Robotic disassembly sequence planning using enhanced discrete bees algorithm in remanufacturing

Research output: Contribution to journalArticle

Authors

  • Jiayi Liu
  • Zude Zhou
  • Wenjun Xu
  • Quan Liu

Colleges, School and Institutes

External organisations

  • Wuhan University of Technology
  • Department of Mechanical Engineering

Abstract

Increasing attention is being paid to remanufacturing due to environmental protection and resource saving. Disassembly, as an essential step of remanufacturing, is always manually finished which is time-consuming while robotic disassembly can improve disassembly efficiency. Before the execution of disassembly, generating optimal disassembly sequence plays a vital role in improving disassembly efficiency. In this paper, to minimise the total disassembly time, an enhanced discrete Bees algorithm (EDBA) is proposed to solve robotic disassembly sequence planning (RDSP) problem. Firstly, the modified feasible solution generation (MFSG) method is used to build the disassembly model. After that, the evaluation criterions for RDSP are proposed to describe the total disassembly time of a disassembly sequence. Then, with the help of mutation operator, EDBA is proposed to determine the optimal disassembly sequence of RDSP. Finally, case studies based on two gear pumps are used to verify the effectiveness of the proposed method. The performance of EDBA is analysed under different parameters and compared with existing optimisation algorithms used in disassembly sequence planning (DSP). The result shows the proposed method is more suitable for robotic disassembly than the traditional method and EDBA generates better quality of solutions compared with the other optimisation algorithms.

Details

Original languageEnglish
Pages (from-to)3134-3151
Number of pages18
JournalInternational Journal of Production Research
Volume56
Issue number9
Early online date8 Dec 2017
Publication statusPublished - 3 May 2018

Keywords

  • disassembly sequence planning, enhanced discrete bees algorithm, intelligent optimisation, remanufacturing, robotic disassembly sequence planning