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Digital twin-driven manufacturing equipment development

delete2023-10-01
delete12
PRE
AI
Y
Yongli Wei
胡天亮 cover
胡天亮 (Tianliang Hu) *
董丽丽 (Lili Dong)
马颂华 cover
马颂华 (Songhua Ma)
DOI:10.1016/j.rcim.2023.102557delete
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Abstract

Abstract

En 中文
Currently, expectations of shorter time-to-market and improved product performance are placing greater de-mands on manufacturing companies. However, the optimization and redesign work between the design stage and the prototype design and manufacturing stage in the traditional product development process lengthens the required product development cycle time (which lasts up to several years in extreme cases). The manufacturing phase for the physical prototype of the product is especially time-consuming and costly. The above reasons make the common product development process increasingly unable to meet the demands of market needs. Motivated by this need, the digital twin (DT)-driven manufacturing equipment (ME) development method is studied in this paper. This method contains three main core elements of the design method based on axiomatic design (AD) theory, the construction of DT models related to ME development, and DT-based validation analysis. The advantage of this method is that it can incorporate the physical prototype manufacturing stage into the digital space with the high-fidelity model provided by the DT technology, which ensures the confidentiality of the design scheme validation while freeing it from the physical prototype stage. This avoids the cost of physical prototyping, shortens the product development cycle, and improves the efficiency of new ME development. At the end of this paper, a case study of the development of a virtual machining dynamic performance test bench (VM-TB) is carried out to show the implementation flow of this proposed method, and its operability and effectiveness are verified.
Keywords:
Digital Twin (DT)
Evolution mechanism
Manufacturing equipment (ME)
CNC machine tools (CNCMT)

Journal

R
Robotics and Computer-Integrated Manufacturing
IF:
11.4
Papers:
3.3K
Citations:
1.3W

Organization

U
university of health & rehabilitation sciences
Scholars:
758
Papers: 540
Citations: 1
S
shandong university
Scholars:
9.1W
Papers: 6.3W
Citations: 94
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