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    Break The Traditional Industry Pain Spot "Cloth Three Generation" Test Water Intelligent Test Cloth

    2019/10/9 10:48:00 0

    TextilesInspection

    These days, "cloth three generation" Wu Tang Houze is a bit busy. His front foot just left from the 2019 Nanjing Xuanwu "Phoenix Xuan Wucai poly silicon lane" innovation and entrepreneurship competition, and the hind foot flew to Shenzhen to meet with investors. These two events are all centered on a project "third party inspection platform for textiles based on the Internet of things". Wu Tang Ze Ze is the person in charge of the project. In the recent Nanjing innovation and entrepreneurship competition, the project stood out from many domestic and foreign projects, all the way into the final, and won the "winning award".

    "Eleven after the national holiday, there are still a few investors to meet." Wu Tang said that the capital market also showed strong interest in the project.

    Compared with traditional innovation and entrepreneurship projects, the project has a higher maturity. It is reported that based on this project, as early as last year, Tang Houze and several like-minded partners set up a more than 2000 square meter Zhejiang Wu Tang textile inspection company in Keqiao, and worked with a technology company in Shanghai to successfully develop an intelligent cloth inspecting machine based on the Internet of things. Today, in the "Wu Tang inspection", with the intelligent cloth inspecting machine as the core, it has also equipped a series of testing equipment to provide customers with the three services, such as fabric appearance inspection, textile physicochemical index test, textile storage management, fabric roll packaging, data analysis and statistics.

    The reporter saw that every cloth was checked by intelligent cloth inspecting machine, and a detailed report was automatically issued. The parameters, location, repair advice, cloth quality evaluation and so on were clear at a glance. "Traditional cloth inspection is generally done by human eyes. After reading it, it is not only inefficient, but also poor in recognition rate, and it can not systematically analyze the data." Wu Tang Hou said that after the inspection of production practice, the secondary recognition rate of the company's intelligent cloth inspecting machine can be increased by 90% compared with the traditional one, and all data can be informationized. In this way, the technical personnel of the company can make systematic analysis of these data, find out the problems of their production process and workshop management, and put forward professional suggestions for improvement.

    "There are more than 300 textile inspection organizations in Shaoxing, most of which are rolling shops. In other words, it is a machine and several old ladies. The environment inside the shop is dirty and scattered, and there are few standardized inspection reports." As a "cloth three generation", Wu Tang Houze grew up in cloth pile, and he felt the pain of traditional cloth inspection. Before entering this field, he returned from the United Kingdom to study more than 2000 textile trade and production enterprises. After face-to-face understanding of customer demand, he was determined to make use of the Internet of things technology to build a professional, data, information and systematized third party fabric inspection service provider, and strive to become a new benchmark for the industry.

    It is understood that there is no similar third party intelligence testing cloth service provider in Shaoxing area. The establishment of "Wu Tang test" has won many customers' favor. Today, the company has a monthly inspection volume of more than 800 thousand meters, mainly serving more than 30 customers in Shaoxing, Shanghai and Taiwan. Next, the company will conduct "ID cards" for every tested textile. Through the "identity card" scanning code, customers can grasp all the information of each cloth manufacturer, physical parameters, storage location, logistics flow and so on, and truly realize the management of big data.
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