Textile Manufacturing Industry Research Articles

Measuring operational efficiency of the textile industry using DEA technique: a study of the northern state of India

PurposeConsidering the role of the textile industry in the generation of employment and export in the Indian economy, it is important to comprehend the efficiency level in the operations of the textile units located in different states in India. In this light, the purpose of this paper is to examine the operational efficiency of textile manufacturing units in Haryana, a northern state of India.Design/methodology/approachThe study applies data envelopment analysis (DEA) approach consisting of input-oriented CCR and BCC techniques along with the return to scale technique for the analysis of five years of data from 2015–2016 to 2019–2020.FindingsThe results reveal that Haryana’s textile units have significantly underperformed operationally, with an average technical efficiency score of just 0.25 for five years, from 2015–2016 to 2019–2020. The yearly ratings of the overall technical efficiency of the selected textile companies include 0.20, 0.18, 0.18, 0.40 and 0.28; PTE scores are 0.43, 0.43, 0.55, 0.60, 0.62 and scale efficiency scores 0.54, 0.44, 0.29, 0.71, 0.38, respectively, from 2015–2016 to 2019–2020. On the other hand, average of 5.8 units are functioning at the constant return to scale, 10.2 units are at increasing return to scale and average of 45 units are functioning at decreasing return to scale (DRS). It is found that most of the companies are functioning at a DRS; to boost efficiency, these companies must reduce their input size since they are running at a DRS.Practical implicationsThe results of the current paper provide key insight into the inefficiency level of the textile manufacturing industry in the context of northern India. Industry professionals can take corrective measures based on these findings. Moreover, for investors and portfolio managers, knowing which companies are efficient and which are not will help them make better decisions. The study helps policymakers to frame appropriate policy guidelines to make the textile units in the state more efficient and competitive.Originality/valueTo the best of the authors’ knowledge, no study has been done so far on the operational performance of the textile industry in Haryana based on the DEA technique. So, it will contribute to the extant literature on the performance of the textile industry.

Circular Business Model Strategies Progressing Sustainability in the German Textile Manufacturing Industry

The EU Textile Strategy for Sustainable and Circular Textiles calls for circularity along the whole value chain of textiles. However, little is known about how circularity is already embedded in German manufacturing textile industries due to a lack of literature. Having conducted a survey study in December 2022 and January 2023, the results of 56 participating German manufacturing textile industries will be presented by applying descriptive statistics and qualitative analysis. The study shows that there is already an understanding of circularity including circular strategies in the German textile manufacturing industry. There are companies that apply the following circular business model strategies: upcycling and recycling, product-as-a-service, repair and reuse, and material innovation. Closed-loop supply chain companies are not yet prominent. Many manufacturing textile companies are not prepared yet for a circular transformation. Another finding is that the EU Strategy for Sustainable and Circular Textiles is so far insufficiently known by the respondents of the sample. A more structured provision of information or financial state support should be discussed.

The Impact of Perceived CSR on Employees’ Pro-Environmental Behaviors: The Mediating Effects of Environmental Consciousness and Environmental Commitment

Employees’ pro-environmental behaviors contribute to environmental sustainability. Drawing on social exchange theory, this research extends corporate social responsibility (CSR) literature by investigating the positive effect of perceived CSR on employees’ pro-environmental behaviors and exploring the mediating mechanisms of environmental consciousness and environmental commitment between perceived CSR and employees’ pro-environmental behaviors. Survey data were collected from 301 employees working in the textile manufacturing industry of Pakistan. The findings of this study demonstrate a positive direct impact of perceived CSR on pro-environmental behaviors. Moreover, environmental consciousness and environmental commitment mediated this relationship. Taken together, this study indicates that perceived CSR has three paths to impact employee pro-environmental behavior: direct effect, indirect effect via environmental consciousness, and indirect effect via environmental commitment. The contributions of this study include supporting social exchange theory and presenting pioneering evidence of environmental consciousness and environmental commitment mediating processes between perceived CSR and pro-environmental behaviors. This paper provides directions for future research and suggests practical implications for organizations.

Recent Developments in Materials and Manufacturing Techniques Used for Sports Textiles

In the recent era of development, the global market for the sportswear textile manufacturing industries has increased with the increase in consumption of active sportswear. The sportswear manufacturers not only focused on the market trends but also focused on material diversification with technology enhancement. The performance characteristics of active sportswear directly influence comfort level and athletic performance during sports activities. Different types of sportswear products require different performance characteristics. Appropriate moisture and heat management are the key factors for the endowment of the required physiological comfort level. In highly engineered textile-based sports goods, special characteristics are incorporated in the polymer/fibers/product manufacturing procedures/finishing techniques to obtain the maximum performance and comfort level. In this review paper current market trends, highly engineered polymers, fibers, fabrics, finishes, nanomaterials, and the recent developments in the manufacturing techniques of sportswear are illustrated.

