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Evaluation of process control effectiveness and diagnosis of variation in paper basis weight via multivariate time-series analysis
- Source :
- IEEE Transactions on Automatic Control. 23:702-708
- Publication Year :
- 1978
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 1978.
-
Abstract
- Multivariate time-series techniques are used to analyze the effectiveness of basis-weight control on a paper machine. Basis weight and four other process variables were collected from a production paper machine under three control conditions, ranging from no computer control to the normal operating basis-weight control strategy. Process control effectiveness is measured by comparing the observed output variation with an estimate of the theoretical minimum variation obtained from autoregressive moving-average vector (ARMAV) time-series models. To diagnose sources of variation in the process, the dynamic effects and interactions of the process variables are evaluated using the analysis of dispersion (AD) and spectral estimates obtained from the ARMAV models are used to diagnose sources of periodic variation in the process.
- Subjects :
- Multivariate statistics
Engineering
Basis (linear algebra)
business.industry
Process (computing)
Ranging
Computer Science Applications
Autoregressive model
Control and Systems Engineering
Statistics
Process control
Statistical dispersion
Autoregressive integrated moving average
Electrical and Electronic Engineering
business
Subjects
Details
- ISSN :
- 00189286
- Volume :
- 23
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Automatic Control
- Accession number :
- edsair.doi...........529d78bdb48d33356fe6bd807a9ffe7a