SoftWear Automation It’s a robotics company that wants to make T-shirts. “We want to make one billion shirts annually in the United States, and they are all made to order,” says SoftWear CEO Palaniswamy Rajan.
The company was launched in 2012 with the help of Georgia Tech Advanced Technology Development Center and contract with DARPA. Two years later, a prototype was built and put into operation. By 2017, work had begun on developing a production line that could mass-produce T-shirts. In the same year, the company concluded a deal with a Chinese clothing manufacturer to create a large group Production facility in Arkansas. But that deal fell through, and SoftWear is now focused on opening its own apparel factories.
The length of time it took to get to this point is not surprising. Machines have proven to be adept at many steps in making clothes, from Textile printing to me cut fabric And Folding and wrapping ready-made garments.
But it is known that sewing was difficult to automate, because textiles gather and stretch as they work. Human hands are skilled at keeping the fabric organized as it passes through the sewing machine. Robots are usually not skilled enough to handle the task.
SoftWear bots have overcome those hurdles. They can make a shirt. But making it as cheap as humans do in places like China or Guatemala, where workers earn a fraction of what they would make in the United States, will be a challenge, says Cheng Lu, professor of fashion and apparel studies at the University of Delaware.
SoftWear calls its Sewbots robotic systems. They are basically elaborate workbenches that combine sewing machines with complex sensors. The company enthusiastically keeps track of the details of how it works, but here’s the basics: The fabric is cut into pieces that will become part of the shirt: the front, back, and sleeves. These pieces are loaded into a working line where, instead of a person pushing the fabric through a sewing machine, a complex vacuum system stretches and moves the material. Cameras track the threads in each panel, allowing the system to make adjustments as the garment is being built.
But no two batches of cotton are exactly alike, and they often vary from one harvest to another; Differences in texture and dyes further complicate matters. Each change can entail a system reset, process interruption, and SoftWear must train its hardware to respond accordingly. “The biggest challenge we have had to get into the production system is the requirement to be able to operate 24/7 at high speeds and with a quality above 98 percent,” says Rajan.
Apparel factories produce more than 20 billion T-shirts annually, the vast majority of which are outside the United States. In order to make it possible to manufacture t-shirts in the United States, it must be cheaper than importing. But eliminating shipping costs and import duties isn’t enough to afford American workers paying to sew clothes. The Bureau of Labor Statistics says the average income of a sewing machine operator in the United States is no more than $28,000 a year. That’s about $13.50 an hour – way more than in the countries where many shirts are currently made. Lu, the Delaware professor, says wages in China for this type of work are roughly a third of wages in the United States, while in Guatemala it is less than a fifth of wages in the United States.
Focusing on shirts allows SoftWear to avoid another problem with automated sewing systems: switching from one type of clothing to another. A skilled team of people may sew men’s short-sleeved shirts one day and women’s jeans the next. Such transformations are more difficult for robots. The way we knit cotton polo together is very different from the way polyester pants are made. Developing a new line of work for cutting different fabric and sewing different stitches is complex and expensive. Once production is set up to make T-shirts, it will be difficult to quickly reconfigure the robots to make something else.
Since its initial funding, SoftWear has raised $30 million in project and grant investment — including a $2 million grant from the Walmart Foundation. Rajan says it will take tens of millions more to reach 1 billion T-shirts a year. To reach this goal, the company will need multiple facilities, each with its own Sewbots software and skilled workers to maintain. Rajan says Sewbot’s line of work can make a shirt every 50 seconds. At this rate, if run continuously, a single line of business could produce just over 620,000 T-shirts per year – which means it would take 1,607 Sewbots to operate continuously to reach a billion per year. A more realistic number, says Rajan, is closer to 2,000; So far, the company has achieved less than 50.
Robots inevitably raise suspicions of displacing people and destroying jobs. Rajan acknowledges that SoftWear will employ fewer people than a traditional T-shirt maker, but believes his company will create higher paying jobs for the people who will maintain the machines. “You want to develop the workforce, you want to train the workforce,” he says. “Our goal is to have skilled labor and fast and flexible production.”