Assessing Social Sustainability Performance in Textile Industry using Integrated Fuzzy Best-Worst Method and Fuzzy Inference System

The main purpose of the research primarily focused on the development of sustainable social indicators and to test their usefulness and applicability in the Nigerian textile sector in terms of social performance. The integrated Fuzzy Best-Worst method (FBWM) and Fuzzy inference system (FIS) was presented to aid in the evaluation of these indicators. The outcomes demonstrate that employee rights received the highest score of 0.206 in the study. Employee rights are regarded as the most crucial and critical factor. Furthermore, among the indicators, fair salary has the highest global weight. The case company's sustainability performance index was 0.248, which was in the "poor" performance category. A case study was conducted in a Nigerian textile industry to demonstrate the effectiveness and efficiency of the proposed method. These findings will assist managers and policymakers in the textile manufacturing industry, particularly in emerging economies such as Nigeria, in developing strategies to lay the groundwork for social sustainability and transition to truly sustainable textile manufacturing industry.

CACFNet: Fabric defect detection via context-aware attention cascaded feedback network

Fabric defect detection plays an irreplaceable role in the quality control of the textile manufacturing industry, but it is still a challenging task due to the diversity and complexity of defects and environmental factors. Visual saliency models imitating the human vision system can quickly determine the defect regions from the complex texture background. However, most visual saliency-based methods still suffer from incomplete predictions owing to the variability of fabric defects and low contrast with the background. In this paper, we develop a context-aware attention cascaded feedback network for fabric defect detection to achieve more accurate predictions, in which a parallel context extractor is designed to characterize the multi-scale contextual information. Moreover, a top-down attention cascaded feedback module was devised adaptively to select the important multi-scale complementary information and then transmit it to an adjacent shallower layer to compensate for the inconsistency of information among layers for accurate location. Finally, a multi-level loss function is applied to guide our model for generating more accurate prediction results via optimizing multiple side-output predictions. Experimental results on the two fabric datasets built under six widely used evaluation metrics demonstrate that our proposed framework outperforms state-of-the-art models remarkably.

Business Development Strategy for CV Hadi Corp Convection in the Domestic Market with a Canvas Business Model Approach

The textile manufacturing industry in Indonesia grew 15 percent, but total exports fell 2.87 percent to 12.84 billion dollars in 2019 compared to 2018 of 13.22 billion dollars. The TPT industry can be divided into several sectors, one of which is the apparel sector. The apparel sector also has an important GDP contribution for Indonesia. In textile product commodities, there is competition with imported quality. Textile products find it difficult to compete in the domestic market due to inferior quality to imported products, both in terms of materials, sewing, styles and finishing which are not neat and not standardized and their availability has not met market demand. In dealing with changes in the external and internal environment CV. Hadi Corp needs a business model mapping to determine the company's business conditions to be able to create breakthrough innovations for the company's business development for the domestic market. Hadi Corp needs a business model mapping to determine the company's business conditions to be able to create breakthrough innovations for the company's business development for the domestic market. The research objective is to analyze the current CV Hadi Corp Canvas Business Model, analyze the strengths, weaknesses, opportunities, and threats (SWOT) of CV Hadi Corp currently based on the 9 elements of the Canvas Business Model and Design the CV Hadi Corp Repair Canvas Business Model as an alternative planning future business strategy. Data processing uses the Canvas Business Model and SWOT and the Blue Ocean Strategy. The results showed that the Improvement of the CV Hadi COrp Canvas Business Model based on alternative strategies resulted in several targets and development for each element including: 1) Business to business customers; 2) product innovation; 3) updating the website to improve online promotion; 4) Conduct site visits to customers and customer assessment of company services through customer satisfaction surveys; 5) Investment in technology or new resources and training; 7) Customers for tool rental and design services, market surveys and manufacturing of innovative products. The target of improving each element in the canvas business model aims to expand the potential value proposition that can be offered by CV Hadi Corp. Keywords: TPT, SWOT, Business Model Canvas, Blue Ocean Strategy, CV Hadi Corp

A context-aware progressive attention aggregation network for fabric defect detection

