An improved multi-objective discrete bees algorithm for robotic disassembly line balancing problem in remanufacturing

An improved multi-objective discrete bees algorithm for robotic disassembly line balancing... Remanufacturing is an effective way to realize the reutilization of resources. Disassembly, as an essential step of remanufacturing, is usually finished by manual work which is low efficiency and high labor cost. Robotic disassembly provides an alternative way to reduce labor intensity and disassembly cost. Disassembly line is an efficient method to deal with end-of-life products on a large scale. Balancing the workload of robotic workstations is the main objective of robotic disassembly line balancing problem. In this paper, an improved multi-objective discrete bees algorithm is proposed to solve robotic disassembly line balancing problem. The feasible disassembly sequence is obtained by space interference matrix method. It is used to generate robotic disassembly line solution by robotic workstation assignment method. After that, the multi-objective robotic disassembly line balancing problem is proposed. With the help of efficient non-dominated Pareto sorting method, the improved multi-objective discrete bees algorithm is proposed to find Pareto optimal solutions. Based on a gear pump and a camera, the performance of the improved multi-objective discrete bees algorithm is analyzed under different parameters and compared with the other optimization algorithms. In addition, Pareto fronts of robotic disassembly line balancing problem are also compared with those of the other two cases. The result shows the proposed method can find better solutions using comparable running time compared with the other optimization algorithms. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The International Journal of Advanced Manufacturing Technology Springer Journals

An improved multi-objective discrete bees algorithm for robotic disassembly line balancing problem in remanufacturing

Loading next page...
 
/lp/springer_journal/an-improved-multi-objective-discrete-bees-algorithm-for-robotic-nkUY0msWWu
Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer-Verlag London Ltd., part of Springer Nature
Subject
Engineering; Industrial and Production Engineering; Media Management; Mechanical Engineering; Computer-Aided Engineering (CAD, CAE) and Design
ISSN
0268-3768
eISSN
1433-3015
D.O.I.
10.1007/s00170-018-2183-7
Publisher site
See Article on Publisher Site

Abstract

Remanufacturing is an effective way to realize the reutilization of resources. Disassembly, as an essential step of remanufacturing, is usually finished by manual work which is low efficiency and high labor cost. Robotic disassembly provides an alternative way to reduce labor intensity and disassembly cost. Disassembly line is an efficient method to deal with end-of-life products on a large scale. Balancing the workload of robotic workstations is the main objective of robotic disassembly line balancing problem. In this paper, an improved multi-objective discrete bees algorithm is proposed to solve robotic disassembly line balancing problem. The feasible disassembly sequence is obtained by space interference matrix method. It is used to generate robotic disassembly line solution by robotic workstation assignment method. After that, the multi-objective robotic disassembly line balancing problem is proposed. With the help of efficient non-dominated Pareto sorting method, the improved multi-objective discrete bees algorithm is proposed to find Pareto optimal solutions. Based on a gear pump and a camera, the performance of the improved multi-objective discrete bees algorithm is analyzed under different parameters and compared with the other optimization algorithms. In addition, Pareto fronts of robotic disassembly line balancing problem are also compared with those of the other two cases. The result shows the proposed method can find better solutions using comparable running time compared with the other optimization algorithms.

Journal

The International Journal of Advanced Manufacturing TechnologySpringer Journals

Published: Jun 4, 2018

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off