Exploring the factors to promote circular supply chain implementation in the smart logistics ecological chain

2022 ◽  
Vol 101 ◽  
pp. 57-70
Author(s):  
Xiaoyu Yan ◽  
Weihua Liu ◽  
Ming K. Lim ◽  
Yong Lin ◽  
Wanying Wei
Keyword(s):  
Supply Chain ◽  
Smart Logistics

scholarly journals Artificial Intelligence Applications in the New Model of Logistics Development Based on Wireless Communication Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-5
Author(s):  
Shuaiqi Wang
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Internet Of Things ◽  
Cost Reduction ◽  
Sharing Economy ◽  
Smart Logistics ◽  
Supply Chain Logistics ◽  
Service Efficiency ◽  
Artificial Intelligence Technology ◽  
The Internet Of Things

With the continuous development of artificial intelligence technology, the supply chain logistics industry has shown new changes. The products of the intelligent era such as smart devices, big data computing, and Internet of Things technology have gradually become the transformation and innovation of logistics and supply chain enterprises. The important driving force of the logistics and supply chain industry will greatly improve the operational efficiency of the logistics and supply chain industry. Methods. This article studies the technical framework of artificial intelligence and explores the upgrading and transformation of supply chain logistics enterprises in logistics infrastructure, production tools, and logistics operation processes under the promotion of artificial intelligence technology, from warehouse location, inventory management, warehousing operations, transportation, and distribution. The data analysis and prediction analyze the impact of artificial intelligence on the supply chain logistics field and finally point out the problems in the intelligent development of the supply chain logistics field and put forward targeted suggestions to promote the modern supply chain logistics to become more intelligent. developThe new development trend of smart logistics is towards sharing economy, automation, service efficiency, and cost reduction. Results. In this context, if logistics companies want to achieve higher-quality development, they cannot do without business model innovation and larger-scale collaboration, transparency of logistics information, and more comprehensive information sharing. The new trend of the development of smart logistics is to develop in the direction of sharing economy, automation, service efficiency, and cost reduction. Conclusion. Intelligence and the Internet of Things are the inevitable trend of the development of smart logistics, which is mainly realized through the Internet of Things path in terms of visual information technology, intelligent robot operation, vehicle scheduling, and cargo traceability.

scholarly journals Manufactura inteligente y logística como un medio del desarrollo de pequeñas y medianas empresas

Indagare ◽  
2019 ◽  
Author(s):  
Laura Patricia Carranza Murillo
Keyword(s):  
Supply Chain ◽  
Smart Logistics

En el marco de la XI Escuela Internacional de Verano, la revista Indagare habló con el doctor Helmut Zsifkovits acerca su experiencia de trabajo en conjunto con la Universidad de Ibagué, a través de la asignatura Smart Logistics and Supply Chain. El doctor Zsifkovits nos comentó sobre de la importancia de estas temáticas en el desarrollo de pequeñas y medianas empresas, su participación en proyectos de investigación en el ámbito internacional y programas relacionados con la movilidad estudiantil y formación de lazos de colaboración con universidades en Colombia y Latinoamérica.

scholarly journals A new approach in Supply Chain Processes – Smart Logistics

2017 ◽  
Vol 121 ◽  
pp. 07004 ◽  
Author(s):  
Olga Bucovetchi ◽  
Andreia Elena Simioana ◽  
Radu D. Stanciu
Keyword(s):  
Supply Chain ◽  
New Approach ◽  
Chain Processes ◽  
Smart Logistics

scholarly journals Intelligent Measurement and Monitoring of Carbon Emissions for 5G Shared Smart Logistics

2022 ◽  
Vol 2022 ◽  
pp. 1-13
Author(s):  
Ailing Zhang ◽  
Sha Li ◽  
Lin Tan ◽  
Yingchao Sun ◽  
Fuxiao Yao
Keyword(s):  
Supply Chain ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Emission Factor ◽  
Carbon Emission ◽  
Storage Technology ◽  
Factor Method ◽  
Smart Logistics ◽  
Intelligent Measurement ◽  
Logistics Process

With the upgrading of logistics demand and the innovation of modern information technology, the smart logistics platform integrates advanced concepts, technologies, and management methods, maximizes the integration of logistics resources and circulation channels, and effectively improves the efficiency of logistics transactions, but its energy consumption problem is particularly prominent. The study of intelligent measurement and monitoring of carbon emissions in smart logistics is of great value to reduce energy consumption, reduce carbon emissions in buildings, and improve the environment. In this paper, by comparing and analyzing the accounting standards of carbon emissions and their calculation methods, the carbon emission factor method is selected as the method to study the carbon emissions of the smart logistics process in this paper. The working principle of each key storage technology in the smart logistics process is analyzed to find out the equipment factors affecting the carbon emission of each storage technology in the smart logistics process, and the carbon emission calculation model of each key storage technology is established separately by using the carbon emission factor method. Meanwhile, according to the development history of energy consumption assessment, the assessment process of different stages from logistics storage energy consumption assessment to smart logistics energy consumption assessment is analyzed, and based on this, a carbon emission energy consumption assessment framework based on 5G shared smart logistics is constructed. This paper applies the supply chain idea to define the smart logistics supply chain, constructs a conceptual model of the smart logistics supply chain considering carbon emissions, and at the same time combines the characteristics of the smart logistics supply chain to analyze the correlation between the carbon emissions of the smart logistics supply chain and the related social, environmental, and economic systems.

scholarly journals Smart Logistics and Supply Chain with Machine Learning and IoT

2021 ◽  
Vol 9 (VI) ◽  
pp. 2180-2184
Author(s):  
Pranav R.M
Keyword(s):  
Machine Learning ◽  
Supply Chain ◽  
Internet Of Things ◽  
Customer Satisfaction ◽  
Small Businesses ◽  
Smart Logistics ◽  
Rural Businesses ◽  
Complex Process ◽  
The Right ◽  
The Military

Logistics is an important part of the Supply Chain. The management of logistics and supply chain is a complex process of planning and management of services, goods from the origin to the point of consumption. Logistics is defined as the process of managing movement of goods in and out of an organization. Supply Chain is defined as the process of managing movement and coordination of goods in between multiple organizations. Together Logistics and Supply Chain includes planning the transport, warehousing, inventory and sales an example of logistics could be the military stockpiling ammo whereas an example of Supply Chain management is making sure the right amount of goods reaches the destination, supplying more could lead to increased storage costs and supplying less could lead to inefficiencies. So, the main objective of Logistics is customer satisfaction and the main objective of Supply Chain is to have a competitive advantage by being more efficient. This project aims to have both customer satisfaction and efficiency and will achieved by implementing Internet of Things and Machine Learning to Logistics and Supply Chain. Large Corporations invest a lot of money to improve supply chains. This paper aims to help small businesses and rural businesses to improve their Supply Chain. This project aims at providing customer satisfaction and efficiency. Implementation using IoT and machine learning provides better efficiency. Keywords— Smart Logistics, Smart Supply Chain, Industry 4.0, Internet of Things, Machine Learning.

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