Parallel Turning Process Parameter Optimization Based on a Novel Heuristic Approach

Author

Lie Tang
Robert G. Landers, Missouri University of Science and TechnologyFollow
S. N. Balakrishnan, Missouri University of Science and TechnologyFollow

Abstract

Process parameter optimization has been widely investigated in single-tool machining operations. However, for multitool machining operation optimization, the research reported in literature is scarce. in this paper, a novel heuristic algorithm based on particle swarm optimization (PSO) is proposed to optimize, in terms of minimum machining time, the process parameters for two-tool parallel turning operations with n features. Both single-pass and multipass operations are considered. the simulation results show that the performance of the proposed algorithm, in terms of total machining time and required computational time, is superior to an exhaustive search algorithm

Recommended Citation

L. Tang et al., "Parallel Turning Process Parameter Optimization Based on a Novel Heuristic Approach," Journal of Manufacturing Science and Engineering, American Society of Mechanical Engineers (ASME), Jun 2008.

The definitive version is available at https://doi.org/10.1115/1.2823077

Department(s)

Mechanical and Aerospace Engineering

Sponsor(s)

National Science Foundation (U.S.)

International Standard Serial Number (ISSN)

1087-1357

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2008 American Society of Mechanical Engineers (ASME), All rights reserved.

Publication Date

01 Jun 2008