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Manufacturing Cell Integrated Layout Method Based on RNS-FOA Algorithm in Smart Factory
by
Zhao, Yanlin
in
Adaptive algorithms
/ Algorithms
/ Factories
/ Internet of Things
/ Logistics
/ Manufacturing cells
/ Mathematical analysis
/ Mathematical models
/ Methods
/ Monolayers
/ Multilayers
/ Optimization
/ Plant layout
/ Product life cycle
/ Product lifecycle management
/ Stability
2022
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Manufacturing Cell Integrated Layout Method Based on RNS-FOA Algorithm in Smart Factory
by
Zhao, Yanlin
in
Adaptive algorithms
/ Algorithms
/ Factories
/ Internet of Things
/ Logistics
/ Manufacturing cells
/ Mathematical analysis
/ Mathematical models
/ Methods
/ Monolayers
/ Multilayers
/ Optimization
/ Plant layout
/ Product life cycle
/ Product lifecycle management
/ Stability
2022
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Do you wish to request the book?
Manufacturing Cell Integrated Layout Method Based on RNS-FOA Algorithm in Smart Factory
by
Zhao, Yanlin
in
Adaptive algorithms
/ Algorithms
/ Factories
/ Internet of Things
/ Logistics
/ Manufacturing cells
/ Mathematical analysis
/ Mathematical models
/ Methods
/ Monolayers
/ Multilayers
/ Optimization
/ Plant layout
/ Product life cycle
/ Product lifecycle management
/ Stability
2022
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Manufacturing Cell Integrated Layout Method Based on RNS-FOA Algorithm in Smart Factory
Journal Article
Manufacturing Cell Integrated Layout Method Based on RNS-FOA Algorithm in Smart Factory
2022
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Overview
The research on the layout of multi-layer manufacturing cells for smart factories is still in its infancy, but there is an urgent need to address this issue in building smart factories. This paper presents the Manufacturing Cell Integrated Layout (MCIL) Method, which integrates multiple layout forms of multi-layer and single-layer manufacturing cells. The paper develops a mathematical model of the MCIL problem which considers the multi-objective functions of logistics handling, occupied space, cell stability, lost time, and non-logistics relations, as well as the constraints between equipment in the cell and cells. An adaptive RNS-FOA algorithm is proposed to solve the high-dimensional and large-scale characteristics of the MCIL problem based on the research of academics. Lastly, a case demonstrates the outstanding contribution of the mathematical model to the solution of the MCIL problem, while simultaneously validating the efficiency and stability of the RNS-FOA algorithm for solving the MCIL problem.
Publisher
MDPI AG
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