International Journal of Control, Automation, and Systems 2024; 22(11): 3377-3385
https://doi.org/10.1007/s12555-024-0040-z
© The International Journal of Control, Automation, and Systems
An automated material handling system (AMHS) is a production line component responsible for transporting products from one machine to another for manufacturing processes. The AMHS also acts as a buffer that enhances overall productivity by reducing the dependency on individual machine operations. This paper introduces a buffer parameter optimization algorithm designed for advanced AMHS with the capability to control the speed of individual products. The buffer parameters targeted for optimization are buffer length (distance between machines) and transfer speed. The algorithm addresses each parameter separately through two distinct optimization problems. The buffer length optimization problem is formulated with the constraint of limited space assigned to the production system. On the other hand, the transfer speed optimization problem is formulated based on the constraints of network resources and hardware limitations. The proposed algorithm employs an aggregation method to evaluate the performance of the production systems analytically.
Keywords AMHS, Industry 4.0, optimization, production system, smart factory.
International Journal of Control, Automation, and Systems 2024; 22(11): 3377-3385
Published online November 1, 2024 https://doi.org/10.1007/s12555-024-0040-z
Copyright © The International Journal of Control, Automation, and Systems.
Seunghyeon Kim, Kyung-Joon Park, and Yongsoon Eun*
DGIST
An automated material handling system (AMHS) is a production line component responsible for transporting products from one machine to another for manufacturing processes. The AMHS also acts as a buffer that enhances overall productivity by reducing the dependency on individual machine operations. This paper introduces a buffer parameter optimization algorithm designed for advanced AMHS with the capability to control the speed of individual products. The buffer parameters targeted for optimization are buffer length (distance between machines) and transfer speed. The algorithm addresses each parameter separately through two distinct optimization problems. The buffer length optimization problem is formulated with the constraint of limited space assigned to the production system. On the other hand, the transfer speed optimization problem is formulated based on the constraints of network resources and hardware limitations. The proposed algorithm employs an aggregation method to evaluate the performance of the production systems analytically.
Keywords: AMHS, Industry 4.0, optimization, production system, smart factory.
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