Topic Covered
Introduction
IoT has a lot of applications in the textile manufacturing industries, from the bale opening of cotton or raw material to the finished cloth or fabric. From detection of fiber characteristics to optimization of blend processing, storing and processing data using IoT can help in reducing the variations in the final product. IoT integration in spinning and weaving machines can improve process optimization and reduce defects. collecting data and Monitoring intermediate processes from the blow room to the Ring Frame can aid in improving the standard, reducing processing time, manpower, documentation work, and machine downtime, as well as increasing production and lowering costs. This real-time monitoring of machine data can provide real-time visibility of the process. It can also aid in the rapid discovery of machine defects, extending the life of the machine. Another feature of this IoT is automatic fault detection of textile products; it may also be used to measure a worker’s efficiency, strengths, and weaknesses. From automatic color matching (Datacolor, for example) to automatic sewing machines, digital printing, and floor space management, the Internet of Things opens up a world of possibilities for the textile industry. One component that might confirm a textile product’s sustainability claims is traceability. Yet, in this fragmented textile supply chain, obtaining effective traceability is quite challenging. The use of IoT and cloud computing can help with this specific feature.
Problem Statement
It has become mandatory for stock exchange-listed corporations to include ESG reports (sustainability reports) in their annual reports. Companies must either follow NVG rules or GRI disclosures to present the results that are affecting the relevant limitations to create this report. As we all know, advancements in AI have provided us with new chances for finding solutions to issues. The most crucial aspect of any report is the data, and ESG reports are focused on the organization’s data. As a result, data monitoring throughout the year becomes the most avoidable and haptic duty because of the large amount of paperwork effort and manpower required. monitoring and measuring them throughout the year is quite challenging.
