Journal
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
Volume 53, Issue 15, Pages 4594-4613Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2015.1005247
Keywords
Bayesian method; multistage manufacturing process; engineering model; ramp-up phase; parameter estimation
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Funding
- National Natural Science Foundation of China [51275558]
- National Key Science and Technology Research Program of China [2014ZX04015-021]
- Shanghai Rising-Star Program [13QA1402100]
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Process monitoring of full mass production phase of multistage manufacturing processes (MMPs) has been successfully implemented in many applications; however, monitoring of ramp-up phase of MMPs is often more difficult to conduct due to the limited information to establish valid process control parameters (such as mean and variance). This paper focuses on the estimation of the process control parameters used for monitoring scheme design of ramp-up phase of MMPs. An engineering model of variation propagation of an MMP is developed and reconstructed to a linear model, establishing a relationship between the error sources and the variation of product characteristics. Based on the developed linear model, a two-step Bayesian method is proposed to estimate the process control parameters. The performance of the proposed Bayesian method is validated with simulation data and real-world data, and the results demonstrate that the proposed method can effectively estimate process parameters during ramp-up phase of MMP.
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