing economies. This study investigates the role of green skills development (GSD), employee training on CE (ETCE), and employee proactive behavior (EPB) in enhancing circular economy performance (CEP) in Pakistan’s textile sector, supported by the Resource-Based View theory. Using a quantitative, cross-sectional survey design, primary data were collected from 215 middle-to-top-level employees working in textile manufacturing organizations across Pakistan through a structured five-point Likert scale questionnaire. Measurement and structural models were examined using PLS-SEM to assess reliability, and validity, and model relationships. Results indicate that GSD (β = 0.431, t = 5.846) and ETCE (β = 0.357, t = 4.728) significantly enhance CEP, emphasizing the importance of technical skills and structural training. EPB, however, showed no significant effect (β = −0.008, t = 0.080), indicating that individual initiative alone is insufficient. The finding suggested that formal skill development and systemic CE training are critical for improving sustainable performance and advancing UN SDGs 8 and 12 in Pakistan’s textile industry. Full article

Achieving simultaneous control over total carbon emissions and intensity is essential for China’s dual carbon goals. Using panel data from 1235 listed manufacturing firms (2015–2022), we construct a composite index to measure dual carbon control and investigate how data elements influence corporate carbon performance from an industry heterogeneity perspective. The main findings are as follows. (1) Data elements significantly enhance dual carbon control, with effects concentrated in high-pollution sectors, particularly metallurgy and mineral products, while remaining insignificant in low-pollution industries. (2) Mechanisms differ across industry types: capacity utilization drives improvements in high-pollution industries, whereas green technology innovation matters in low-pollution sectors such as agro-processing and textiles. (3) ESG disclosure and green credit subsidies amplify these effects, though with varying efficacy. Policymakers should adopt differentiated strategies including removing structural barriers to green innovation in high-pollution industries and activating capacity utilization through monitoring standards and technology markets in low-pollution sectors. A tailored policy framework is essential to realize the full potential of data elements in advancing China’s dual carbon goals. Full article

This study investigates the conversion of textile wastewater sludge (TWS) and textile cotton waste (TCW) into solid biofuels through pelletization and torrefaction, addressing the growing need for sustainable waste management and alternative fuels in the textile sector. Blended feedstocks were conditioned to ~10% moisture, pelletized into 8 mm cylinders, and thermally upgraded at 200–240 °C for 30–90 min. Proximate and ultimate analyses, calorific value measurements, compressive strength testing, bulk and true density assessment, and TGA–DTG were used to evaluate fuel properties, while response surface methodology (RSM) optimized torrefaction parameters. The TCW-rich 20:80 (TWS:TCW) blend with 5% starch exhibited the most favorable overall performance, achieving a calorific value of 3377 kcal kg⁻¹, ash of 10.3%, bulk density of 554 kg m⁻³, and maximum compressive strength of 14.9 N mm⁻². Torrefaction at 200 °C for 60 min increased the GCV to 4083 kcal kg⁻¹ with a high mass yield of 92%, indicating mild thermal decomposition and good energy retention. Further Torrefaction at 220–240 °C increased GCV to 4362–4565 kcal kg⁻¹, accompanied by expected mass-yield reductions due to increased devolatilization. TGA–DTG confirmed faster and cleaner decomposition for TCW-rich pellets and higher residues for sludge-rich blends. RSM indicated temperature as the dominant factor governing mass and energy yields. These findings demonstrate that optimized co-pelletization and mild-to-moderate torrefaction can effectively transform textile residues into energy-dense, mechanically stable biofuels suitable for industrial heat applications. Full article

Phytic acid (myo-inositol hexakisphosphate) and its salts, including iron, aluminum, sodium, and lanthanum phytate, are perhaps the most recent discovery in the field of bio-sourced flame retardants. Phytic acid can be extracted from sustainable resources, such as beans, cereals, and oilseeds. Its high phosphorus content (28 wt.% based on molecular weight) organized into six phosphate groups justifies the growing interest this biomolecule has attracted over the last decade in various sectors (as a corrosion inhibitor, antioxidant, and anticancer additive, among others). In addition, when exposed to a flame or an irradiative heat flux, phytic acid is a highly efficient dehydrating and char-forming agent. It also contributes to excellent flame-retardant properties when combined with other carbon sources, such as chitosan, or nitrogen-containing additives, including melamine, urea, and polyethyleneimine. This paper reviews the most recent advances in using phytic acid and its derivatives to design effective flame-retardant systems for textiles, bulk polymers, and foams. It also provides perspectives on possible future developments and implementations. Full article

