Traditional Industries Evolve Implementing Machine Learning

Reporter: PENG Hui-ming (彭慧明) | Source

Artificial intelligence (AI) technology is not only a tool for refining strategy within the sector, but also an upgrade to traditional industries. Recently, Hermin Textile, a Taiwanese textile manufacturer, implemented Google’s AI and machine learning technology to enhance their daily operations, which has significantly reduced the time spent on textile pattern matching and order processing. This shows that high-tech is relevant to many industries, if not all, including the traditional ones.

Google has newly launched an AI and machine learning tool “Cloud AutoML” that can be used by small and medium-sized enterprises and even individuals. It integrates visual recognition with cloud development tools and allows companies to develop their own AI models without highly specialized engineers. The trained model can be generalized to kickstart a new model with transfer learning and accelerate the entire learning process.

Hermin Textile produces high-quality fabrics and supplies to international brands such as Burberry and Coach. It used to rely heavily on labor in the past.

ChiaHsien Lee (Neil), Digital Transformation Executive Consultant of HerMin Textile, disclosed that until last year, the company had to proceed the textile pattern matching manually. It required experienced personels to match the patterns requested by the clients with their stock and decide to redesign and produce if there were no matching found.

Since last year, HerMin decided to use machine learning to replace the manual procedures. They worked out the application with CloudMile, a Google Cloud Premier Partner, as the technical consultant. They have built a database by filing tens of thousands of cloth patterns, automated the manual matching procedures by creating an exclusive algorithm and developing a pattern recognition system on Google Cloud Platform that can automatically identify pattern of fabrics. It has successfully shortened the communication time gap between the textile manufacturer and overseas designers, significantly saving time and labor costs, and increasing production efficiency.

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