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International Journal of Artificial Intelligence & Applications (IJAIAP)
Volume 1, Issue 2, Jan-Dec 2021, pp. 1-6. Article ID: IJAIAP_01_02_001
Available https://iaeme.com/Home/issue/IJAIAP?Volume=1&Issue=2
Journal ID: 4867-9994
© IAEME Publication
MACHINE LEARNING APPLICATIONS TO
MINIMIZE DELIVERY DAMAGES IN SUPPLY
CHAIN OPERATIONS
Bidyut Sarkar
IBM, NJ, USA
Rudrendu Kumar Paul
Boston University, Boston, MA, USA
ABSTRACT
The e-commerce and supply chain industries face significant challenges in ensuring
undamaged deliveries to customers. Traditional approaches, which rely on experience
and historical data, often fail to capture the latest trends and complex interactions
among factors contributing to damaged shipments. This paper proposes a machine
learning-based solution for improved detection and prevention of damaged deliveries.
This paper presents the development of multiple classification models that predict the
probability of damages using a comprehensive set of features. The models are trained
on the latest data to capture trends across all US locations. The proposed approach
emphasizes model interpretability and stakeholder buy-in through effective
communication of business insights and model explainability. The implementation of
the machine learning solution can lead to several performance improvement projects,
such as switching carriers, adding new delivery hubs, and negotiating e-commerce-
ready packaging with vendors. Future work includes continuous monitoring and
improvement of ML operations, as well as further investigation of root causes and new
projects for sustained performance enhancements. By leveraging machine learning, the
proposed approach offers a predictive and proactive solution to the pervasive issue of
damaged deliveries in e-commerce and supply chain operations.
Keywords: Artificial Intelligence, Machine Learning, Data Science, Delivery Damages,
Predictive Modeling, Supply Chain Operations, e-commerce, Damage Prevention,
Supply Chain
Cite this Article: Bidyut Sarkar and Rudrendu Kumar Paul, Machine Learning
Applications to Minimize Delivery Damages in Supply Chain Operations, International
Journal of Artificial Intelligence & Applications (IJAIAP), 1(2), 2021, pp. 1-6.
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