The Impact of Supply Chain Analytics and Artificial Intelligence on Supply Chain Management Education

ZANNATUN NAYEEM; Dan Tenney; Tauhid Uddin Mahmood

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Conference: 2024 ASEE North East Section
Location: Fairfield, Connecticut
Publication Date: April 19, 2024
Start Date: April 19, 2024
End Date: April 20, 2024
Page Count: 13
DOI: 10.18260/1-2--45784
Permanent URL: https://peer.asee.org/45784
Download Count: 259

Paper Authors

biography

ZANNATUN NAYEEM University of Bridgeport

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I am Zannatun Nayeem, originally from Dhaka, Bangladesh, and I am currently embarking on a journey in the field of Analytics and Systems as a Master's candidate at the University of Bridgeport. My academic journey began with a focus on Resource Management and Entrepreneurship at the prestigious University of Dhaka. My experience is further enriched by my role as a Teaching Assistant at the University of Bridgeport, where I have the privilege of contributing to the growth and development of the University.

My interest deeply lies in the intricacies of supply chain mechanics and their optimization. Beyond the theoretical knowledge, I have a hands-on approach to data. I am proficient in using advanced analytical tools such as Microsoft Office, Tableau, Python, Power BI and SAS to dive deep into data, analyze it, and present it visually. This skill set not only broadens my understanding of supply chain dynamics but also enables me to propose innovative solutions to enhance their efficiency.

My dedication to my field is reflected in my continuous quest for knowledge and my desire to make a meaningful contribution to the improvement of supply chain systems. The combination of my theoretical understanding, practical expertise, and a passionate commitment to research shapes me as an aspiring influencer in the domain of supply chain analytics and systems.

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Dan Tenney University of Bridgeport

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Dr. Tenney is an Assistant Professor at the University of Bridgeport in the Technology Management Department as part of the Engineering School. Dan Tenney worked in various Quality, Technical and Operational positions in manufacturing divisions of HJ Heinz Company, 3M Company and Nile Spice Foods (acquired by Quaker Oats). For more than 25 years Dan was a member of the executive teams that directed and managed these divisions. Dan’s current focus is strategic technical and business management, application and research. Dan is a Board member on a Child’s Mental Health nonprofit agency where he has facilitated strategic planning and operational management training and guidance. He has published numerous publications on strategic and business management topics.

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Tauhid Uddin Mahmood University of Bridgeport

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Abstract

Artificial intelligence (AI) is on the brink of changing various sectors, including the industrial sector. Artificial intelligence has a considerable influence on supply chain management. This innovative technology improvement is transforming the traditional supply chain framework, boosting its innovativeness, efficiency, and, most importantly, profitability. AI has allowed the application of machine learning and predictive analytics in the industrial sector, enabling businesses to accurately forecast and estimate demand and supply. Using these technologies, businesses may forecast and prepare for potential difficulties, such as inventory delays or shortages, while also creating more favorable circumstances for greater production output AI assists businesses in optimizing their operations by accurately projecting various market trends such as client preferences, industry demands, and sales estimates. Its ability to swiftly assess large amounts of data enables it to outperform human capabilities. This capability allows businesses to adjust their production in anticipation of demand swings, reducing the risk of excess inventory or shortages of critical components. Furthermore, artificial intelligence enables the rapid monitoring and surveillance of goods across the supply chain. AI allows businesses to get real-time updates on the status of commodities in transit, weather conditions, and other important information This enables them to take proactive actions to fix any delivery issues and ensure timely deliveries. The instant availability of information boosts productivity reduces costs associated with delays and increases user satisfaction. Artificial intelligence (AI) has the potential to improve warehouse operations by automating repetitive tasks. AI-powered robots can manage inventory, pick orders, package products, and even transport goods inside the warehouse. This automated technique helps to reduce labor costs, reduce the likelihood of human error, and improve overall effectiveness. Furthermore, these robots have the potential to work constantly, increasing productivity. Predictive analytics, machine learning, and real-time monitoring may help reduce operating costs, manage demand variations, and increase customer satisfaction. These changes eventually lead to more income. Implementing AI technology in industrial processes may provide significant benefits by increasing efficiency and production. The purpose of this review is to provide insight into the emerging field of supply chain analytics by using artificial intelligence to improve business performance through supply chain management education. Key Words: Artificial Intelligence, Supply Chain Analytics, Supply Chain Management Education, and Supply Chain Analytic Education.

Citation
Format

NAYEEM, Z., & Tenney, D., & Mahmood, T. U. (2024, April), The Impact of Supply Chain Analytics and Artificial Intelligence on Supply Chain Management Education Paper presented at 2024 ASEE North East Section, Fairfield, Connecticut. 10.18260/1-2--45784

TY - CPAPER
AB - Artificial intelligence (AI) is on the brink of changing various sectors, including the industrial sector.
Artificial intelligence has a considerable influence on supply chain management. This innovative
technology improvement is transforming the traditional supply chain framework, boosting its
innovativeness, efficiency, and, most importantly, profitability. AI has allowed the application of machine
learning and predictive analytics in the industrial sector, enabling businesses to accurately forecast and
estimate demand and supply. Using these technologies, businesses may forecast and prepare for potential
difficulties, such as inventory delays or shortages, while also creating more favorable circumstances for
greater production output AI assists businesses in optimizing their operations by accurately projecting
various market trends such as client preferences, industry demands, and sales estimates. Its ability to
swiftly assess large amounts of data enables it to outperform human capabilities. This capability allows
businesses to adjust their production in anticipation of demand swings, reducing the risk of excess
inventory or shortages of critical components. Furthermore, artificial intelligence enables the rapid
monitoring and surveillance of goods across the supply chain. AI allows businesses to get real-time
updates on the status of commodities in transit, weather conditions, and other important information This
enables them to take proactive actions to fix any delivery issues and ensure timely deliveries. The instant
availability of information boosts productivity reduces costs associated with delays and increases user
satisfaction. Artificial intelligence (AI) has the potential to improve warehouse operations by automating
repetitive tasks. AI-powered robots can manage inventory, pick orders, package products, and even
transport goods inside the warehouse. This automated technique helps to reduce labor costs, reduce the
likelihood of human error, and improve overall effectiveness. Furthermore, these robots have the potential
to work constantly, increasing productivity. Predictive analytics, machine learning, and real-time
monitoring may help reduce operating costs, manage demand variations, and increase customer
satisfaction. These changes eventually lead to more income. Implementing AI technology in industrial
processes may provide significant benefits by increasing efficiency and production. The purpose of this
review is to provide insight into the emerging field of supply chain analytics by using artificial
intelligence to improve business performance through supply chain management education.
Key Words: Artificial Intelligence, Supply Chain Analytics, Supply Chain Management Education, and
Supply Chain Analytic Education.
AU - ZANNATUN NAYEEM
AU - Dan Tenney
AU - Tauhid Uddin Mahmood
CY - Fairfield, Connecticut
DA - 2024/04/19
PB - ASEE Conferences
TI - The Impact of Supply Chain Analytics and Artificial Intelligence on Supply Chain Management Education
UR - https://peer.asee.org/45784
DO - 10.18260/1-2--45784
ER -