Non-productive time optimization for 5-axis EDM drilling using HVNTS algorithm
Jian Wang,
Xue-Cheng Xi,
Ling Qin,
Ya-Ou Zhang and
Wan-Sheng Zhao
International Journal of Production Research, 2021, vol. 59, issue 16, 5068-5082
Abstract:
This paper presents a hybrid variable neighbourhood search/tabu search (HVNTS) method and a neighbourhood generation strategy called pairwise inter-reshuffle (PIR) for process planning of 5-axis electrical discharge machining (EDM) drilling processes, which aims to minimize the total non-productive time of the machining process, including tool travelling time, tool switching time and Z-axis compensation moving time. To obtain a mathematical model of the non-productive time, a kinematic transformation and a Chebyshev distance function are then utilized. To solve the mathematical model efficiently, an HVNTS algorithm is applied as the model has a large number of 0–1variables. To improve the solution quality, the PIR method and a dynamic neighbourhood strategy are applied simultaneously and verified. The obtained simulation results demonstrate that the proposed basic and the improved HVNTS have a significant contribution in optimizing the non-productive time of the 5-axis EDM drilling process effectively.
Date: 2021
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2020.1779961 (text/html)
Access to full text is restricted to subscribers.
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:taf:tprsxx:v:59:y:2021:i:16:p:5068-5082
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2020.1779961
Access Statistics for this article
International Journal of Production Research is currently edited by Professor A. Dolgui
More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().