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2025 | OriginalPaper | Buchkapitel

The Bees Algorithm for Robotics-Enabled Collaborative Manufacturing

verfasst von : Wenjun Xu, Hang Yang, Zhenrui Ji, Zhihao Liu, Jiayi Liu

Erschienen in: Intelligent Engineering Optimisation with the Bees Algorithm

Verlag: Springer Nature Switzerland

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Abstract

Robotics-enabled collaborative manufacturing is vital to improving the efficiency and flexibility of industrial manufacturing processes and realising the digitalisation and intelligentisation of industry. In recent years, enabled by intelligent optimisation algorithms, robotics-enabled collaborative manufacturing approaches have been steadily developed as promising solutions to support industries. However, each robotics-enabled collaborative manufacturing approach has some optimisation problems, limiting its applicability in practice. To address this issue, in this chapter, the Bees Algorithm and robotics-enabled collaborative manufacturing are integrated as an effective approach. In this approach, the efficiency and flexibility of robotics-enabled collaborative manufacturing are significantly improved. Robotics-enabled collaborative manufacturing is composed of robotic collaborative manufacturing and human–robot collaborative manufacturing. In terms of robotic collaborative manufacturing, the improved multiobjective discrete Bees Algorithm and the improved discrete Bees Pareto algorithm are utilised to solve the robotic disassembly line balancing optimisation problem and multiobjective robotic collaborative manufacturing service aggregation optimal selection problem. In terms of human–robot collaborative manufacturing, the Pareto-based modified discrete Bees Algorithm is used to solve the task sequence planning optimisation problem. Afterwards, two case studies are presented to show the performance of the Bees Algorithm in robotics-enabled collaborative manufacturing. The results demonstrate that the Bees Algorithm is superior to some other comparative approaches.

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Metadaten
Titel
The Bees Algorithm for Robotics-Enabled Collaborative Manufacturing
verfasst von
Wenjun Xu
Hang Yang
Zhenrui Ji
Zhihao Liu
Jiayi Liu
Copyright-Jahr
2025
DOI
https://doi.org/10.1007/978-3-031-64936-3_10

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