Detecting Misalignment for Efficient, Sustainable Fabric Finishing
Finishing is crucial to the textile manufacturing process, giving luxury fabrics unique properties such as their shine, softness, or even functions like insect repellence or flame retardance. It also comes with a margin for error, where small differences in tension across the fabric can lead to distortion that proves costly and wasteful.
WT Johnson is a global leader in luxury woollen and worsted fabric finishing, working with manufacturers and brands from all over the world. Building on its relationships with Future Fashion Factory researchers, the historic company is developing a new system that can spot weft misalignment as it happens, giving the skilled team opportunities to correct the issue, ensure consistency, and minimise waste during a key manufacturing process.
One of the key criteria that buyers assess is the straightness of the weft – the yarns that are woven horizontally through the fabric. Any imbalance in tension across the fabric as it goes through machines during finishing can lead to the weft being distorted: if it is not completely straight and at a right angle to the vertical yarns (the warp), the whole batch of fabric can fail a quality assessment.
Although WT Johnson’s skilled team monitor the fabric closely as it enters each machine, there is still a margin for error. On inspection as much as 1.5% of the company’s production is stopped as a result of weft misalignment, which then requires significant time, energy and cost to fix.
“Getting weft alignment right first time is the biggest day-to-day problem we face,” explains Alan Dolley, Technical Manager at WT Johnson.
“Every dyer and finisher in the world has this problem and re-processing fabric can be disastrous: it causes production delays and uses energy, water and chemicals. There is a big market opportunity for an effective solution.”
To explore a new system that could minimise the waste and cost implications of weft misalignment, WT Johnson built on its existing relationships with academic partners at the University of Leeds.
Collaborating with sensing expert Dr Zhiqiang Zhang from the university’s School of Electrical Engineering and textile technologist Professor Ningtao Mao, who worked with WT Johnson on a Future Fashion Factory-supported project last year, the team developed a prototype system to detect the misalignment as it occurs.
Zhiqiang has worked extensively on wearable sensing and signal processing, particularly for medical applications. He says the same principles of data processing apply to working with textiles, though working closely with the WT Johnson team during site visits was crucial to gain an understanding of their specific needs and challenges.
“The only difference is in the image data itself,” he says, “But it is processed in a similar way. We realised that the first step was to have a system that could ‘see’ the fast-moving misalignment in the production line and alert the machine operator to the problem.”
The team developed a system that colour-codes images from a camera on the production line in real time. As the machine operator monitors this footage, they can immediately see when the weft is falling out of alignment as the colour shifts from green to orange to red – giving them time to stop the machine and correct the error.
Alan, Zhiqiang and Ningtao hope to use this proof of concept as a stepping stone to a more efficient solution which could stop the machine automatically, or even be connected to a new system that would automatically correct the error. By giving WT Johnson’s team the chance to prevent distortion before they need to re-process the fabric, the new system can help to minimise waste in the process, reducing the amount of water, energy and chemicals used to give fabrics the perfect finish.
“This is a very real challenge that we would never solve without academic support, and which academics couldn’t tackle without the benefit of our industry experience,” says Alan.
“A whole sector of the textile industry is dedicated to weft straightening and nobody is doing it this way. The principle is great: now we need to take it further.”