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RFID in Supply Chain2
RFID• Asset Tracking
• Race Timing
• Inventory Management
• Tool Tracking
• Access Control
• Attendee tracking
• Supply Chain Management
RFID in Supply Chain3
Classification Models For RFID-Based Real-time detection of Process Events in
the Supply Chain:
An Empirical Study
Transactions on
Management Information System
Publication Date: October 2014
by
VishnuTeja Thummanapelli
2671322
RFID in Supply Chain4
Agenda
• Introduction to topic
• Prior Research and drawbacks
• Development of different Classifiers
• Results
• Critique
RFID in Supply Chain5
Need for RFID in SCM
• Saves on Labor cost
• Less paperwork
• Saves time
• Bulk identification
• Affordable hardware prices
• Identification of objects without a line of sight
• Better analysis of data
• Better tracking of goods as they move from Supplier to Customer
RFID in Supply Chain6
Architecture
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Flow of events
Warehouse person approaches the RFID
gate
Motion sensor recognizes him/her
RFID Reader starts scanning for
transponders/tags
Reading runs for 5 seconds - Gathering
Cycle
Collected pallet ID’s are sent to Warehouse
Management System
Visual feedback through signal light
person informs the system that the
loading is complete
Invoices are issued to the store
Shipping
RFID in Supply Chain8
Problems in existing system
• Because of the range of RFID readers, B1, B2 and M are detected accidentally.
• Wrong invoices are generated
RFID in Supply Chain9
Errors in reading pallets
True positive Read correctly Moved pallet
False positive Read unexpectedly Static pallet
False negative Not detected
Reasons for false-negative: • Water and liquids like shampoo can absorb radio waves.
• Dysfunctional tags
• Tags shielding each other
Reasons for false-positive: • Human error of placing the pallet in the read range
• Metals can increase the range of radio waves
RFID in Supply Chain10
Low level RFID dataEach tag event has three types of informationRSSI (Received Signal Strength Indication)• How loudly the tag was heard by antennae
• Increases if closer, decreases when distant.
• dBm (decibel mill watts)
SinceStart• Time stamp relative to gathering cycle(5 seconds period)
• milliseconds
Antenna
• Which of the antennae read the tag
• Unique id of the antenna
RFID in Supply Chain11
Sample of problem
This example is based on a case where- One tag is being moved x (Moved pallet)- Another tag was placed near by antenna ● (Static pallet)
RFID in Supply Chain12
Previous researchStudy Approach
Brusey et al. [2003]
Method: Used Queue(First in, First Out) and Robotic arm removes the item after reading. Results: Other items are also scanned.
Bai et al. [2006] Method: Used multiple cycles. If the number of reads reaches a threshold, its classified as true positive. Results: False positives are increased.
Jiang et al. [2006] Method: More than one tag is used for the same object. Transmit N polls per second. Uses rotation and calculates. Results: Performance data is released, but the design is not revealed.
Tu and Piramuthu [2008]
Method: Multiple readers are used for the same tag. If both readers detects, its assumed to be present. Results: Just a simulation, but the design is not revealed.
RFID in Supply Chain13
Comparison of previous and current researches
Weaknesses in previous research
• Previous researches ignored low level RFID data like Signal Strength.
• Additional readers and tags increases the hardware cost.
• Previous researches are based on lab tests and simulation results only.
Strengths in current research
• Signal strength plays a prominent role in current research
• Data Mining approaches are used to address false-positives.
• Massive real-time data is used (Source: METRO Group Inc., Germany)
RFID in Supply Chain14
Types of RFID Reader portals
RFID in Supply Chain15
Logical structure of tag event data - Conceptual Class diagram
Tag Event t = (RSSI, SinceStart, Antenna)Tag Occurrence T = {t1, t2,.……, tn}
RFID in Supply Chain16
Finding meaningful attributes for Classifications
“meaningful” here indicates whether a particular attribute really helps in correct classification of moved and static pallets.
Sources for Attributes:
• Tag Occurrence
• Tag Event
RFID in Supply Chain
Attributes from Tag Occurrence level
17
Aggregation functions are applied on Tag Occurrencelike
-Maximum
-Minimum
-Mean
RFID in Supply Chain
Attributes from Tag Event level
18
• Tag Event forms a time-series, because they are ordered based on time.
• The idea: is to examine whether time series of a particular tag is similar to moved or static tag.
RFID in Supply Chain19
k-NN (k-nearest neighbor Algorithm)
RFID in Supply Chain20
Attributes development
3 types of attributes are used for the classification :
1. Domain attributes
2. Logical attributes
3. Time-series attributes.
RFID in Supply Chain21
Classifier developmentClassifiers
Decision Stumps. Standard Classifiers
Logistic regression
Decision trees
Neural networks
Rule-Based Classifier
RFID in Supply Chain22
Rule based Classifier
All the data that is not classified
Artificial attributes are generated based on domain attributes to improve efficiency of Decision trees Decision tree is generated
Classify the “moved” or “static”
RFID in Supply Chain23
Classification performance• True Positives (TP) : number of moved pallets that were correctly classified as “moved.”
• False Positives (FP) : number of static pallets that were wrongly classified as “moved.”
• True Negatives (TN) : number of static pallets that were correctly classified as “static.”
• False Negatives (FN) : number of moved pallets that were wrongly classified as “static.”
• Derived metrics from the results
measure of the risk of incomplete shipments
measure of the risk of shipping pallets that were not ordered
RFID in Supply Chain24
Decision stumps Classifier
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Standard Classifiers
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Rule-based customer classifier
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RFID in Supply Chain28
Critique
• Automated RFID systems like Conveyor belt based ones are available at the time of writing paper this paper, which would reduce the error rate. Those systems were not taken into consideration.
• Creating the Training data is a tedious process which may not be available readily for all the clients. So, the immediate results can’t be expected from a new client of the Warehouse Management system.
• Classifiers on the production systems are dangerous.
• So this classification model works well with the companies which has previous data.
• Which “Artificial attributes” are used aren’t mentioned in the paper.
RFID in Supply Chain29
Conclusion
• Custom classifiers yield better results when applied to RFID systems in SCM.
• This approach can be applied to various other industries and models.
RFID in Supply Chain30
Questions ?
RFID in Supply Chain31
Thank you