Fabric defect detection plays a critical role for measuring quality control in the textile manufacturing industry. Deep learning-based saliency models can quickly spot the most interesting regions that attract human attention from the complex background, which have been successfully applied in fabric defect detection. However, most of the previous methods mainly adopted multi-level feature aggregation yet ignored the complementary relationship among different features, and thus resulted in poor representation capability for the tiny and slender defects. To remedy these issues, we propose a novel saliency-based fabric defect detection network, which can exploit the complementary information between different layers to enhance the representation features ability and discrimination of defects. Specifically, a multi-scale feature aggregation unit (MFAU) is proposed to effectively characterize the multi-scale contextual features. Besides, a feature fusion refinement module (FFR) composed of an attention fusion unit (AFU) and an auxiliary refinement unit (ARU) is designed to exploit complementary important information and further refine the input features for enhancing the discriminative ability of defect features. Finally, a multi-level deep supervision (MDS) is adopted to guide the model to generate more accurate saliency maps. Under different evaluation metrics, our proposed method outperforms most state-of-the-art methods on our developed fabric datasets.

Energy Utilization and Saving Opportunities in Process Industries: Case Study of Textile Manufacturing Industry in Kenya

The industrial sector is seriously threatened by high energy costs brought on by inefficient energy use. Energy, together with labor and raw materials, make up the majority of production costs in the textile industry. As a result, the only real way for the textile industry to turn a profit and maintain its competitiveness is to reduce its energy costs through energy conservation measures and energy management strategies. The main objective of the study was to investigate energy utilization in textile manufacturing plant and identify energy saving and conservation measures that help reduce energy costs. In the current work, energy investigation was carried out to determine performance of high energy consuming utility systems and equipment such as compressed air systems, boilers, motors, lighting systems and steam distribution systems. Boiler flue gas analysis test, air compressor air leak test, heat loss analysis for steam distribution system, motor load assessment and load variation trends in air compressor were done. Energy utilization analysis showed that high electricity consumption occurs in spinning (48%), followed by weaving (26%) and wet processing (22%). Statistical analysis of energy consumption in spinning, weaving and wet processing showed linear relationship between production and energy consumption with correlation coefficients (R2) of 0.782, 0.708 and 0.637 respectively which reveals that there continues to be a large potential of energy efficiency across all the major textile manufacturing processes in the plant. The study found potential savings in electric energy to be approximately 367,784 kWh/year, wood fuel savings 1,219 tones/year and furnace oil savings to be 22,275 L/year. The results displayed 31.6% overall energy cost saving potential with an average simple payback period of 0.5 years on the investigated high energy consuming utility systems and equipment. In conclusion, significant energy savings in the sector might be attained by implementing free or inexpensive investments including sealing air and steam leaks, insulating bare pipes, and properly drying wood fuel.

Will the imposition of carbon tariffs enhance or worsen the carbon performance of China's export industries? A reality check based on 28 manufacturing industry segments.

Carbon tariffs are directly linked to carbon performance and have an impact on export sectors. This paper examines the relationship between carbon tariffs and carbon performance based on China's manufacturing sector, helping to visually quantify the impact of carbon tariffs and to adopt more favourable strategies to address the impact. This paper uses data from 28 manufacturing industry segments in China from 2009 to 2019, estimating carbon performance using an SBM model incorporating non-desired outputs. The panel Tobit model is also used to explore the driving role of carbon tariffs and related variables on carbon performance. The results show the following: First of all, China's manufacturing carbon performance is generally on an upward trend but is mainly driven by improvements in the light textile and machinery manufacturing industries. Secondly, in terms of drivers of carbon performance, the imposition of carbon tariffs will increase the carbon performance of China's manufacturing sector. Furthermore, R&D investment is positively correlated with carbon emission performance. The significant positive impact of export dependence is manifested in the light and textile industry. Energy intensity has a significant positive impact on the textile industry and a significant negative impact on the resource processing industry. Environmental regulations have a negative impact on the light textile industry. China should optimize the industrial chain of resource processing industry. At the same time, China should increase R&D investment in emission reduction and product upgrades, encourage the export of light and textile industrial products, increase the import of resource processing industrial products. Also, the government should formulate environmental regulatory policies that are close to the nature of the industry.

