American Association of
State Highway and Transportation Officials
Special
Committee on Research and Innovation
Problem
Number: 2023-B-32
NCHRP Problem Statement
Title:
Improving
Supply Chain Visibility for Agricultural Commodities Using Artificial
Intelligence
Other extraordinary challenges facing the agriculture
industry include changes in consumer income and preferences that have resulted
in more expensive supply chains.
Supply chains are expanding to include many complex and innovative components
(ex. big data, machine learning), controlled by numerous independent
stakeholders (distributors, producers, state agencies), and designed to serve
diverse customer segments. For example,
identity preserved (IP) commodities such as grains organic meats and produce
are increasing in popularity with global populations, including
socioeconomically disadvantaged residents seeking healthier dietary options.
However, IP commodities require systems of production, handling, documenting,
certifying, marketing, and monitoring at all stages to ensure product quality
and integrity that results in additional costs.
All the transactional information must be collected, coordinated, and
distributed to the right people at the right time to trigger the right actions. Manually performing these complex, time-sensitive
interactions is inefficient, unfeasible, and can be better facilitated using
‘smart contract’ blockchain technology and artificial intelligence (AI). These state-of-the-art technologies can be
utilized to improve efficiency and smoothen the flow of grain at each point in
the supply chain.
Buyers
are perpetually confronted with challenging decisions when placing food
commodity orders and often enter a vicious “bull-whip effect” cycle in which
their produce spoils and they run out or run low, then they over-correct by
over-ordering, and that produce also spoils because it does not sell fast
enough. AI coupled with blockchain technologies can assist in calculating more
accurate forecasts and compute economic order quantities resulting in orders placed
for the right amount or number of commodities at the right time.
Examples
of this effect are the market disruptions resulting from the Covid-19 pandemic
on the global and U.S. food supply.
Before the pandemic, the food supply chains were more stable, and
produce arrived at its destination just in time. However, as the pandemic commenced, customers
started “panic buying,” creating a spike in demand for certain commodities
followed by an extended and unexpected lull in demand. Further, plant worker illnesses and plant
shutdowns in the food processing industry created a bottleneck at the packaging
and processing plants resulting in colossal waste (euthanatizing oversized
hogs, chickens, cattle) and a shortage of meat despite the availability of
livestock and the increased demand at stores.
A sensing
system based on blockchain technology provides supply chain visibility
solutions that can help connect and synchronized the food supply chain to track
the cause of waste, while also assisting buyers in monitoring transportation
processes to predict realistic shelf-life based on data, determining the
optimum condition for the food, and ensuring lead-times are adequate to get the
commodity to the consumer.
Food
storage and transit also present supply chain challenges as conditions must be
continuously monitored and maintained at favorable conditions. Artificial Intelligence with IoT and
blockchains can enhance quality assurance by monitoring and controlling
parameters while in storage and transit, such as humidity, light exposure,
ventilation, and temperature to maintain agricultural commodity shelf-life,
food safety, and ensure that the commodities reach the end-user in a
satisfactory state.
Improving
Supply Chain Visibility for Agricultural Commodities Using Artificial
Intelligence research includes database and expert system development for
optimal grain storage and will result in transparent supply chain management
and optimization of trucking drayage and railroad contracts that can be
utilized by other agricultural commodities including fresh food. Advanced machine learning algorithms can be
designed to quantify the effects of available train frequency and velocity,
truck and rail drayage data, demand changes at grain elevators, and price of
grain in domestic and international markets. This research is vital for
assisting stakeholders in choosing the right market and right time to sell
their commodities. Therefore, the resulting expert systems designed with the
support of AI will monitor all factors that affect the quality and condition of
the grain and other commodities during the entire supply chain.
Alarming
Statistics:
Dallas-based
technology company Symphony
Retail AI has revealed.
There are
additional challenges with food exports and its tractability when shipped
overseas.
An online
web search for “Agriculture Supply Chain Visibility Using Artificial
Intelligence” resulted in several reports and articles regarding the technology
developments and benefits of AI for supply chain visibility using. AI has been
shown to improve supply chain visibility and transports good more efficiently.
However more research is needed for effective implementation.
In a
report of data-driven agriculture supply chains, the findings found that
information collection and sharing is highly valuable and beneficial for a
supply chain to remain competitive, address challenges of food perishability,
demand-supply variations, safety, and sustainability (Kamble et al 2020)[1]. This is dependent on
accessibility to high quality data.
There has
not been significant research on the efficient implementation of a digitized
supply chain across an agricultural market to improve supply chain visibility.
According to a white paper
by Frost & Sullivan, in partnership with IBM,
1.
Summarize
existing AI technology for improved supply chain visibility for agricultural
commodities
2.
Identify
challenges/barriers to implement AI in supply chains and distinguish between:
a.
Urban
and rural challenges including equity
b.
Challenges
for small farmers
c.
AI
for producers vs. consumers vs. distributor
3.
Assemble
case studies to identify transport efficiency gains and business savings of
successful implementation of AI for supply chains, including the use of
blockchain technology and IoT.
4.
Utilizing
AI, IoT, and blockchain to develop the supply chain of the future
5.
Develop
recommendations for effective implementation of AI for interstate agricultural
transportation markets including:
a.
Resiliency
for emergency events including Covid-19
b.
Congestion
and bottlenecks at various stages of the supply chain
c.
Rural
and Urban
d.
The
urgency for improving freight supply-chain efficiency is extremely high,
particularly given widespread challenges in the U.S. that have negatively
impacted producers, shippers, manufacturers, and consumers everywhere. Many of the challenges being experienced
today and over the past 1.5 years could be mitigated with better information
systems and visibility, to allow improved decision-making by participants
throughout the supply-chain. The
potential benefits include:
·
Reduced
delivery times
·
Improved
equipment utilization
·
Reduced
energy utilization, increased environmental benefits (air quality)
·
Lower
transportation cost
·
More
effective planning and coordination with public transportation system
·
Improved
safety
·
Improved
system performance
·
$400,000
·
18
months
Eric
Jessup
Research
Professor
Washington
State University
509-335-4987/
eric_jessup@wsu.edu
Satpal S.
Wadhwa
Transportation
Research Analyst
North
Dakota State University
701-231-9594/ satpalsingh.wadhwa@ndsu.edu
Frida Cruz
Economic
Analyst
AECOM
703-340-3103/
frida.cruz@aecom.com
AT030 Agriculture and Food Transportation Committee
Sherry
Pifer
Branch
Manager, Freight, Trade, and Connectivity Section
118 E.
Riverside Dr.
Austin,
Texas 78704
Cell:
512-460-1727
Email: sherry.pifer@TxDOT.gov
Kelly
Eagan
Chief –
Freight Performance Management Branch
California
Department of Transportation
Division
of Transportation Planning
Office of
Freight Planning
1120 N
Street (MS 32)
Sacramento,
CA 95814
Office/Cell:
(916) 639-6373
Email: kelly.eagan@dot.ca.gov