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RFID Data Helps Power Schneider Electric's Smart Factory
The company is inviting customers and partners to view its IoT solution that employs data from RFID, as well as augmented and virtual reality systems, to monitor the status of production and supplies, capture analytics regarding work-in-progress and boost efficiency.
With the advent of the EcoStruxure system, the company reports, the plant will serve not only as a production facility, but also as a showcase for customers and partners to learn how it is using IoT technology to make decisions that can improve profitability, asset-management performance and operational efficiency, while enabling a smarter, productive workforce. When the RFID technology was launched a decade ago, it was intended to track the movements of products on what was, at the time, its new automated monorail conveyor system. In fact, the RFID solution enabled the automated conveyor system to operate.
The company applied 13.56 MHz passive HF RFID tags, compliant with the ISO 15693 standard, to carriers on which racks holding components were attached as the parts were processed and painted. With the technology, the company was able to link each carrier with a particular product, and to read each carrier's tag as it moved through zones in the production process. The material-handling conveyor system is complex; in fact, it moves product at high volume from 10 fabrication or load points through 10 assembly-line points, mostly related to painting. Altogether, Labhart says, the factory has approximately 900 conveyor tags attached to carriers where products are suspended as they undergo these processes.
There are 75 readers throughout the facility that capture tags reads as each item is processed. The tag passes within three inches of each reader, at which time data is read and routing is accomplished accordingly. When an item enters the paint section, the paint recipe for that product is written to the tag as well. Users can view in real time where each carrier tag was last read, thereby gaining data regarding WIP or potential reductions in materials and supplies. However, the data was previously captured at the edge, and not stored, so it couldn't be analyzed later.
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