Ammonia recovery and fouling mitigation of hydrolyzed human urine treated by nanofiltration and reverse osmosis

Ammonia is a critical compound due to the numerous industry products which rely on its production such as fertilizer, refrigerant gas, and textile manufacturing. Ammonia is also a pollutant in...

IMPACT OF INDUSTRIAL FREIGHT FLOWS ON THE OVERALL TRAFFIC IN SURAT CITY, INDIA

Surat is one of the major textile manufacturing hubs in India, having 40% of the synthetic fabric produced in the country. The textile industry in the city has witnessed tremendous growth in the last decade, leading to many transportation-related changes within it. Textile manufacturing has different phases like weaving, processing, value addition and trading or distribution. These phases are located as clusters or pockets in different parts of the city. The scattered nature of the industry generates numerous freight trips. This study focuses on characterizing and estimating textile freight trips in the city. Establishment survey data was collected from production units located in various clusters. A multi-linear regression model for freight trips generated using the quantity of cloth produced was developed for the estimation of the total textile freight trips. Thus, this study will help the planner identify the strategic location of the textile and its allied industries as well as for freight infrastructure in the city. More so, it would help in understanding the impacts of textile freight movement on the city’s overall traffic.

Cloud-Based Analytics Module for Predictive Maintenance of the Textile Manufacturing Process

Industry 4.0 has remarkably transformed many industries. Supervisory control and data acquisition (SCADA) architecture is important to enable an intelligent and connected manufacturing factory. SCADA is extensively used in many Internet of Things (IoT) applications, including data analytics and data visualization. Product quality management is important across most manufacturing industries. In this study, we extensively used SCADA to develop a cloud-based analytics module for production quality predictive maintenance (PdM) in Industry 4.0, thus targeting textile manufacturing processes. The proposed module incorporates a complete knowledge discovery in database process. Machine learning algorithms were employed to analyze preprocessed data and provide predictive suggestions for production quality management. Equipment data were analyzed using the proposed system with an average mean-squared error of ~0.0005. The trained module was implemented as an application programming interface for use in IoT applications and third-party systems. This study provides a basis for improving production quality by predicting optimized equipment settings in manufacturing processes in the textile industry.

Ichalkaranji: India’s Manchester needs to weave magic

Supplementary materials The case includes links to video clips on textile and apparel manufacture to familiarize students with the textile manufacturing process. The case also provides links to audio and video clips of the case protagonist discussing the strengths and weaknesses of the cluster at IK. Learning outcomes The case offers opportunities for the learner to analyze the situation from three cases as follows: industry, cluster (broadly location) and firm. Specific teaching objectives are as follows: How to identify and analyze the drivers of competitiveness of a cluster. Assess the strength of clusters using Porter’s Diamond framework. Map the linkages between players of a cluster as follows: across firms, industries and public organizations. Benchmark and compare clusters to identify opportunities for upgrading competitiveness. Case overview/synopsis The case describes the challenge facing Mr Nikunj Bagdia, the owner and chief executive of Ken Enterprises Private Limited (Ken), a textile manufacturing unit located in the town of Ichalkaranji (IK), in October of 2019. IK boasts the largest number of cutting-edge air-jet looms in India and Ken is IK’s largest exporter of woven textile fabrics. However, IK lags the textile and apparel manufacturing cluster of Tiruppur, in another region of the country. The case enables a microeconomic analysis of the business environment of industrial clusters and a cluster mapping exercise, which helps identify opportunities for enhancing IK’s textile cluster. As the case closes, Nikunj is trying to prioritize opportunities that could emerge from the analyzes. Complexity academic level Masters/MBA level courses on competitiveness, strategy for economic development and microeconomics of competitiveness. Subject Code CSS 11: Strategy.

Tekstylia i pieczęcie. O relacjach pomiędzy produkcją włókienniczą a praktykami stemplowania w Grecji epoki brązu oraz o zupełnie nowych danych z odcisków glinianych pieczęci

This contribution discusses the evidence of textile impressions preserved on the undersides of clay sealings from Bronze Age Greece. A collection of modern casts taken from these sealings, stored in the Corpus der minoischen und mykenischen Siegel in Heidelberg, is currently being analyzed by the author. The assumed reliability of textile impressions as a source of knowledge about the qualities of actual textiles and raw materials used to produce them has been verified by a series of archaeological experiments and comparative analysis of modern raw materials of various origin. Results ofthe analysis of 199 casts from two Aegean sites: Lerna in Argolid and Phaistos on Crete, have provided new evidence for technical uses of textile and organic products in the daily storage routine and sealing practices, as well as for the specific parameters of threads, cords, and fabrics impressed on clay. Due to the relatively large number of textile imprints, it is possible, for the first time, to make site-specific comparisons of textile production on the basis of products and to tracktechnical developments in textile manufacturing throughout the Aegean Bronze Age.

Structure-Function in Helical Cardiac Musculature Using Additive Textile Manufacturing

For more than fifty years, it has been hypothesized that the helical alignment of the heart gives rise to its mechanical function. Testing this hypothesis in an engineered environment is difficult, as the fine spatial features and complex three-dimensional (3D) structures of the cardiac musculature are challenging to reproduce using current biofabrication techniques. Addressing this, here we report a new form of additive textile manufacturing, Focused Rotary Jet Spinning (FRJS). FRJS allows for the rapid manufacturing of micro/nanofibers with controlled alignments. Using this method, we manufacture 3D models of the left ventricle, showing that helically aligned scaffolds display increased strain uniformity, axial shortening, cardiac output, and ejection fractions as compared to circumferential models. We then demonstrate how FRJS can enable the assembly of a full-sized model of the human heart’s musculature. This work experimentally confirms that ventricular alignment plays a critical role in ensuring healthy cardiac performance.