The digital transformation of the textile industry poses unique challenges due to its labor-intensive processes, complex global supply chains, and coexistence of traditional methods and emerging technologies. Despite the urgency of this transition, existing digital maturity models lack sector-specific frameworks and often fail to integrate multi-criteria decision-making (MCDM) methodologies for quantitative performance assessment. This study addresses these gaps by proposing a novel digital maturity model tailored specifically to the textile sector. The research employs an integrated decision-making framework using the Method Based on the Removal Effects of Criteria (MEREC) to determine objective criterion weights and the Operational Competitiveness Rating Analysis (OCRA) method to rank firm-level digital maturity performance. The findings indicate that Strategy is the most influential dimension, whereas Technology receives the lowest weight. At the sub-criterion level, Management Support, Market Analysis, and Vision and Strategic Awareness are the most critical factors, while Technology Usage Competency is less influential. The performance evaluation shows that Company A3 achieves the highest level of digital maturity, whereas Company A2 ranks lowest. The robustness of the proposed framework is comprehensively validated through a scenario-based sensitivity analysis and a comparative evaluation using the Additive Ratio Assessment System (ARAS) method. Overall, the results suggest that successful digital transformation in the textile sector depends primarily on strategic vision and managerial support rather than on technological infrastructure alone. Full article

Textile-to-textile recycling is increasingly recognised as essential to reduce the environmental footprint of the textile sector, yet fibre-to-fibre routes remain constrained by complex composition of fibre blends, chemical finishes and the degradation of fibre quality during repeated processing. This review provides a comprehensive overview of recycling strategies for major textile fibres, cotton, polyester, viscose, polyamide, and wool, from a fibre-level perspective, highlighting the relationships between fibre chemistry, structure, and recyclability. Mechanical, chemical, and biological recycling routes are analysed with a particular focus on fibre integrity, yarn and fabric performance, and their suitability for industrial textile applications rather than solely on waste management aspects. The review also examines industrial initiatives and emerging technologies driving the transition towards circular textile systems, critically identifying key barriers such as feedstock heterogeneity, fibre blending, and downcycling. Building on existing review articles on textile recycling, this work synthesises current knowledge on fibre-to-fibre routes, compares different process options in terms of recycled-fibre quality and scalability, and highlights remaining technological and implementation gaps. To advance textile circularity, integrated recycling frameworks are proposed that align material design, process optimisation, and policy instruments. This work contributes a cross-disciplinary understanding of how fibre-level innovation can enable resource-efficient, closed-loop textile production, offering a roadmap for future sustainable materials engineering in industrial textile systems. Full article

The textile industries mostly rely on synthetic dyes, which contain nonbiodegradable components and high toxicity, making their use environmentally hazardous. The present research delves into the unique application of proteins extracted from the Black Soldier Fly (BSF) as a natural dye for wool fabrics. The hydrolyzates extracted from each insect material (larvae, cocoons and flies) using superheated water at 170 °C for 1 h were used as natural dyes for dyeing wool fabrics with and without mordant (ferrous sulfate, 5% o.w.f.). Fabrics treated with mordant-free hydrolyzate derived from cocoons showed the best results, with an increase in color strength (K/S value) from 0.43 to 2.78 with an increasing dye concentration from 2% to 50% o.w.f. Color fastness to washing shows that dyed fabrics undergo variable color changes (from grade 4 to grade 1) but release little dye onto other fabrics, especially wool and synthetic fibers. Dry and wet rubbing color fastness tests showed overall variable color fastness, with little color loss on the abraded reference fabric. Overall, this work emphasizes the possible use of hydrolyzate from BSFs as a natural and environmentally friendly dye, which may represent a promising alternative to synthetic dyes in the textile industry. Full article

With the rapid expansion of the global textile sector and increasing awareness of the environmental pollution caused by textile waste, enhancing the recycling of textile waste has become essential to reduce the volume of materials sent to landfill or incineration. As recycling technologies advance, automated sorting systems that are capable of handling large waste streams and accurately identifying materials for appropriate recycling pathways are increasingly recognised as being critical for efficient textile-waste management. Since 2015, over 20 studies have specifically explored technologies and strategies for automating textile sorting of textile wastes. This mini review introduces various textile fibre identification technologies, including traditional visual and tactile examination; label checking and modern identification technology; and NIR, FT-IR, RFID tags. It summarises the current state of sorting processes, with particular emphasis on the development of AI-assisted, fibre-type-based sorting technologies. Commercial scale automated sorting is not established yet for textile waste recycling, due to the complexity of materials used in textiles, the equipment identification limits and high cost of processing, while machine learning and artificial neural networks provide opportunities for future research advancement and commercialisation. Full article

