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TopThe three-dimensional printing cloud platform (3DPCP) is an online service platform based on 3D printing technology, facilitating efficient collaboration with multiple entities, including demand, production, and logistics (Cui et al., 2022). Among them, 3D printing (3DP) is a disruptive technology boasting not only production advantages such as high digitization, rapid prototyping, and print-on-demand but also environmental advantages like low energy consumption and minimal material waste (Karimi & Ning, 2021; Sgarbossa et al., 2021; Srinivasan et al., 2018). Moreover, cloud platforms serve as service platforms combining technologies like cloud computing and the Internet, characterized by resource optimization and fostering green and sustainable manufacturing processes (Feng et al., 2022; Lin & Ma, 2022; Wu et al., 2022). With the rapid development of emerging technologies, the application of 3DPCP continues to grow (Zhong et al., 2022). Industry players like Xometry have established an extensive network of manufacturer partnerships, providing convenient 3DP manufacturing services to various customers (Wu et al., 2022). Similarly, platforms like 3D Hubs, Shapeways, Sculpteo, and Quickparts provide cloud-based 3DP services (Darwish et al., 2021).
As the global market evolves and competition escalates, how manufacturing companies improve their competitiveness has become a critical issue (Zhang et al., 2024). Scheduling serves as a key means to achieve the goals of cloud platforms and promote sustainable manufacturing (Alvarez-Meaza et al., 2021; Liu et al., 2019). Many scholars have researched 3DPCP scheduling. Still, various challenges persist in addressing multi-dynamic information perturbations in green scenes. Compared with traditional approaches, scheduling tasks in 3DPCP within green scenes has several characteristics:
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Resource and task distribution: Task scheduling in green scenes aims to coordinate customer-uploaded tasks with resources provided by suppliers, necessitating a resource and task-distributed 3DPCP model.
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Integration of 3DP and environmental material production: Deeper integration of the 3DP manufacturing industry with eco-friendly materials will lead to a diversity of materials. Therefore, attributes like material and accuracy must be considered in the scheduling process.
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Interconnection with the clean energy industry: The interconnection of the clean energy industry with the 3D printing manufacturing industry can respond to energy efficiency needs. However, clean energy availability varies geographically, requiring task scheduling adjustments based on the availability of clean energy (Tan & Lin, 2023).
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Integration with the logistics industry: Green scenes will drive the integration of the logistics industry with 3DPCP, necessitating closer coordination between production and transportation. This will require more efficient task-scheduling strategies.
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Autonomous handling of dynamic information: Traditional scheduling methods usually address task scheduling under the real-time arrival of order information. However, considering multi-dynamic information perturbations, 3DPCP should autonomously deal with dynamic information, such as order arrivals and cancellations, device additions and failures, and device time-window changes for intelligent manufacturing.