Sameer Pandee, Gantec Corporation
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Transcript of Sameer Pandee, Gantec Corporation
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Sameer Pandey
RFID Middleware Design: Accomplishing real time integration of an RFID Application with Oracle Apps or any Business Application
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Sameer Pandey
The concept of RFID
Advantages offered and constraints imposed by RFID technology
Key challenges in RFID Middleware Design
Proposed design for an RFID middleware• The Rule Engine• Data filtering• Data Aggregation• Buffering and Exception Handling• Data classification and dissemination
Case Study: Understanding the middleware design concepts through actual business transactions
Summary
AGENDA
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RFID describes a class of technology that exchanges data wirelessly.
RFID systems consist of three key components:• TAG, a microchip that contains a unique digital serial number and is attached to an antenna. • READER, a device used to communicate with RFID tags to read data.• SOFTWARE, that processes, routes and manages Tag data and Readers.
The concept of RFID
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The key characteristics that influence RFID performance are:
FREQUENCY determines RFID range, resistance to interference and other performance attributes. Most commercial RFID systems operate at either the UHF band (859 to 960 MHz), or High Frequency (HF) at 13.56 MHz.
RANGE: The proximity to the tag that a reader antenna must be within, to read the information stored on the tag’s chip – varies from a few centimeters to tens of meters.
SECURITY: RFID chips are extremely difficult to counterfeit. One would need specialized knowledge of wireless engineering, encoding algorithms and encryption techniques to break-in.
STANDARDS: RFID standards exist for item management, logistics containers, fare cards, animal identification and many other uses. The International Standards Organization (ISO) and EPCglobal Inc. are two of the standards organizations most relevant for the supply chain.
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Advantages offered by the RFID technology
Exceptional speed and accuracy: More than a thousand reads can be performed each second.
Versatility: RFID enables monitoring and data collection even in extreme environments, without any manual intervention required.
Tag-reader alignment: Unlike bar codes, RFID does not require direct line of sight between tag and reader.
Total Cost of Ownership: The data on an RFID tag can be altered repeatedly.
Constraints imposed by the characteristics of RFID
Limited communication bandwidth. Reliability issues. Tag memory.
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Key challenges in RFID Middleware Design
Seamless Data Bridging: Maintain a channel of communication between the business application and the RFID application.
Filtering: Weeding out duplicates from the data flowing in.
Data Classification: Mapping the classified data to – First the business application it should hit, and secondly the actual transaction bucket it falls into.
Buffering and aggregation.
Extendibility and adaptability.
Interoperability: To cater to the heterogeneous reader landscape.
Flexibility: Interfacing the data to the application in a format that is acceptable to that application.
Two-Way data integration: Writing back to the tags.
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TAGS
Protocol Engine
Oracle Apps SAP SCM
TAGS TAGS TAGS TAGS
RFID HARDWARE
R1 R2 R3 R4 R5
PROTOCOLS
MESSAGING SERVER
DATA PRESENTATION
Filtering
Filtering
Data Classification
Buffering
Aggregation
RULES ENGINE
Exception Handling
VTMS
RDBMS
Proposed design for RFID Middleware
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Rule Engine
Well suited to the nature (large sets of data from multiple sources) and status (changing standards, protocols) of the RFID technology.
Rule driven: All forms of data handling and options to publish or subscribe the data are driven by the rules.
Based on the concept of solving a problem using a set of logical rules specific to the problem domain.
Converts data and messages from lower layers to actionable information for the upper layers; based on the business or process semantics as perceived by the end user.
Fits in perfectly for solutions requiring processing of large sets of rapidly changing data – like in an RFID network.
Offers immense flexibility to the users to incorporate their own rule chunks.
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Context Based Data filtering
Filtering weeds our the inconsistencies in tag reading or writing like• Multiple reads of the same tag.• Some tags not being read.• Erroneous reads.
Removal of such tag read events based on the reader which generated the event and the tag data captured is the key objective of the filtering mechanism.
Two filter types can be supported by the proposed middleware design
• Reader IdentifierThis filter type allows the application to specify that it is only interested data from a particular set of readers.
• Tag Identifier and DataThe application can define the tag population that it is interested in, e.g., the restriction totags attached to pallets.
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Data Aggregation
- Reduces the flood of raw tag reads to more meaningful events.
- Addresses the problem of temporary false negative reads and to smooth the data accordingly.
Following aggregate types can be supported by the middleware design
Entry & Exit Reduces a number of successful reads of a tag to the best estimate when the tag appeared and disappeared from the read range.
Count Applications can prefer to receive information about the total number of items of a specific category detected rather than the individual ID of each object.
PassageWhen a tagged object passes a gate, applications would prefer receiving a passage event rather than being forced to interpret a sequence of entry and exit events from two individual readers.
Virtual readers When an application does not distinguish between two readers, this aggregate type allows it to virtually join their read range.
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Buffering
Data persistence component of the middleware, which is based on message queues.
