The Indian textile industry is one of the most distinctive, brimming with cultural traditions and techniques-driven. With the support of ever-changing technology, the sector has undergone a rapid transition over the years. The advanced adoption of technologies has improved machinery, quality evaluation, workforce efficiency, and data management for organizations.
SRF technical textile, a multi-business chemicals organization that manufactures industrial and specialty intermediates, is a leader in textile technology innovation. The organization is well-known for its adoption of modern technologies and is the first to welcome any new technological endeavors.
Continuing this outlook, the organization has initiated the digital road by concentrating on the production, process, and people. All components will enable the business to boost its market expansion.
“At SRF technical textile industry, we have always been an early adopter of the latest technology. We are focusing on upscaling predictability, sustainable operations, and a faster decision-making process. That’s the objective, and we will continue to dive towards being more digital,” said Bimal Puri, Chief Information Officer of SRF technical textile.
In the textile sector, product quality is pedestaled as the market king, stronger product quality results in a better reputation and consumer sales. Therefore, to maintain product quality, the business is focusing on AI, video, and predictive analysis.
Through leveraging AI, Puri says, the company wishes to upscale the standardization of the product quality and utilization rates.
“The organization has been actively utilizing the video analytics on fiber. It is a technique to detect visible damages on fabric with which the operation team can take quick action before it is done to the entire fabric. Thus, it saves the product from any future risks and cost losses,” he added.
Furthermore, predictive analytics is adopted to estimate product quality in the case of a disaster to enhance the assessment of the fiber. Puri expands and says, that predictive analytics may help in detecting the temperature of a product and alert them to a catastrophe if it is uncontrollable. Hence, it protects them from product damage and increases machine uptime while also reducing maintenance costs.
Uplifting employee efficiency and automation to save the machines from damages, an early warning system is activated on a real-time basis to detect machine damage and protect the equipment from downtime. He elaborates, “For example, If the motor of the machine is overheated or there is any problem, then the sensors signal about the cause and inform the team regarding the same which did not allow further harm to the machines”.
Along with placing product quality as a priority, increasing team productivity inside the organization is equally vital. Concentrating on this, the organization ensures that all decisions are based on up-to-the-minute data and real-time analytics. Puri cited those real-time analytics may help an employee in case of a manufacturing delay, by alerting them beforehand saving their time to perform alternate activities.
Additionally, implementing the shop floor automation or automated guided vehicles (AGV), will speed up the process and allow the personnel on the job to work more efficiently. AGV is computer-controlled and can load carriers that go across a facility’s floor without an onboard human, as the combination of software and sensor-based navigation systems directs their movement.
