Authors :
Kagame Fred; Dr. Musoni Wilson
Volume/Issue :
Volume 7 - 2022, Issue 11 - November
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3H2hoAk
DOI :
https://doi.org/10.5281/zenodo.7388555
Abstract :
For the modern industrial sector, data created
by machine learning and devices, product lifecycle
management (PLM) tools, production planning tools, or
quality and inventory control tools has reached a volume of
more than a thousand Exabyte yearly and is anticipated to
rise in the next years. To store, manage, analyze, interpret,
and visualize such a large volume of data, Data technologies
are now required.Supply Chains (SC) are a network of
locations that connect a variety of enterprises. To reduce the
overall cost of the supply chain, these organizations should
cooperate. This necessitates that these entitiescooperate,
integrate, and share information. However, there is still a
disconnect between the supply chain network's ideal and
actual states. the digital transformation of the supply chain
is needed today more than ever. The Digital
Transformation has emerged as an important
preoccupation and a key strategic matter for all kinds of
organizations. One of the causes could be that producers
increased output in expectation of increased demand
despite not knowing the consumers' actual need. The goal
of this study is to identify several business applications of
machine learning (ML) in supply chain management. The
study examines instances of supply chain optimization that
make use ofmachine learning.
For the modern industrial sector, data created
by machine learning and devices, product lifecycle
management (PLM) tools, production planning tools, or
quality and inventory control tools has reached a volume of
more than a thousand Exabyte yearly and is anticipated to
rise in the next years. To store, manage, analyze, interpret,
and visualize such a large volume of data, Data technologies
are now required.Supply Chains (SC) are a network of
locations that connect a variety of enterprises. To reduce the
overall cost of the supply chain, these organizations should
cooperate. This necessitates that these entitiescooperate,
integrate, and share information. However, there is still a
disconnect between the supply chain network's ideal and
actual states. the digital transformation of the supply chain
is needed today more than ever. The Digital
Transformation has emerged as an important
preoccupation and a key strategic matter for all kinds of
organizations. One of the causes could be that producers
increased output in expectation of increased demand
despite not knowing the consumers' actual need. The goal
of this study is to identify several business applications of
machine learning (ML) in supply chain management. The
study examines instances of supply chain optimization that
make use ofmachine learning.
