Abstract
The 3D printing cloud platform (3DPCP) plays a pivotal role in breaking down the information silos between supply and demand, effectively reducing waste through information integration and intelligent production. However, due to the complexity of 3DPCP scheduling in green scenes and the multidynamic information perturbations, unveils problems in traditional task scheduling methods in 3DPCP. These issues manifest as incomplete considerations, subpar green performance, and weak adaptability to dynamic changes. There is an urgent need to design practical methods to realize the multidynamic information perturbations in green scenes within 3DPCP. Therefore, this article first defines the 3DPCP task scheduling problem for multidynamic information perturbation in green scenes. Second, the article proposes a task scheduling model and a heuristic task scheduling strategy to minimize both the average cost and carbon dioxide (CO2) emissions per unit of quality product. Finally, the article validates effectiveness and superiority of the proposed strategy through simulation experiments. © 2024 IGI Global. All rights reserved.
| Original language | English |
|---|---|
| Journal | Journal of Global Information Management |
| Volume | 32 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 2024 |
Funding
The work was supported by the National Natural Science Foundation of China [grant number 71871144], Shanghai Philosophy and Social Science Planning [grant number 2023BGL009], and the Science and Technology Development Project of the University of Shanghai for Science and Technology [grant number 2020KJFZ046].
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 13 Climate Action
Research Keywords
- 3D Printing Cloud Platform (3DPCP)
- Green Scene
- Heuristic Scheduling Strategy
- Multidynamic Information
- Task Scheduling
Publisher's Copyright Statement
- This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/
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