Buffering is required for two main purposes
• Facilitates asynchronous processing of the data streams. This is imperative for providing sufficient time for the rules to “add value” to the raw data.
• Supports different latencies of the destination applications, depending on the application type.
Exception Handling
Raising the red flags: Any discrepancy of data during the data scrubbing is processed as exceptions. Numerous alerting systems are available for resolution – emails, messages, or user defined triggers.
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RFID data dissemination
- Classifies the extracted data into relevant transaction types.- Classifies the transactions to the relevant business application.
Full content-based routing• Key element for classifying the data into correct transaction buckets.
• Full content-based routing (rather than subject- or topic-based routing) is accomplished in order to carry out the filtering within the messaging system itself.
Air Interface: Subscription feedback mechanism• Overcomes the constraint of limited bandwidth available to RFID.
• Feeds back the readers to communicate whether applications are interested inthe RFID data they produce.
• Leads to appropriate adaptation of the queries exercised by a reader over the air interface, (e.g. targeting a particular tag population at a higher sampling rate or switching off completely to make the bandwidth available to another reader).
• The filtering of the RFID data is then no longer carried out in software, but over the air interface.
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VTMS: Reading from and writing to a tag
VTMS is specifically aimed at shielding the application from the particularities of RFID tag memory:• limited memory size.• different memory organizations.• reduced write range.
VTMS response to different write scenarios
If the write succeeds, the RFID middleware will acknowledge this to the application and will store a backup copy of the data in the virtual representation of the tag in the VTMS.
If the memory gets corrupted at a later stage or the application wants to access the tag’s memory, while the tag is outside the range of any reader, the RFID middleware can make the data available via this virtual memory.
If the write to the tag fails due to insufficient power, the key-value pair will be stored in the VTMS and flagged as “open”. The RFID middleware will retry the write command at a later point of time.
If there is insufficient memory space, the application will receive the appropriate error message and the key-value will be stored in the virtual tag memory only.
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Manufacturing WIP Status
[SUPPLIERS]MFG - WIP
Finished Goods
[SUPPLIERS]MFG - Complete
Pick release and RFID tag attachment
[SUPPLIERS]Ready to Ship
Transport enroute to stocking location
Shipment Intransit
•Receiving at Receiving dock•Inspect all components installed•Sales order shipment Warehouse
Transport enroute toCustomer site
Shipment Intransit
Port of Import (POI)•Scan/Verify•Unload & On Hand at POI•Departure from POI
POI- In/POI- Out
Installed at site
•Scan/Verify•Installation, Periodic meter datafor maintenance Asset Management
In- House Mfg. WIP Status
[SHOP FLOOR]MFG - WIP
Case Study: Deployment of RFID in the Supply Chain
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Shipment Number Vendor Name Airway Bill NumberTransaction Date Quantity Unit of MeasureItem Description Document and Line Number Vendor SiteBill of Lading Packing Slip Number of Containers
Additional data generated by the reader at the Receiving dock:• Location Code (Row / Rack / Bin)• Reader Id• Transaction Date
The filtered transaction then can be classified as a PO receiving transaction. This can be done by a combination of the tag id, reader id, location at the receiving dock and PO number.
TAG ID + READER ID + PO NUMBER + LOCATION AT RCV DOCK
Supplier
ASN
PO RECEIVING TRANSACTION
PO receiving against ASN
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Intra warehouse movements• Movement from one stocking location to another within the warehouse.• Movement from the warehouse to a manufacturing facility.• Movement to a packing and staging area for shipment against a sales order.
Transaction Type Transaction Date Bill of Lading Physical LocationPacking Slip Demand Source Shipment number Quantity and UOMTag ID Warehouse Location Code Transfer SubinventorySales Order Number LPN Delivery Number Transfer organization
Combination of these fields along with the tag ID and reader ID identifies and classifies the type of business transaction.
TAG ID + READER ID + SALES ORDER + LPN + DELIVERY NUMBER SALES ORDER BASED SHIPMENT
Manufacturing Facility
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Application based filtering and classification
The transaction classification along with the RFID data will be used to identify the business application bucket in which it resides.
READER LOCATION TRANSACTION CLASSIFICATION DESTINATION APPLICATION
Receiving Dock PO Receipt ERP/WMS
Warehouse Intra warehouse movement ERP/WMS
Supplier Site Customer Service CRM
Once this classification is completed, the data will be mapped as per the requirements of the destination application.
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Summary
RFID is a promising technology that could yield immense contextual intelligence.
RFID middleware forms the bridge between the RFID Application and the pre-existing business applications.
RFID can be deployed at each stage of the Supply Chain for improved visibility of goods.
The proposed RFID middleware design: - Talks to the RFID application and extracts data. - Performs context-based Data Filtering. - Classifies the extracted data into relevant transaction types. - Classifies the transactions to the relevant business application. - Performs Buffering, Aggregation and Exception handling. - Adheres to the relevant protocols. - Is Interoperable and Scalable. - Overcomes the limitations of Tag Memory through VTMS.