State of RFID Dr. Ray Huetter CTO

State of RFID

Dr. Ray Huetter CTO

Large Volume Applications

$500+M global industry; $3B by 2010 (Gartner) State of the Art

ePedigree Global Supply Chain and Logistics Maintenance Repair and Overhaul (MRO) Real-time Location Sensors (RTLS)

RFID Issues Research

ePedigree Pharmaceutical Authenticity

Combats counterfeiting and diversion No one knows the size of the problem e.g. Epogen/Amgen, red blood cell production, needs storage requirements,

dosage ripoff, vials look identical Drug from 3rd world into 1st world, price point margin Almost impossible to detect visually

Regulatory requirement emerging in US and EU ePedigree cut in date for California in Jan 2009

Driving force in the US Forcing anyone selling product in CA to conform (China and India)

India has 15,000 pharmaceutical companies RFID and serialized barcodes are both solutions Key solution is data management

Correlate location/state with everything that has been manufactured Food supply chain equivalent

Track & Trace Other Goods Emerging applications in luxury goods, media

Supply Chain Track and trace for goods and containers (retail)

Item level tracking on the horizon Not really used today

Tracking of pallets and containers; end-to-end From manufacturer (world wide/cross-oceans) Through ports, distribution centers To stores

Cooperative between all parties Manufacturer, shipping, truck, rail Store: storeroom out to shelf

Mainly pilot projects Defense Departments

Would like to track all goods Now are tracking high value goods Primary goal is fighter readiness Broad utilization

MRO Maintenance, Repair, Overhaul

Extension of supply chain tracking What happens to item after it has been bought/delivered Tracking through

Duty cycle of item Warranty management Over remanufacturing events Through to disposal

Dangerous items Environmental (electronic goods, etc) ROHS (e.g. lead content) National Security (defense surplus) eg. authority to purchase

Greatest value / use case is complex assemblies with long life span Aviation Automotive

Can help in monitoring counterfeit replacements

Issues

Standardization No “perfect” tag

Many different kinds of tags for many different types of applications E.g. active v. passive; cold chain

RF standards HF vs UHF E.g. in pharma: How are biologicals (large molecular weight drugs)

affected by RF? Push back from manufacturers. Placement on tagged object

Size, material, liquid viscosity (can change RF characteristics) E.g. only one tag fitted on Viagra packaging

Installation still requires skill; not DIY Antenna placement RF interference

Access standards EPCIS starting to make an impact SQL databases not a good fit

Our View of RFID

RFID & sensors augment the physical world Goal: assist people and machines to make better use

of physical objects plan & observe use, identify misuse, predict service analyze systemic cause and effect

Succeed when ROI is demonstrated coincides with maximal assistance reduction in time, space, matter & energy of processes

This is common across many domains Supply chain, ePedigree, health care, MRO, logistics,

…

Potential of RFID

RFID will make many contributions Economic, environmental, social (health)

Effectiveness & ROI will be substantial Physical optimization (more for less) Correct distribution, location and usage Safety and correctness Prevents harm (food safety) Reduction in resources, waste and errors Physical process improvements Lead to new opportunities…

Best ROI Results

Successful pilot projects are showing 5 to 10 times ROI when end-to-end visibility occurs Single, accurate timely view Across physical & logical boundaries By multiple parties

Why? Able to see what happened and when Able to reason about it, as and when it happens Discover cause and effect Use it to ones advantage or correct it Optimize: time, space, energy & matter

Control-Feedback Loop

Holistic View

Real-WorldSystems

ComputerSystem

Observe

Optimize

Maximizing ROI

Maximal ROI occurs when optimization takes into account As much fine-grained detail as possible Of as many physical objects as possible Across as many boundaries as possible In as short a time-frame as possible For the least price possible

Conversely, ROI will be limited by coarse-grained, filtered / summarized, isolated,

untimely or expensive systems

Not Possible Today

Most contemporary systems substantially constrain effectiveness & ROI Are expensive (relative to the cost of tags) Are isolated “stove-pipes” Are not real-time Do not support continuous operation Do not scale with hardware Do not cope with volume