Biocatalytic potential of Brassica oleracea L. var. botrytis leaves peroxidase for efficient degradation of textile dyes in aqueous medium

Dye-contaminated wastewater discharge from textile and dye manufacturing industries is reported as a world worse water polluter due to the toxic and mutagenic behavior of dyes. Peroxidase, one of the key enzymes of oxidoreductases, is widely distributed in nature and has been currently exploited in industries for various applications. Widespread applications of peroxidases are associated with their nonspecific nature towards a wide spectrum of substrates such as phenols, aromatic amines, pesticides, antibiotics, and synthetic dyes. The present study explored the potential of ammonium sulfate precipitated partially purified Brassica oleracea L. var. botrytis leaves peroxidase for degradation of reactive textile dyes Remazol Turquoise Blue 133 G and Drim Red CL4BN. Various physico-chemical parameters such as pH (2–9), temperature (20–70 ℃), enzyme activity (3–24 U/mL), concentrations of H2O2 (0.4–1.4 Mm) and dye (10–100 mg/L) were optimized for enzymatic decolorization of both dyes’ solution. Studies revealed that maximum degradation (95%) of Remazol Turquoise Blue 133 G with peroxidase was achieved with 25 mg/L of initial dye concentration, in the presence of 0.8 mM hydrogen peroxide with 45 min of incubation time, at pH 3, 4, and 5, and 70 °C. Maximal decolorization (97%) of Drim Red CL4BN was obtained at pH 2.0, in 10 min of incubation time at 45 ℃ using o-dianisidine hydrochloride as a redox mediator. In conclusion, the findings illustrate the prospect of Brassica oleracea peroxidase to remediate dye pollutants and dye-based industrial effluents in a green technology theme.Graphical abstract

Chemometric analysis and risk assessment indices to evaluate water and sediment contamination of a tropical mangrove forest

BackgroundMangroves are among the utmost productive forest residing at the interface amid terrestrial and marine environments. They play an essential role in carbon storage, nutrient cycling, and the marine food web's sustenance. Rapid land use and land cover changes have severely affected these ecosystems worldwide. Material and methodsThe present study was carried out in the mangrove forest of Kachchh district in Gujarat. This area is one of India's most swiftly growing industrialized coastal regions, embracing several ports, thermal power plants, salt production units, textile, petrochemical, cement, and fertilizer manufacturing industries. Therefore, this study aims to investigate nutrients and trace metal contamination status in mangroves. A total of 25 physicochemical parameters for water and 16 parameters for surface sediment were analysed using standard protocols. Trace metals were determined using Flame Atomic Absorption Spectrophotometry. Results and discussionImmensely higher chloride (20,116 ± 1929 mg L −1) and sulfate (2315 ± 679 mg L −1) concentrations were observed, suggesting high seawater and saltpan brine mixing in this coastal region. High tidal influx and arid-climate of the area are responsible for higher salinity (52.7 ± 5.0 PSU) in water. Cluster analysis depicts that sites M2, M3, M5, and M6 incorporate higher nutrient levels, indicating the anthropogenic origin of nutrients. The results depict the role of granulometric composition in controlling carbon, nitrogen, sulfur, and metal biogeochemistry in sediments. Results showed that mean trace metal (Fe, Cu, and Ni) content in sediment was higher than the world average shale value, indicating anthropogenic sources. Geo-accumulation index (Igeo) and Enrichment factor (EF) indicates sediment samples were moderately polluted with Cu, Zn, and Ni. ConclusionThe findings revealed that anthropogenic activities have affected the hydrogeochemistry of mangroves in the studied region, which will eventually impact flora and fauna. Therefore, there is a pressing necessity to implement pollution control, mitigation, and restoration policies for the endurable management of the mangroves.

Characteristics, Sources, and Risk Assessment of Perlyfluoroalkyl Substances in Surface Water and Sediment of Luoma Lake

Through the investigation and detection of the surface water and sediments of Luoma Lake, the structure and occurrence characteristics of PFASs (perlyfluoroalkyl substances) in the two types of media were analyzed, and the principal component analysis method was used to analyze the characteristics of such substances in the surface water. The source was analyzed, and the potential health risks of such substances were evaluated using the risk quotient method. The results showed that a total of 13 PFASs were detected in the surface sediments of Luoma Lake, and one more species was detected in the surface water (PFTeA); ρ(ΣPFASs) in the surface water ranged from 46.09 to 120.34 ng·L-1, and ω(ΣPFASs) in sediments ranged from 2.22 to 9.55 ng·g-1. PFPeA was the major component in surface water, and the mass fraction of PFPeA was 38%. PFBA was the major component in sediment, and the mass fraction of PFPeA was 61%. The multi-media PFASs in Luoma Lake were mainly short-chain substances; the high concentration area of PFASs in the surface water of Luoma Lake was concentrated and distributed at the mouth of the northern rivers. Its concentration showed a decreasing trend from north to south, and the content of PFASs in the sediments showed a decreasing trend from southwest to northeast. The distribution of ΣPFASs, PFBA, and PFOS in the sediments of Luoma Lake and the TOC content in the sediment were related; the principal component analysis showed that the PFASs in the surface water of Luoma Lake were mainly from textile flame retardant, rubber product emulsification, food packaging processes and paper surface treatment industries, the metal electroplating industry, and leather and textile manufacturing industries. PFASs in the surface water of Luoma Lake were at a relatively low health risk level.

