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The digital twin of the quality monitoring and control in the series solar cell production line
- Source :
- Journal of Manufacturing Systems. 59:127-137
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- With the development of intelligent manufacturing (IM), the Digital twin (DT) has become an important means to the evolution mechanism of the process. Many researchers pay attention on the realization of DT in different industries. Based on the DT and Digital Twin Shop Floor (DTS) model, a novel, high throughput metrology method is proposed in the process quality monitoring and control of the Series Solar Cell Production Line (SSCPL) for detailed performance analysis. The variance of individual loss parameters and their impact on quality performance are quantified and mapped into the virtual space. The nature of their distributions and correlations provide great insights about quality loss mechanisms in process monitoring, helping to prioritize efforts for optimizing the control of the SSCPL in the physical space. Additionally, the parameters can be tied back to the physical space, allowing the data to be used directly for the control in the manufacturing. The data-loop of “Autonomous perception of process parameters - Dynamic behaver mapping - Online monitoring - Online data analysis - Parameters configuration & control” can be obtained in the model. This paper provides an application paradigm for DT and IM.
- Subjects :
- Production line
0209 industrial biotechnology
Computer science
media_common.quotation_subject
Real-time computing
Process (computing)
02 engineering and technology
Variance (accounting)
Work in process
Industrial and Manufacturing Engineering
Metrology
020901 industrial engineering & automation
Hardware and Architecture
Control and Systems Engineering
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Quality (business)
Throughput (business)
Realization (systems)
Software
media_common
Subjects
Details
- ISSN :
- 02786125
- Volume :
- 59
- Database :
- OpenAIRE
- Journal :
- Journal of Manufacturing Systems
- Accession number :
- edsair.doi...........abe2ac0172fec69d406aaa65db7397ff