In recent years, sustainability and the concept of a circular economy have grown in importance within almost all industrial sectors. Especially in the chemical industry, recycling of polymer waste streams has become an important pathway to avoid plastic waste being landfilled or incinerated. Additionally, traditional carbon sources, such as fossil fuels, can be substituted with streams of recycled polymer. For example, polyethylene terephthalate (PET), which is utilized in plastic bottles and textiles, may be recycled via glycolysis. This depolymerization yields the monomer bis(2-hydroxyethyl) terephthalate (BHET). This study focuses on the thermal behavior and stability of BHET, both in pure form as well as in the presence of ethylene glycol (EG), as it results from PET glycolysis. For this, differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FTIR), high-performance liquid chromatography (HPLC), powder X-ray diffraction (PXRD), and thermogravimetry (TG) were utilized. The results exhibited pure BHET polymerizing to PET at temperatures above 120 °C, while further increasing temperatures increased the reaction kinetics. Additionally, no reaction was observed in BHET/EG mixtures at any temperature investigated, which can be attributed to the presence of EG shifting the equilibrium of the reaction towards the BHET, thus inhibiting polymerization. Based on these results and the determined BHET/EG (solubility) phase diagram, potential purification strategies based on crystallization are proposed. Full article

The construction sector faces increasing pressure to reduce the embodied energy of building materials while valorizing industrial waste streams. This study evaluates the direct incorporation of post-industrial textile waste (100% cotton and cotton–polyester blends) in its native form to develop high-performance cementitious ceiling sheets. Composites were fabricated under a controlled hydraulic compaction pressure of 2.0 MPa, optimized to achieve matrix densification while preserving the integrity of the fibrous network. Viscoelastic recovery of the compressed fibers induced a hierarchical double-porosity architecture characterized by macro-voids and hollow fiber lumens. This microstructural evolution reduced thermal conductivity to 0.091 W/m·K, approximately 50% lower than commercial cement–fiber benchmarks—without compromising mechanical compliance. Scanning Electron Microscopy (SEM) revealed a mechanistic decoupling between water absorption and dimensional stability. Although the CP15 formulation (15 wt.% cotton–polyester) exhibited high moisture uptake (~21%), thickness swelling remained limited to 1.35%. This dimensional stability is attributed to the hydrophobic polyester framework, which bridges microcracks and constrains hygroscopic expansion within the cellulosic phase. The optimized CP15 composite achieved a Modulus of Rupture (MOR) of 8.75 MPa, exceeding ISO 8336 Category C, Class 2 requirements. Despite increased thickness, the areal density (10.84 kg/m²) remains compatible with standard gypsum-grade suspension systems, eliminating the need for structural modification. These findings establish a scalable, direct-valorization strategy for circular construction materials delivering enhanced thermal insulation and robust performance under tropical climatic conditions. Full article

Textile and fashion designers play a strategic role in sustainable development within the textile chain. Several studies highlight the decision-making role of designers, emphasizing how their choices influence the entire production sector. The aim of this research is to examine how design decisions within the Portuguese textile and fashion industry influence the implementation of sustainable development principles by exploring designers’ perceptions, practices, and the challenges they encounter throughout the design process. To achieve the proposed goal, semi-structured interviews were conducted with 11 designers from the industry. The collected data were qualitatively evaluated using NVivo software, highlighting the complexity of incorporating sustainability into the design process. The findings revealed that daily challenges are primarily related to fashion business models, greenwashing, limited knowledge of raw materials and finishing processes, cost constraints, lack of transparency and traceability in the supply chain, and low consumer awareness. By examining both the conceptual understanding and practical application of sustainability in the design process, this research provides strategic lines into designers’ decision-making processes, highlights barriers to sustainable practice, and underscores the importance of design education. The study contributes to academic debate and identifies opportunities for advancing sustainable practices and circularity in the textile and fashion industry, in alignment with the Sustainable Development Goals, especially SDGs 9, 12, and 13, to transform the current industrial and consumption models. Full article

The textile industry is facing increasing pressure to improve its sustainability performance across environmental, economic, and social dimensions. A substantial share of textile production relies on polymer-based fibers, such as polyester, polyamide, and acrylics, whose production, use, and end-of-life management raise significant sustainability challenges. In this context, life cycle-based assessment tools have become essential for supporting informed decision-making and guiding the transition toward more circular textile systems. This review critically examines the application of Life Cycle Assessment (LCA), Life Cycle Costing (LCC), and Social Life Cycle Assessment (S-LCA) within the textile sector, with a specific focus on polymeric textile materials and circular economy strategies. The analysis highlights the strengths and limitations of each methodology, emphasizing persistent challenges related to system boundary definition, data availability and quality, methodological heterogeneity, and limited comparability across studies. Particular attention is given to how methodological choices influence the robustness and interpretability of sustainability outcomes, especially when assessing circular solutions for polymer-based textiles. The review reveals that, despite their conceptual complementarity, LCA, LCC, and S-LCA are often applied in a fragmented manner, limiting their integration into holistic sustainability assessments. Overall, this work underscores the need for greater methodological alignment and integrated frameworks to enhance the decision-making relevance of life cycle-based tools and to effectively support sustainable and circular transitions in the textile industry. Full article