Correlation between Workers’ Characteristics and Workplace Noise with Subjective Hearing Disorders in Textile Industry

Introduction: The textile manufacturing industry has a noisy work environment as a result of the weaving machines which have a noise intensity exceeding the threshold value. Noise can cause complaints of hearing disorders. Other factors that influence hearing disorders are agework period, and the use of ear protection equipment. This study aims to analyze the relationship between age, work period, the use of ear protection equipment, and noise intensity on complaints of subjective hearing disorders in the AJL Weaving Department of Textile Industry. Method: This research was a descriptive observational study with a cross sectional approach. Data were obtained by measuring noise intensity and distributing questionnaires to workers. Respondents in this study amounted to 45 people who were the total population of weaving operators and maintenance workers in the AJL Weaving Department of Textile Industry. Results: The results of this study indicate that age and work period have a sufficient relationship with complaints of subjective hearing disorders, while the use of ear protection equipment has a weak relationship with complaints of subjective hearing disorders, and noise intensity has a strong relationship with complaints of subjective hearing disorders. Conclusion: Individual characteristics only have a weak to moderate relationship with subjective hearing complaints. Meanwhile, exposure to noise intensity has a strong relationship with subjective hearing complaints.

One-step electrospinning PCL/ph-LPSQ nanofibrous membrane with excellent self-cleaning and oil-water separation performance

The ladder-like phenyl polysilsesquioxane (ph-LPSQ) was synthesized by sol-gel method. Then the Polycaprolactone/ladder-like polysilsesquioxane (PCL/ph-LPSQ) nanofibrous membranes were prepared via one-step electrospinning technique. The addition of ph-LPSQ was proposed to improve the hydrophobic and thermal properties of PCL membranes. Scanning electron microscopy (SEM) and atomic force microscopy (AFM) images showed the PCL/ph-LPSQ composite fibers had porous rough surface structure, which was caused by solvent evaporation induced phase separation, respiration diagram and silicon segment migration. The composition of PCL/ph-LPSQ membranes was characterized by using fourier transform infrared spectroscopy (FT-IR), x-ray photoelectron spectroscopy (XPS) and energy dispersive x-ray spectroscopy (EDS). Compared with pristine PCL membranes, the water contact angle and initial degradation temperature for PCL/ph-LPSQ membranes were increased to 158.0° and 355 °C, respectively, from the corresponding 133.6° and 340 °C. The superhydrophobic PCL/ph-LPSQ membranes exhibited excellent self-cleaning, anti-fouling and oil-water separation performance. Driven by gravity alone, the oil-water separation efficiency remained as high as 98% after ten cycles. More importantly, the as-prepared membrane showed good stability in 80 °C, 1 M acid, alkali and salt solutions. Considering the comprehensive properties of PCL/ph-LPSQ membranes, it might be a promising nonwoven fabric material in many fields like textile manufacturing industry. • A facile and ingenious method of preparing super hydrophobic nanofibrous membrane was developed in this paper. • The thermal and hydrophobic properties of the composite membrane were improved with the addition of organo-silicon polymer. • The as-prepared membranes exhibited excellent self-cleaning and oil-water separation performance.

Thermal and Sound Insulation Performances of Building Panels Produced by Recycling Waste Fibres of Yarn Factories

Waste recovery is very important issue due to having vital effects on sustainability of economy and environment health. Recycling of materials such as textiles, plastics, glasses, papers and metals instead of storing, burying or burning results a reduction in raw material demands of industry. This means also that a reduction in amount of money, time and energy spent on to obtain raw materials. From this point of view, the main purpose of this study was determined as the production of textile surfaces with high waste fiber content by recycling textile fiber wastes in sizes that cannot be used in the textile manufacturing industry again. In this sense, various composite plates that can be used for sound and heat insulation on the exterior and interior surfaces of the buildings were produced by using unconventional methods from the waste fibers varying between 0.1-25 mm lengths. Another aim of the study was to produce widely used panels at low costs in order to compete with commercial products. The effect of changed parameters such as density, fiber type, waste fiber ratio and aluminum foil layer addition were investigated. As a result of the tests, it was observed that the thermal conductivity coefficient values of the all produced composite panels varied between 0.033-0.038 W/mK, and the sound transmission loss values between 24.2-32.6 dB. For further studies, the produced samples also showed that they are convenient to innovation in the lights of results.

