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Technology/Machinery
Pushing the boundaries of fabric inspection
Solution transfers all production and quality information to a central database.
10th May 2022
Innovation in Textiles
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Kortrijk, Belgium
Automatic on-loom fabric inspection, Industry 4.0 and energy monitoring solutions for the textile value chain will be presented by BMSvision at the forthcoming Techtextil 2022 in Frankfurt (June 21-24), within the Belgian National Pavilion in Hall 12.
BMSvision has pioneered camera based on-loom inspection systems since the introduction of the Cyclops system 20 years ago. Hundreds of looms have now been equipped with this system for the on-line quality control of many technical fabrics.
With its new Argus, BMSvision is again pushing the boundaries of automatic inspection as it extends the possibilities from the inspection of plain fabrics to complex Jacquard fabrics such as OPW (one-piece woven) airbags.
Through the intelligent wireless networking of all production equipment in the mill, the BMSvision MES solution transfers the huge amount of production and quality data originating from the various processes to a central database and translates it into meaningful information for managers.
The BMSvision MES suite of applications includes software modules for real time monitoring, business intelligence, scheduling, maintenance and quality. The Management Dashboard application allows the combined presentation of data from different software modules into a single web-based report showing all KPIs at a glance. The MyMES app, available for both Android and iOS, allows all important production and quality data to be consulted any time, anywhere.
With escalating prices, energy consumption has become a critical cost component across the entire textile production chain. EnergyMaster, one of the modules of the BMSvision MES solution, makes all energy streams in the plant transparent and allows the exact energy cost to be allocated to each production batch. Excessive consumption or consumption while the machine is idle is immediately detected and highlighted.
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