Dynamic Modeling of Manufacturing Capability for Robotic Disassembly in Remanufacturing

Zongqing Zheng, Wenjun Xu, Zude Zhou, Duc Truong Pham, Yongzhi Qu, Jian Zhou

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)
181 Downloads (Pure)

Abstract

Product disassembly plays an important role in the sustainable manufacturing, and it is usually the first step in remanufacturing process, which determines the efficiency and capability of remanufacturing. Industrial robot (IR) as an intelligent manufacturing equipment to increase the productivity and reduce energy consumption (EC), has been applied to semi-automated product disassembly, and the thing that matters is studying and modeling of manufacturing capability for robotic disassembly in remanufacturing. In this paper, the IR disassembly capability is modeled dynamically using OWL, based on the mapping relation which associating the disassembly capability attributes and the real-time data. Furthermore, a method of association rules mining (ARM) based on bees algorithm (BA) is proposed to mine the association relationships from the data of disassembly processes. The effectiveness of the proposed modeling method is validated by a case study, and the results show that the dynamic modeling method could efficiently reflect the current state and dynamic capability of IRs during product disassembly process in remanufacturing.

Original languageEnglish
Pages (from-to)15-25
Number of pages11
JournalProcedia Manufacturing
Volume10
Early online date7 Jul 2017
DOIs
Publication statusE-pub ahead of print - 7 Jul 2017

Keywords

  • Association Rules Mining
  • Disassembly Capability
  • Industrial Robot
  • Meta-data Model
  • Ontology

ASJC Scopus subject areas

  • Artificial Intelligence
  • Industrial and Manufacturing Engineering

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