Journal Article10.1016/J.RCIM.2019.101858
A dynamic and static data based matching method for cloud 3D printing
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TL;DR: A modeling framework is proposed to describe two models of the print task and print resource by model-based systems engineering that can support the efficient matching of the two types of models and can realistically simulate the supply-demand matching process of cloud 3D printing platform.
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Abstract: 3D printing is widely used in such sectors as industry, medical, sports and education with the rapid development 3D printing technology and continual breakthrough of new material technology. Faced with the continual expansion of 3D printing market and the diversity and rapid growth of the scale of 3D printing devices, efficiently manage 3D print resources in the environment of distributed network manufacturing is a critical problem urgently to resolve. As a novel business paradigm, Cloud manufacturing can effectively integrate and manage manufacturing resources. Therefore, based on the cloud manufacturing paradigm, this study focuses on dynamic and static data based matching method for cloud 3D printing. In this paper, we propose a modeling framework to describe two models of the print task and print resource by model-based systems engineering. This modeling framework can support the efficient matching of the two types of models. Finally, the dynamic and static data based matching method can realistically simulate the supply-demand matching process of cloud 3D printing platform and provide a technical solution for quick supply-demand matching of large-scale resources in the environment of cloud manufacturing. During in the modeling process, we not only consider the static characteristics of 3D printers and analyze quantitatively all the parameter indicators of static characteristics, but also consider the dynamic characteristics of 3D printers to establish a universal dynamic data acquisition system, which can be used for real-time monitoring and automatic diagnosis of the health status of 3D printers. Therefore, this matching method has important theoretical significance and engineering value.
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3D Printing in the Context of Cloud Manufacturing
Jin Cui,Jin Cui,Natalie Glynn,Lei Ren,Lei Ren,Ubiratan Silva Alves,Jingeng Mai,Pai Zheng,Lin Zhang,Lin Zhang +9 more
TL;DR: A comprehensive study of 3D printing in cloud manufacturing environment is presented and two typical models of3D printing, i.e. primary 3D printer cloud model and advanced 3D Printing cloud model are presented and compared and the system architecture design of a 3D printers cloud platform is proposed to support the latter model.
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Game theory based multi-task scheduling of decentralized 3D printing services in cloud manufacturing
TL;DR: A two-layer nested method based on genetic algorithm is developed to improve scheduling efficiency and shows that it has a better performance than traditional scheduling methods.
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Towards sustainable industry 4.0: A green real-time IIoT multitask scheduling architecture for distributed 3D printing services
TL;DR: In this paper, a real-time green-aware multi-task scheduling architecture for personalized 3D printing tasks in the Industrial Internet of Things (IIoT) is proposed, which is divided into two interconnected folds, namely, allocation and scheduling.
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