AI TECH With the latest PicConnect platform, Picanol has aimed to digitize and harness the intuition of the expert weaver. Picanol
JUST in TIME Predictive Fulfilment is the Goal as AI Moves In By Adrian Wilson, IFJ International Correspondent
or a number of decades now, the supply chains of many high-tech industries have been highly structured and strictly managed top-down by the OEMs (original equipment manufacturers) they ultimately serve, to ensure both maximized efficiency and just-in-time sequencing. The automotive industry is a good example of this, explains Jason Kent, CEO of the British Textile Machinery Association (BTMA). “Control from the top over a fully visible supply chain extends not just to suppliers of individual components such as, for
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example, carpets, but even to the suppliers of the machinery on which these carpets are made,” he explains. “As a result, companies making machines on which automotive carpets are to be produced must not only be ISO 9001 certified, but also meet many other stipulations in areas such as power consumption and wastage.”
Restructuring Such a top-down structure could now be very rapidly established across the highly complex and fragmented textiles and fashion apparel supply chain Kent believes, in response to a raft of new legislative measures that are poised to be introduced,
Automotive OEMS like BMW Group have established a digital-first approach to their complex manufacturing systems across production networks, including real-time digital twin simulations to virtually optimize layouts, robotics and logistic systems. BMW
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initially in both the European Union and parts of the USA. This major restructuring will be enabled by ever-improving AI tools providing greater transparency, digitization and automation. “Having committed to ambitious sustainability goals by 2030, the majority of major apparel brands, as well as the corporations extensively using nonwovens and technical textiles in their products, are taking a much greater interest than ever before in their supply chains,” Kent emphasizes. “They are now examining each link in the complex succession of processes that result in their final products, in order to more fully understand how they are being made and exactly what they are made from. This new level of cooperation and transparency – stretching right back to the chemical and fiber producers – is to be welcomed, and can only lead to more sustainable practices across many areas, and not least in designing for circularity in the first place.” The term ‘predictive fulfilment,’ he adds, encapsulates everything AI – from generative design tools for enhancing creativity and streamlining initial process steps to quality and wastage control in manufacturing, assisted by predictive maintenance and machine learning.
