Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Roza Dastres"'
Publikováno v:
Data Science and Management, Vol 7, Iss 1, Pp 47-63 (2024)
Virtual manufacturing is one of the key components of Industry 4.0, the fourth industrial revolution, in improving manufacturing processes. Virtual manufacturing enables manufacturers to optimize their production processes using real-time data from s
Externí odkaz:
https://doaj.org/article/4e84db6649fe474d8a36dea04e716eef
Publikováno v:
Sustainable Operations and Computers, Vol 5, Iss , Pp 73-87 (2024)
To minimize the quantities of carbon emissions produced by the production process, sustainable manufacturing should be implemented. CNC machining operations can be made more sustainable by optimizing machining parameters to reduce material waste and
Externí odkaz:
https://doaj.org/article/5f6782095ce1417d98a8115de538234e
Publikováno v:
Journal of Economy and Technology, Vol 1, Iss , Pp 179-196 (2023)
Artificial Neural Networks (ANNs) are a type of machine learning algorithm inspired by the structure and function of the human brain. In the context of supply chain management, ANNs can be used for demand forecasting, inventory optimization, logistic
Externí odkaz:
https://doaj.org/article/e8c9194193774d01b3340ca48ae56e76
Publikováno v:
Journal of Economy and Technology, Vol 1, Iss , Pp 222-241 (2023)
Artificial Intelligence (AI) algorithms can be employed to enhance the security of the blockchain networks in the era of industry 4.0. Smart contracts, powered by blockchain, can be developed by using the AI capabilities. These contracts can execute
Externí odkaz:
https://doaj.org/article/2ba72751cb7c480f9b00c28d998230b5
Publikováno v:
Sustainable Manufacturing and Service Economics, Vol 3, Iss , Pp 100026- (2024)
The integration of blockchain technology in the Industrial Internet of Things (IIoT) for sustainable supply chain management in the context of Industry 4.0 offers several potential benefits. A public and auditable record of the environmental impact o
Externí odkaz:
https://doaj.org/article/283349cbc53344a381da8233d3d4176f
Publikováno v:
Internet of Things and Cyber-Physical Systems, Vol 3, Iss , Pp 192-204 (2023)
The Internet of Things (IoT) is playing a significant role in the transformation of traditional factories into smart factories in Industry 4.0 by using network of interconnected devices, sensors, and software to monitor and optimize the production pr
Externí odkaz:
https://doaj.org/article/690430a2f16b4a108cbbcb57c1fd7ed3
Publikováno v:
Cognitive Robotics, Vol 3, Iss , Pp 142-157 (2023)
Optimization of energy consumption in industrial robots can reduce operating costs, improve performance and increase the lifespan of the robot during part manufacturing. Choosing energy-efficient components such as motors, drives, and controllers can
Externí odkaz:
https://doaj.org/article/4b0914e7f0c34757898fd4488e628075
Publikováno v:
Cognitive Robotics, Vol 3, Iss , Pp 54-70 (2023)
Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) have revolutionized the field of advanced robotics in recent years. AI, ML, and DL are transforming the field of advanced robotics, making robots more intelligent, efficient,
Externí odkaz:
https://doaj.org/article/6f717dfeaf374caba8266538020d5430
Publikováno v:
Sustainable Manufacturing and Service Economics, Vol 2, Iss , Pp 100009- (2023)
Artificial Intelligence (AI) and Machine learning (ML) represents an important evolution in computer science and data processing systems which can be used in order to enhance almost every technology-enabled service, products, and industrial applicati
Externí odkaz:
https://doaj.org/article/3cec3e63e6c8437984c14a243028b990
Publikováno v:
Sustainable Manufacturing and Service Economics, Vol 2, Iss , Pp 100017- (2023)
A virtual representation of a physical procedure or product is called digital twin which can enhance efficiency and reduce costs in manufacturing process. Utilizing the digital twin, production teams can examine various data sources and reduce the nu
Externí odkaz:
https://doaj.org/article/4cc2cb7be8234b9685bada5bc27c7f81