Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Using AI to generate Robot Disassembly Planning in Autonomous Remanufacturing Process based on Slicing and CAD technologies
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
2023 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The effects of climate change and the need for sustainable practices have brought attention to the need to handle end-of-life (EOL) item disposal, especially in sectors like automotive manufacturing. The idea of a circular economy, which encourages repairing, reusing, and recycling goods, has gained popularity as an achievable option. The circular economy is greatly aided by remanufacturing, which prolongs the life of EOL products. Robotic disassembly is a crucial step in the remanufacturing process, but it is difficult because EOL products vary so much and because industrial robots nowadays have certain limits. Therefore, the research will focus on the creation of a 3D spatial model and a Bee Swarm Optimization (BSO) algorithm that utilizes prior spatial information for automated disassembly path planning. The efficiency of the automated disassembly path planning will be evaluated using two evaluation techniques; Chebyshev and the Euclidean distance, to minimize the path for Disassembly Path process. The results for the extraction of spatial information using slicing technology were satisfactory, however, the BSO results can be enhanced more by introducing complex optimization techniques. The necessity to use AI and CAD models to optimize the disassembly process while considering the limitations and complexities of EOL products and industrial robots forms the basis for this research. The focus of this thesis is on automated robotic disassembly planning, including planning the disassembly sequence and identifying spatial restrictions. The design of a robotic environment or of custom algorithms is not part of the research.

Place, publisher, year, edition, pages
2023.
Keywords [en]
Disassembly, EOL, Robotic Disassembly Process (RDP), Computer Aided Drawing (CAD), Disassembly Path Planning (DPP), Bee Swarm Optimization Algorithm (BSO)
National Category
Robotics
Identifiers
URN: urn:nbn:se:ltu:diva-101508OAI: oai:DiVA.org:ltu-101508DiVA, id: diva2:1801438
External cooperation
Leeds Beckett University; Universiti Kebangsaan Malaysia; The University of Nottingham Malaysia
Subject / course
Student thesis, at least 30 credits
Educational program
Master Programme in Green Networking and Cloud Computing
Supervisors
Examiners
Available from: 2023-10-18 Created: 2023-10-01 Last updated: 2023-10-18Bibliographically approved

Open Access in DiVA

No full text in DiVA

By organisation
Department of Computer Science, Electrical and Space Engineering
Robotics

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 26 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf