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Introduction



Radio Frequency Identification (RFID) refers to a set of technologies that use radio waves to identify and transmit information from tagged objects. While there are several mechanisms to identify objects using RFID, an important approach is to store a serial number that identifies a product, along with other product information, on a microchip that is attached to an antenna. The chip and the antenna together constitute an RFID transponder or an RFID tag. The antenna enables the chip to transmit identification information to a reader. Microchip-based RFID tags first started appearing in the late 1980s, with initial applications in areas such as access systems for office buildings and toll roads .

RFID technologies range from Very Short Range Passive RFID, Short Range Passive RFID, Active Beacon, Two-way Active, and Real-Time Locating Systems (RTLS). Low-frequency (30 KHz to 500 KHz) systems have short reading range and are commonly used in asset tracking and security access implementations. High-frequency (850 MHz to 950 MHz and 2.4 GHz to 2.5 GHz) systems, offer long read ranges (greater than 90 feet) and high reading speeds. The range of frequencies and their general distance ranges are noted below.

Business Opportunities

The opportunities from leveraging RFID technologies are varied and span a gamut of application areas. For example in retail settings, radio-tagging can help to reduce theft and loss, more easily locate items, provide suppliers with better information on real-time demand for products, and improve the speed of product distribution. While conventional barcodes need to be passed in front (line of sight) of a scanner, RFID tags can be read remotely by a device up to 20 yards away, reducing the time and labor needed to recognize and process objects. RFID tags can also be encoded with data in addition to the basic identification. Some of the areas in which RFID tagging is expected to improve supply chain performance include:

Forecasting Information: RFID tagging has significant implications for generation of better forecasts. Downstream data can be accurately assembled and processed for use in driving multi-tier forecasting processes . Such data can include warehouse inventories and withdrawals, inventory replenishments, as well as product consumption. Retailers such as Wal-Mart, which are pushing RFID technologies, are promising their suppliers information on products as they arrive and leave their warehouses, stores, and store stockrooms, in addition to the point-of-sale data.

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