Research on the implementation method of loom monitoring

A loom monitoring system was designed and developed to realize monitoring loom in both industrial field and remote network environments and to meet the on-site workers’ convenient operation and centralized management of enterprises. This article uses the touch screen as the main carrier of the field system and cooperates with configuration technology and expert system to realize fault diagnosis. And this article uses the B/S architecture as the remote system cloud platform network architecture which builds the Redis database and Nginx server operating environment, and the front-end technology such as HTML5 is used to design a web client interface to meet the functional needs. This implementation method has three advantages: First, it breaks the traditional way of mechanical button matching with touch screens in the textile manufacturing industry; second, it can quickly find out the reason for loom failure; and third, it lifts the regional restrictions, thus improving the intelligence and information level of textile machinery and equipment.Article HighlightsThis monitoring system combines configuration technology with computer technology to realize monitoring in both industrial fields and remote environments. Industrial site workers quickly and directly operate the loom through the on-site touch screen. Enterprise management personnel centrally manage the loom through remote means. Therefore, the system is convenient for different types of users in the enterprise.The industrial field monitoring system has comprehensive functions and friendly interface operation, which realizes the comprehensive monitoring and operating parameter setting of each link of the loom production. It can also meet functional requirements such as fault alarm and debugging and maintenance.The use of the cloud platform and other technologies to achieve remote monitoring of the loom, breaking through the geographical restrictions. It is possible to log in to the remote system anytime and anywhere to monitor the running status and production information of the loom, which also provides convenience for later maintenance and upgrades.

Long-term trends of fluorotelomer alcohols in a wastewater treatment plant impacted by textile manufacturing industry

Fluorotelomer alcohols (FTOHs) are important precursors and substitutes of perfluoroalkyl carboxylic acids (PFCAs). This study investigated the long-term trends of FTOHs in a municipal wastewater treatment plant impacted by textile manufacturing industry (T-WWTP) in Wuxi city from 2013 to 2021. For comparison, four domestic wastewater treatment plants (D-WWTPs) were also selected for the investigation. The total concentrations of FTOHs, which were 9.8–43 ng/L, 5.9–29 ng/L and 10–50 ng/g in influent, secondary effluent, and sludge samples from the T-WWTP, were significantly higher than those of the D-WWTPs (p < 0.01). The significant correlation between decrease of mass loads for FTOHs and the increase for PFCAs was observed, suggesting the potential biotransformation of FTOHs to PFCAs. Concentration variation in FTOH concentrations was observed for the T-WWTP, which was in accord with the variation in annual output of textile products in Wuxi city (p = 0.005). The predominance of 8:2 FTOH in the influents of T-WWTP between 2013 and 2016 switched over to 6:2 FTOH in 2020–2021. This work highlighted the textile manufacturing industry as a significant discharge route for FTOHs to municipal WWTP, as well as the dramatic change in the usage of FTOHs in the textile manufacturing industry in Wuxi.

Manufacturing Advantage: War, the State, and the Origins of American Industry, 1776–1848

Manufacturing Advantage: War, the State, and the Origins of American Industry, 1776–1848

Effective degradation of azo dye from textile wastewater by electro-peroxone process

Color-producing chemicals emitted from many sources, such as textile or dye manufacturing industries, are a significant concern worldwide. The present study focuses on the electro-peroxone (EP) process for decolorizing a synthetic azo dye, C.I. Reactive Black 5 (RB5). Findings suggest that the EP process is more effective for dye degradation than ozonation and electrolysis. The EP process resulted in 100% decolorization after 60 min of contact time under optimum testing conditions such as pH 7, applied current 300 mA, and sulfate concentration 3.55 g L−1. Based on the findings of the primary investigation, EP treatment of real textile effluent was carried out and 2 h of EP treatment resulted in 99% decolorization and 74%total organic carbon (TOC) removal. As an outcome, the EP process can treat textile wastewater in a cost-effective and environmentally friendly manner.