Building blocks for digital twin of reconfigurable machine tools from design perspective
Sihan Huang,
Guoxin Wang and
Yan Yan
International Journal of Production Research, 2022, vol. 60, issue 3, 942-956
Abstract:
Reconfigurable machine tool (RMT) is the core facility of the reconfigurable manufacturing system (RMS), which can provide customised flexibility for RMS through reconfiguration. The reconfiguration of RMT is complicated due to unpredictable changes in demand and the flexibility of RMT, where new RMT should be designed to satisfy the new demand. The concept of digital twin of RMT is introduced to solve complex reconfiguration problems by executing reconfiguration experiments on high-fidelity virtual RMT. Considering the design processes of RMT during reconfiguration, three building blocks for digital twin of RMT should be studied thoroughly, including structure design, configuration generation, and configuration evaluation. First, the structure design of RMT for multi-part families is studied, including the design principles, module division, and design method. Second, the configuration generation process of RMT based on the results of the structure design is analysed, where quantitative description of configuration is proposed to facilitate the generation process. Third, configuration evaluation is presented to confirm the performance of each configuration based on kinematics analysis. Finally, a case study is provided to demonstrate the effectiveness of the proposed three building blocks for digital twin of RMT during reconfiguration to obtain suitable design scheme of RMT.
Date: 2022
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2020.1847340 (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:60:y:2022:i:3:p:942-956
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2020.1847340
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 ().