Will be suboptimal There is a missing link here…

Requirements

Build systems to maximize ROI Collect sensor based-data (notably RFID) of arbitrarily large

physical systems in real-time Use that data to create fine-grained models of in real-time Enable new & existing applications / systems to securely

observe, reason & optimize physical systems by querying the current state and history of the model adjust the physical system continuously in real-time

Do this by supporting Real-time write back to tags Apply rules to produce actionable alerts in real-time Pushing changes to applications as they happen Applications querying history (prior state) as required Replay history of events as they occurred

Holistic View of Physical Systemsreal world

Supply-Chain 1

Supply-Chain 2

Supply-Chain 3

SensorConnect

Model of Supply-Chain 1

Model of Supply-Chain 2

Model of Supply-Chain 3

History

Applications

tracking, planning, optimization, exception

management, reporting...

Events

(in-memory model)

(real-world system)

Queries

SensorConnect System Qualities

High performance > 50,000 events per second per 64-bit CPU < 100 millisecond response time per event, including write-back Balance queries with ingestion maintain detailed history; replay event history

Indefinitely scalable Support models with billions .. trillions of physical objects

Widely compatible Devices & systems

Standards compliant EPCIS (repository)

Highly reliable Continuous operation via hot failover

Secure Access & authorization controls

University of Arkansas

University of Arkansas invited to test SensorConnect core

Run tests indicative of loads of an entire supply chain

Motivations: Interested in scalable grid technology with application to sensor

networks and identity Have skills and technology to do synthetic data generation Longer term collaboration with RFID technology

Proof of Concept Experiments

Purpose Test configuration Synthetic Data Generation (SDG) Descriptions, results, and analysis

Purpose

Measure performance of the SensorConnect system while accepting data from an independent, outside source Ingestion (insertion) Balanced (concurrent ingestion and queries)

Test Configuration

ACE four node grid (provided by NSF grant #0410966)

64-bit dual processor AMD Opterons 1.6 GHz 2 GB RAM 60 GB Hard Drive 1Gbps Ethernet Rocks 4.2, Linux Kernel 2.6.9

Part of the Open Science Grid

Synthetic Data Generation (SDG)

Written in Java Accepts Synthetic Data Description Language (SDDL)

file as input Capable of generating data sequentially or in parallel Partitioning algorithms assure that the resulting data set

will be consistent regardless of the degree of parallelism used during generation

Capable of direct-to-database generation, but generating to intermediate text file is more common, and faster

Application:Simple RFID Supply Chain Data

Problem: Generate synthetic RFID events (“arrive” and “depart”) for 10 million unique objects traversing 100 read points (total = 2 billion events)

Row: TagID, ReaderNum, BizEvt, Timestamp

Total data generated: 86 GB (2B rows)

Reader 1

Reader 2

Reader 3

Reader 100

. . .

Experiments Run

Peak ingestion Event replay Query item Query history Query location description

Peak Ingestion Test

Event Replay Test

Query Item Test

A balanced test that returns a tag’s current, or most recent, location

Query History Test

This balanced query returned the event history of a tag, or all records recording an “enter” or “leave” event for a given tag

Query Location Description Test

A balanced test that returns all tags at a given location, or position, within a supply chain

Experiment Conclusions

SensorConnect is designed for multi-core, multi-cpu System allows for an unbalanced 400,000 events/second

peak ingestion rate Balanced tests were able to query data at a rate greater

than ingestion Deployment of the SensorConnect system in a foreign

environment was accomplished with relative ease Ultimately the test results far exceeded expectations

indicating great promise for the system

Summary

Goal of RFID is to assist people and machines to make better use of physical objects

Successful projects demonstrate ROI ROI coincides with maximal assistance SensorConnect is a high-volume real-time

EPCIS system which models the real-world Tests by University of Arkansas show peak

performance >400,000 events per sec