TY - GEN
T1 - Manufacturing Line Design Configuration with Optimized Resource Groups
AU - Nakano, Takahiro
AU - Daiki, Kajita
AU - Chen, Heming
AU - Kovalenko, Ilya
AU - Balta, Efe
AU - Qamsane, Yassine
AU - Barton, Kira
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/8/23
Y1 - 2021/8/23
N2 - This research aims to develop methods to quickly build new manufacturing lines in response to changes in product varieties and manufacturing fluctuations in a factory. We propose a meta-heuristic algorithm for solving large-scale optimizations of the line design process, which includes resource configuration, process design, control design, and line configuration. The proposed framework improves the automation and system-level interactions of the line design process as compared to conventional methods that manually solve each step in the process design problem individually using skilled line engineers with previous experience. This research introduces the concept of a resource group or module that consists of various manufacturing resources such as robots, tools, autonomous guided vehicles, and conveyors. The line design process is then reconfigured for module or group configuration. To demonstrate the proposed framework, a case study is conducted in which the proposed framework is applied to the line design of an assembly manufacturing facility with production costs and manufacturing lead times selected as the key performance indicators of interest. Results indicate improved line costs and manufacturing lead times concurrently.
AB - This research aims to develop methods to quickly build new manufacturing lines in response to changes in product varieties and manufacturing fluctuations in a factory. We propose a meta-heuristic algorithm for solving large-scale optimizations of the line design process, which includes resource configuration, process design, control design, and line configuration. The proposed framework improves the automation and system-level interactions of the line design process as compared to conventional methods that manually solve each step in the process design problem individually using skilled line engineers with previous experience. This research introduces the concept of a resource group or module that consists of various manufacturing resources such as robots, tools, autonomous guided vehicles, and conveyors. The line design process is then reconfigured for module or group configuration. To demonstrate the proposed framework, a case study is conducted in which the proposed framework is applied to the line design of an assembly manufacturing facility with production costs and manufacturing lead times selected as the key performance indicators of interest. Results indicate improved line costs and manufacturing lead times concurrently.
UR - https://www.scopus.com/pages/publications/85117037456
UR - https://www.scopus.com/pages/publications/85117037456#tab=citedBy
U2 - 10.1109/CASE49439.2021.9551650
DO - 10.1109/CASE49439.2021.9551650
M3 - Conference contribution
AN - SCOPUS:85117037456
T3 - IEEE International Conference on Automation Science and Engineering
SP - 625
EP - 632
BT - 2021 IEEE 17th International Conference on Automation Science and Engineering, CASE 2021
PB - IEEE Computer Society
T2 - 17th IEEE International Conference on Automation Science and Engineering, CASE 2021
Y2 - 23 August 2021 through 27 August 2021
ER -