Co-Optimization of Supply Chain Reconfiguration and Assembly Process Planning for Factory-in-a-Box ManufacturingSource: Journal of Manufacturing Science and Engineering:;2022:;volume( 144 ):;issue: 010::page 101006-1Author:Nwodu
,
Arriana;Pasha
,
Junayed;Jiang
,
Zhengqian;Guo
,
Weihong;Dulebenets
,
Maxim;Wang
,
Hui;Minor
,
Kayla
DOI: 10.1115/1.4054519Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Factory in a box (FiB) is an emerging technology that meets the dynamic and diverse market demand by carrying a factory module on vehicles to perform on-site production near customers’ locations. It is suitable for meeting time-sensitive demands, such as the outbreak of disasters or epidemics/pandemics. Compared to traditional manufacturing, FiB poses a new challenge of frequently reconfiguring supply chain networks since the final production location changes as the vehicle carrying the factory travels. Supply chain network reconfiguration involves decisions regarding whether suppliers or manufacturers can be retained in the supply chain or replaced. Such a supply chain reconfiguration problem is coupled with manufacturing process planning, which assigns tasks to each manufacturer that impacts material flow in the supply chain network. Considering the supply chain reconfigurability, this article develops a new mathematical model based on nonlinear integer programming to optimize supply chain reconfiguration and assembly planning jointly. An evolutionary algorithm (EA) is developed and customized to the joint optimization of process planning and supplier/manufacturer selection. The performance of EA is verified with a nonlinear solver for a relaxed version of the problem. A case study on producing a medical product demonstrates the methodology in guiding supply chain reconfiguration and process planning as the final production site relocates in response to local demands. The methodology can be potentially generalized to supply chain and service process planning for a mobile hospital offering on-site medical services.
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| contributor author | Nwodu | |
| contributor author | Arriana;Pasha | |
| contributor author | Junayed;Jiang | |
| contributor author | Zhengqian;Guo | |
| contributor author | Weihong;Dulebenets | |
| contributor author | Maxim;Wang | |
| contributor author | Hui;Minor | |
| contributor author | Kayla | |
| date accessioned | 2022-08-18T13:01:21Z | |
| date available | 2022-08-18T13:01:21Z | |
| date copyright | 5/25/2022 12:00:00 AM | |
| date issued | 2022 | |
| identifier issn | 1087-1357 | |
| identifier other | manu_144_10_101006.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4287283 | |
| description abstract | Factory in a box (FiB) is an emerging technology that meets the dynamic and diverse market demand by carrying a factory module on vehicles to perform on-site production near customers’ locations. It is suitable for meeting time-sensitive demands, such as the outbreak of disasters or epidemics/pandemics. Compared to traditional manufacturing, FiB poses a new challenge of frequently reconfiguring supply chain networks since the final production location changes as the vehicle carrying the factory travels. Supply chain network reconfiguration involves decisions regarding whether suppliers or manufacturers can be retained in the supply chain or replaced. Such a supply chain reconfiguration problem is coupled with manufacturing process planning, which assigns tasks to each manufacturer that impacts material flow in the supply chain network. Considering the supply chain reconfigurability, this article develops a new mathematical model based on nonlinear integer programming to optimize supply chain reconfiguration and assembly planning jointly. An evolutionary algorithm (EA) is developed and customized to the joint optimization of process planning and supplier/manufacturer selection. The performance of EA is verified with a nonlinear solver for a relaxed version of the problem. A case study on producing a medical product demonstrates the methodology in guiding supply chain reconfiguration and process planning as the final production site relocates in response to local demands. The methodology can be potentially generalized to supply chain and service process planning for a mobile hospital offering on-site medical services. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Co-Optimization of Supply Chain Reconfiguration and Assembly Process Planning for Factory-in-a-Box Manufacturing | |
| type | Journal Paper | |
| journal volume | 144 | |
| journal issue | 10 | |
| journal title | Journal of Manufacturing Science and Engineering | |
| identifier doi | 10.1115/1.4054519 | |
| journal fristpage | 101006-1 | |
| journal lastpage | 101006-13 | |
| page | 13 | |
| tree | Journal of Manufacturing Science and Engineering:;2022:;volume( 144 ):;issue: 010 | |
| contenttype | Fulltext |