Tajima set to launch AI Embroidery Machines on Jan ’22 – Solution for Shortage of labour at production Sites
15 January 2021: While society has been going through great technological progressions like digitization in recent years, the apparel-manufacturing industry has come to face emerging issues associated with the labor shortage caused by the global COVID-19 outbreak.
Tajima Industries Co., Ltd, Japan, a leading embroidery machine manufacturer striving for automation of embroidery, production network management, and promotion of smart embroidery businesses, is set to launch a new embroidery machines on January 22, 2021, as the brand-new “TMEZ-KC Series” models. The company is centering its corporate focus around automation of the machine embroidery production process by equipping machines with its proprietary AI technology “i-TM,” designed to automate the embroidery finish, as a solution to the manufacturing labor shortage. The i-TM models are especially suitable for embroidering on ready-made products with mixed levels of fabric thickness and elasticity, such as caps, T-shirts, patches, shoes and socks.
“i-TM” stands for “Intelligent Thread Management.” In machine embroidery, patterns may be stitched in all different directions and the stitch length may vary even in a single design, making machine embroidery one of the most difficult types of sewing. The company has successfully algorithmized the embroidery finish patterns acquired through many years of experience to produce “i-TM.” This AI technology analyzes the stitch-by-stitch sewing direction and fabric thickness to compute the appropriate amount of upper thread feed for the next stitch and makes proper adjustments to stitches so that the embroidery finish that is considered to be “good” can be achieved in a stable manner.
The i-TM models automatically adjust the embroidery finish to achieve good results in a stable manner, thus contributing to reduction of manufacturing losses. With “i-TM,” operators’ tasks are eased as the thread tension does not need to be adjusted manually, saving managers the time for training operators.