The Covid-19 pandemic has changed lives and industries across the world, accelerating a shift in consumption patterns and manufacturing processes that were already on its way. Amid this unprecedented crisis, work processes are now being carried out digitally, to gain efficient business growth and eventually to reduce risk.
According to McKinsey report- State of Fashion 2021, the challenging environment born out of the events of 2020 will linger into 2021, with global fashion sales projected to be below 2019 levels by as much as 15 percent in the Later Recovery scenario. It added that a full recovery of global fashion sales to pre-crisis levels will not come until the third quarter of 2022 at the earliest.
The textile industry is no exception to this change and it has been gradually adopting artificial intelligence (AI) and automation to transform the production, manufacturing process, and customer relations. They are using different types of AI-based expert systems, neural network, fuzzy logic, genetic algorithm and other approaches in the process of manufacturing. The industry is aiming to embrace robotics, and AI to transform the way they function, eventually resulting in lower labour and manufacturing costs, and speedy deliveries.
With AI taking over the entire process, the systems have been streamlined in a way that human involvement has been reduced to the bare minimum and the process has become appreciably more efficient.
Let’s begin with yarn manufacturing. Currently, AI is being used in each operation, from the blow room to carding, painting, lap shaping, combing, speed frame, ring spinning, winding, conditioning, to packaging — it has fully transformed the manufacturing process. The automation of this stage has not only sped the process but has proven to be cost-effective as well. AI has cut the error rate in estimating wool grading by as much as 60%, resulting in improved cotton grading.
So far, trained staff across the industry opted for physical testing to ensure quality products. Whereas with cutting-edge technology, AI has sped up the process and ensured consistency and accuracy. Devices such as the Autoburst 70, TPI Tester, Moisture Meter Digital, Digital Tachometer CE, and Stroboscope are being used to make the process more efficient. While, raw cotton properties such as length intensity, MIC, colour, and uniformity are checked using instruments like the Premier Art-2.
Supply Chain Management and Merchandising
AI tools not only detect anomalies in the production phase but can also be used to automate transportation and packaging in the textile industry. AI applications can be found throughout supply chains, from the manufacturing floor to front-door delivery. Today several shipping companies are using Internet of Things (IoT) devices to gather and analyse data about goods in shipment and track mechanical health.
In order to maintain a flow of materials from manufacturers to retailers, smooth supply chain management is a significant stage. It demands huge storage spaces, better warehouse management, product segregation, and better communication. AI can provide all these benefits through robotics, RPA, machine learning, IoT, and other technologies. These special tech tools can also be leveraged to analyse data, personalise customer experiences, track customer behaviour, and predict market trends.