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Multi-task scheduling of distributed 3D printing services in cloud manufacturing

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Abstract

The problem of service matching and scheduling in cloud manufacturing (CMfg) is complex for different types of manufacturing services. 3D printing, as a rapidly developing manufacturing technology, has become an important service form in the CMfg platform due to its characteristics of personalized manufacturing. How to solve the task scheduling problem for distributed 3D printing services in CMfg needs further research. In this paper, a service transaction model of 3D printing services in CMfg is built. Based on the service transaction model, we propose 3D printing service matching strategies and matching rules of different service attributes, including model size, printing material, printing preciseness, task cost, task time, and logistics. To reduce the delivery time of tasks from service suppliers to service demanders, a 3D printing service scheduling (3DPSS) method is proposed to generate optimal service scheduling solutions. In 3DPSS, optimization objective, constraints, and optimization algorithm are presented in detail. Experimental results show that the average task delivery time of 3DPSS is shorter than that of typical scheduling methods, such as particle swarm optimization, pattern search, and sequential quadratic programming, when the amounts of tasks change.

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Acknowledgements

The authors would like to gratefully acknowledge the financial support of the National High-Tech Research and Development Plan of China (Grant No. 2015AA042101), the National Natural Science Foundation of China (Grant No. 61374199), and the Natural Science Foundation of Beijing Municipality (Grant No. 4142031).

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Authors and Affiliations

  1. School of Automation Science and Electrical Engineering, Beihang University, Beijing, China

    Longfei Zhou, Lin Zhang, Yuanjun Laili & Chun Zhao

  2. Engineering Research Center of Complex Product Advanced Manufacturing Systems, Ministry of Education, Beijing, China

    Longfei Zhou, Lin Zhang, Yuanjun Laili & Chun Zhao

  3. The Sate Key Laboratory of Intelligent Manufacturing System Technology, Beijing Institute of Electronic System Engineering, Beijing, China

    Yingying Xiao

Authors
  1. Longfei Zhou
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  2. Lin Zhang
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  3. Yuanjun Laili
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  4. Chun Zhao
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Corresponding author

Correspondence to Lin Zhang.

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Zhou, L., Zhang, L., Laili, Y. et al. Multi-task scheduling of distributed 3D printing services in cloud manufacturing. Int J Adv Manuf Technol 96, 3003–3017 (2018). https://doi.org/10.1007/s00170-017-1543-z

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  • DOI: https://doi.org/10.1007/s00170-017-1543-z

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