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2/8/2017
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Tejas Bhatt, MS CFS
Institute of Food Technologists (IFT)
03.02.2015 3:00 ET | 2:00 CT
Vir tual Integrated Real-Time User AnaLytics(VIRTUAL) Tool
SUPPLY CHAIN SECURITY PROJECTS
OVERALL OBJECTIVES: To create a continuously evolving food supply chain model that outputs distribution dynamics To create an ontological framework that would facilitate connecting the outputs of this model with existing (or under development) food defense models
IMPACT: The model will be a development tool to minimize data collection activities and maximize innovation potential within academia The model will be an analytics tool for the food industry to justify implementation and enhancement of food defense practices
DATES: July, 2014 – June, 2016
PROJECT INTRO
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RESEARCH TEAM
Tejas Bhatt, PI Janet Zhang, co-PI Rosie Newsome, Senior Scientist
William Fisher, Industry Liaison
Brian Sterling, Technology Specialist
Active External Partners Department of Homeland Security (DHS) Chemical Security Analysis Center (CSAC)
Bumble Bee Foods
Other External Partners University of Minnesota / NCFPD
Purdue University Georgia Institute of Technology Battelle GS1USMetro Germany
PepsiCo
PROJECT PARTNERS
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Two primary deliverables: A food defense model An ontological framework
End Users Academic Community Researchers Model developers
Public Sector Food and Drug Administration DHS Chemical Security Analysis Center
Private Sector Food Industry Non‐governmental Organizations
PRODUCT(S) & END USERS
BACKGROUNDERGLOBALIZED SUPPLY CHAINS
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BACKGROUNDERMODELING AND SIMULATION
Application of Modeling and Simulations (M&S)
Predictive microbiology
Processing conditions
Packaging operations
Sensory characteristics
Shelf-life studies
Supply chain dynamics
Advantages of Modeling and Simulations (M&S) Cost effective
Fast turnaround
Near real-time feedback
Measure secondary and tertiary effects
Impact of decision-making
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BACKGROUNDERLOCALIZED BARRIERS
Researcher
Dat
a?Joint P
roposal?
GovernmentIndustry
Academia
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BACKGROUNDER
Garbage In = Garbage Out
MODELING AND SIMULATIONS: VALIDATION
Statistical Significance Error rates
Confidence intervals
Software Development Lifecycle Requirements gathering
Design
Development
Deployment
Testing
Evaluation
Refinement
Modern Methodologies Automated learning techniques
Behavioral software analysis
Experimentation & Exercise Workshop
Seminar
Tabletop
Functional
Full-scale
Homeland security exercise evaluation plan (HSEEP)
Mixed reality environment
Verification, Validation and Testing
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Source: Giannakopoulou & Păsăreanu, 2010; FEMA, Chaturvedi, et al., 2008
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BACKGROUNDER
Reduced Resources
Faster Innovations
Incentivize Smarter Research
METHODOLOGYOVERVIEW
Source(Pre-harvest)
Transport(Post-harvest)
Storage Processing Retail & Consumption
Economic Impacts?
Impacts?
Public Health
Impacts?
Farm•Grains•Animals •Plants
Storage ProcessingDistributing
Center Retail
Restaurant
Consumer
Transport Transport
VIRTUAL World
REAL World
Transport
Transport
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METHODOLOGYENVIRONMENTAL SCAN
METHODOLOGYMODEL DEVELOPMENT
Inputs to the Model
Use existing data from
models
Identify gaps in data
Use industry data to fill
gaps
For each food For each company
For each critical tracking event Collect key data elements such as:• Supplier, Event Owner, Customer, Trailer, Carrier, Transporter• Origin, Location, Destination• Product, Commodity, Variety, Species, Quantity, Amount• Packaging Type, Materials, Style• Date, Time, Batch, Lot Code, Sell-by Date, Use-by Date• Bill of Lading, Invoice, Packing Slip, Purchase Order, Work Order• Others
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METHODOLOGYMODEL DEVELOPMENT
Supply Chain Dynamics
Build a VIRTUAL model of the supply chain using distribution dynamics and business intelligence extracted from the input data
Update VIRTUAL model of the supply chain as more data (and therefore more insights) becomes available
Continuous Evolution
METHODOLOGYMODEL DEVELOPMENT
Outputs from the Model Supply Chain Dynamics
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METHODOLOGYMODEL DEVELOPMENT
Outputs from the Model Comparative Analysis
Scenario 1 Scenario 2
METHODOLOGYMODEL DEVELOPMENT
Use Case 1: Academic Modeler IDEA: I think I have come up with a better way to assess supply chain
risks…
NEED: I need a complex supply chain to test my theory…
