An effective and automatic approach for parameters optimization of complex end milling process based on virtual machining
Hengyuan Ma,
Wei Liu (),
Xionghui Zhou (),
Qiang Niu and
Chuipin Kong
Additional contact information
Hengyuan Ma: Shanghai Jiao Tong University
Wei Liu: Shanghai Jiao Tong University
Xionghui Zhou: Shanghai Jiao Tong University
Qiang Niu: Shanghai Jiao Tong University
Chuipin Kong: Shanghai Jiao Tong University
Journal of Intelligent Manufacturing, 2020, vol. 31, issue 4, No 11, 967-984
Abstract:
Abstract The demand for optimization of manufacturing processes rises as a reflection of the highly competitive market environment that requires shorter lead time and lower production costs. Although some approaches to milling process optimization have been developed based on analytical model using average cutting parameters, they are not available for complex workpieces when cutting parameters are time-varying and instantaneous cutting conditions need to be considered. In order to automate the optimization process and avoid costly machining tests, in this paper, an effective approach for parameters optimization of complex end milling process based on virtual machining is proposed. A computer-aided design (CAD)/computer-aided manufacturing (CAM) application is integrated for actual tool path generation and feedrate scheduling based on material removal rate. Then, a machining simulator based on octree and instantaneous force model is developed to evaluate feasibility of the given numerical control (NC) program, and the correctness of this simulator is verified by machining tests. The optimization process is controlled by the efficient global optimization method to find global optimal solution with fewer simulations and less computation time. During each iteration of the optimization process, NC programs are generated and evaluated automatically by the CAD/CAM application and the simulator, respectively. The effectiveness and efficiency of the proposed approach are proved by comparing the generated optimal solution (has reduced machining time and production cost) with the recommended cutting parameters from machining experts when machining an impeller.
Keywords: Parameters optimization; End milling; Virtual machining; System integration (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://link.springer.com/10.1007/s10845-019-01489-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:joinma:v:31:y:2020:i:4:d:10.1007_s10845-019-01489-6
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10845
DOI: 10.1007/s10845-019-01489-6
Access Statistics for this article
Journal of Intelligent Manufacturing is currently edited by Andrew Kusiak
More articles in Journal of Intelligent Manufacturing from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().