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AI and data analytics are in full swing in the textile sector

2023-12-17ZhaoXinhua,ZhongMengxia

China Textile 2023年4期

The implementation of artificial intelligence and data analytics varies from management automation to product inspection.These technologies detect visual defects and measure wrinkles in the fabric.Also, machine learning algorithms identify previously hidden operating patterns to optimize business processes.Moreover, AI tracks consumer behavior to provide better recommendations and get insights into market fluctuations.This way, data-driven solutions improve workflows, control the labor pool, and enhance end-product quality.

Apparel 4.0 Technologies Pvt Ltd: Digitalisation of apparel sewing

Intelligent Skill Mapping and Rating Technology (i-SMART) creates digital twin of sewing machine worker.Fashion is about change and slight modification of a style can necessitate a specific spare part/attachment at production stage and availability of the right part at the right time can become a challenge.i-SMART is the world's first and only technology that evaluates the skill of a sewing machine operator.Supervisor can use the i-SMART for scientific operator allocation, human resources can use i-SMART for wage fixation, merchandisers can use i-SMART for order acceptance, and many more.

Intelligent Real-time Production Monitoring (i-RPM) is the world's first and only technology that calculates the sewing production remotely without any actions from the sewing operator.While the existing external systems (RFID/NFC/QR etc.) are subject to human frailties, and IoT based systems offer limited accuracy, i-RPM is completely automatic, uses Artificial Intelligence, can work with any sewing machine and captures sewing production with highest accuracy possible in the industry.

Intelligent Work Study (i-WS) is the world's first and only technology that conducts Time & Motion study without any sweat (human intervention).i-WS uses machine vision systems and Artificial Intelligence to calculate Key Performance Indicators (KPI) like needle running time, handling time, hand movement heat map, etc.While existing methods are cumbersome, time consuming and prone to manual error, i-WS is a fast, accurate and unprecedented method improvement tool to Industrial Engineers.

Myth.AI: AI print design generator

MYTH is an artificial intelligence-based “state of the art” pattern design tool that brings together designers and businesses.Thanks to MYTH’s cutting-edges technology,green and digital transformation is provided to all sectors and meets the requirements of the 4.0 industry.You can have a unique, unlimited, and always “new” pattern design by choosing Designers & Enterprises or Professional Model.Adapt your unique pattern to 3D visual models that MYTH customize for your main product, eliminating physical workflow and increase your productivity.The companies can improve customer satisfaction by 70%, speed up your design process by 70%, increase your efficiency by 80%and reduce production & design cost.

SENSTILE delivers AI apparel tagging

Spanish startup SENSTILE digitizes textile properties using sensors and AI algorithms.The startup builds sensors that scan textiles’ visual and chemical properties.Then its AI algorithms understand the fabric’s sensory mechanics such as feel and touch.The startup’s aggregator FabrikHUB translates the data into a file with the material’s digital identification.Based on that, SENSTILE navigates through the databases to suggest the most suitable suppliers, thus,saving time and eliminating fashion waste.

Yoona.ai provides AI-based design automation

German startup Yoona.ai provides AI-based software to automate design processes.It uses machine learning to analyze fashion input data and generate digital designs.As input data, the platform collects users’ drawings, photos, and prototypes.Based on that the analytical tool suggests new collections, prints, materials, and color schemes.As a result, yoona.ai optimizes design workflows making them time-efficient, costsaving, and environmentally friendly.