2022AIP conference proceedingsRequires access

A comprehensive study on intelligent approaches to effective supply chain management

Kiruba James, Sujitha Juliet

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Abstract

The activities involved in handling the complete production flow of both goods and service, commencing from the procurement of Raw Material and culminating with the supply of finished products or service to the consumer is termed as Supply Chain Management. To extract the best benefits of Supply Chain, and to optimize the performance of the Supply Chain, it is a good opportunity to use Machine Learning in the different phases of the Supply Chain. There are multiple stake holders in the Supply chain, such as vendors, customers, distributors, retailers, and logistic support agents. Machine Learning when used in a Supply Chain, can bring about a positive impact on the efficiency of the stake holders in the supply chain. A lot of research effort has been done in Prediction using Machine Learning in Supply Chain Engineering. Several Prediction Algorithms have been used in domains other than Supply Chain Management also. This application can serve as a guideline for Supply Chain Management based Applications. However, there is a need to identify the possibility of using improved Prediction Algorithms in the Supply Chain

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What this paper is about

The activities involved in handling the complete production flow of both goods and service, commencing from the procurement of Raw Material and culminating with the supply of finished products or service to the consumer is termed as Supply Chain Management. To extract the best benefits of Supply Chain, and to optimize the performance of the Supply Chain, it is a good opportunity to use Machine Learning in the different phases of the Supply Chain. There are multiple stake holders in the Supply chain, such as vendors, customers, distributors, retailers, and logistic support agents. Machine Learning when used in a Supply Chain, can bring about a positive impact on the efficiency of the stake holders in the supply chain. A lot of research effort has been done in Prediction using Machine Learning in Supply Chain Engineering. Several Prediction Algorithms have been used in domains other than Supply Chain Management also. This application can serve as a guideline for Supply Chain Management based Applications. However, there is a need to identify the possibility of using improved Prediction Algorithms in the Supply Chain

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Available abstract

The activities involved in handling the complete production flow of both goods and service, commencing from the procurement of Raw Material and culminating with the supply of finished products or service to the consumer is termed as Supply Chain Management. To extract the best benefits of Supply Chain, and to optimize the performance of the Supply Chain, it is a good opportunity to use Machine Learning in the different phases of the Supply Chain. There are multiple stake holders in the Supply chain, such as vendors, customers, distributors, retailers, and logistic support agents. Machine Learning when used in a Supply Chain, can bring about a positive impact on the efficiency of the stake holders in the supply chain. A lot of research effort has been done in Prediction using Machine Learning in Supply Chain Engineering. Several Prediction Algorithms have been used in domains other than Supply Chain Management also. This application can serve as a guideline for Supply Chain Management based Applications. However, there is a need to identify the possibility of using improved Prediction Algorithms in the Supply Chain

Key concepts: Supply chain, Service management, Procurement, Supply chain management, Supply chain risk management, Service (business), Demand chain, Computer science

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