USE: Use the VIRTUAL model to create a supply chain of hundreds of nodes/entities and thousands of links/connections
IMPACT: Overlay a supply chain risk assessment model to measure impact/effectiveness/plausibility/gaps/refinement…
EXAMPLE: Food defense model at Purdue University
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METHODOLOGYMODEL DEVELOPMENT
Use Case 2: Student Development IDEA: Engage student learning through group mock exercises in
supply chain resiliency…
NEED: I need multiple complex supply chains to practice recall management scenarios…
USE: Use the VIRTUAL model to create multiple supply chains of different commodities
IMPACT: Overlay an educational model to measure student learning…
EXAMPLE: Food Safety and Defense Graduate Certificateat Kansas State University
METHODOLOGYMODEL DEVELOPMENT
Use Case 3: Industry Capacity Building IDEA: I want to test the capabilities of a new traceability software
vendor…
NEED: I need challenging complex supply chains to test product tracing scenarios without giving away my business confidential information
USE: Use the VIRTUAL model to create challenging complex supply chain that closely match own product commodity and supply chain systems
IMPACT: Overlay a capability-testing model to measure effectiveness of tool/technology in handling challenging complex food production scenarios…
EXAMPLE: Technology selection process at a large MNC such as PepsiCo
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METHODOLOGYMODEL DEVELOPMENT
Use Case 4: Industry Assessments IDEA: I want to test the resiliency of my own distribution system…
NEED: I need to mimic my own supply chain dynamics without the need to engage in complicated non-disclosure agreements
USE: Use the VIRTUAL model to recreate own product commodity and supply chain system with anonymized and approximated supply-customer relationships
IMPACT: Overlay a “what-if” scenario model to measure resiliency of the distribution system to compare baseline distribution dynamics with anomalies (such as single or multiple nodes/links going down)
EXAMPLE: Internal risk assessments at food retailerssuch as Metro
METHODOLOGYMODEL DEVELOPMENT
Use Case 5: Regulatory Analytics IDEA: I want to reduce the signal to noise ratio in the traceability records
collected during a food defense outbreak investigation…
NEED: I need to compare the distribution records collected during the investigation with “normal“ distribution dynamics
USE: Use the VIRTUAL model to create a parallel supply chain system and compare the baseline with the records collected to identify anomalies
IMPACT: Using comparative analysis, a more focused investigation could proceed…
EXAMPLE: Flagging seasonal variances in supply chain distribution dynamics in the tomato-pepper outbreak
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METHODOLOGYMODEL DEVELOPMENT
Use Case 6: Regulatory Functioning IDEA: I want to estimate the magnitude of the impact of an outbreak or
of new regulatory mandates…
NEED: I need a set of representative supply chains impacted by the outbreak or new rules
USE: Use the VIRTUAL model to create large scale supply chains with millions of nodes and edges representing a sector of the food industry within the USA (or globally)
IMPACT: Overlay a public health or economic model to estimate the impact of an on-going outbreak or new regulations…
EXAMPLE: Estimate the scale and scope of the PCA outbreak or the economic impact of requiring food defense mitigationstrategies
METHODOLOGYMODEL DEVELOPMENT
Ontology Development“An explicit formal specification of how to represent the objects, concepts and other entities that
are assumed to exist in some area of interest and the relationships that hold among them.”
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Got the work plan approved by DHS and NCFPD!
PRELIMINARY FINDINGSACCOMPLISHMENTS TO DATE
Stakeholder Buy-in
Model DevelopmentModel Rollout
YEAR 1 COMPLETION
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Education and Training
Model Enhancements
Publicize and Promote
YEAR 2 COMPLETION (15/16)
Model
Open source model development
Users/Modelers Manual
Documented case studies and use cases
Ontology
Publication (for example UC Davis BioPortal)
Best practices and guidance document
TRANSITIONING RESEARCH
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Know of existing research / models that could be… … studied
… incorporated
… utilized
… connected
Know of existing ontological developments in the area of food supply chains … learn from
… partner with
… cede control to
Know of other stakeholders who might be interested to participate … provide data to build the model
… provide scenarios to use the model
CALL FOR ASSISTANCE!
STAKEHOLDER RESPONSE
Defending the safety of the food system through research, education & transition.
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